The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly ― and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
This document discusses data governance and data architecture. It introduces data governance as the processes for managing data, including deciding data rights, making data decisions, and implementing those decisions. It describes how data architecture relates to data governance by providing patterns and structures for governing data. The document presents some common data architecture patterns, including a publish/subscribe pattern where a publisher pushes data to a hub and subscribers pull data from the hub. It also discusses how data architecture can support data governance goals through approaches like a subject area data model.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
This document discusses data governance and data architecture. It introduces data governance as the processes for managing data, including deciding data rights, making data decisions, and implementing those decisions. It describes how data architecture relates to data governance by providing patterns and structures for governing data. The document presents some common data architecture patterns, including a publish/subscribe pattern where a publisher pushes data to a hub and subscribers pull data from the hub. It also discusses how data architecture can support data governance goals through approaches like a subject area data model.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Why an AI-Powered Data Catalog Tool is Critical to Business SuccessInformatica
Imagine a fast, more efficient business thriving on trusted data-driven decisions. An intelligent data catalog can help your organization discover, organize, and inventory all data assets across the org and democratize data with the right balance of governance and flexibility. Informatica's data catalog tools are powered by AI and can automate tedious data management tasks and offer immediate recommendations based on derived business intelligence. We offer data catalog workshops globally. Visit Informatica.com to attend one near you.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
This document discusses the development of a data strategy for an organization. It begins by introducing the presenter and organization. It then covers why a data strategy is needed to address common data issues. The strategy should define what the data team will and will not do. Developing the strategy requires gathering information, consulting other teams, and linking it to the organization's mission. Key aspects of the strategy include objectives, principles, delivery areas, and ensuring it is concise enough to be accessible and remembered.
The Role of Data Governance in a Data StrategyDATAVERSITY
A Data Strategy is a plan for moving an organization towards a more data-driven culture. A Data Strategy is often viewed as a technical exercise. A modern and comprehensive Data Strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The people aspect includes governance, the execution and enforcement of authority, and formalization of accountability over the management of the data.
In this RWDG webinar, Bob Seiner will share where Data Governance fits into an effective Data Strategy. As part of the strategy, the program must focus on the governance of people, process, and technology fixated on treating and leveraging data as a valued asset. Join us to learn about the role of Data Governance in a Data Strategy.
Bob will address the following in this webinar:
- A structure for delivery of a Data Strategy
- How to address people, process, and technology in a Data Strategy
- Why Data Governance is an important piece of a Data Strategy
- How to include Data Governance in the structure of the policy
- Examples of how governance has been included in a Data Strategy
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
The document discusses data governance and why it is an imperative activity. It provides a historical perspective on data governance, noting that as data became more complex and valuable, the need for formal governance increased. The document outlines some key concepts for a successful data governance program, including having clearly defined policies covering data assets and processes, and establishing a strong culture that values data. It argues that proper data governance is now critical to business success in the same way as other core functions like finance.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
The document discusses the challenges and opportunities of data-driven marketing based on a global survey of over 2,200 marketers. Some key findings include:
1) Marketers want an integrated view of customers by combining online and offline data sources, but many struggle with data integration challenges.
2) While most marketers feel pressure to be more data-driven, over 40% give their department's use of data low grades of C or below.
3) Marketers recognize opportunities to better leverage data insights, but lack of processes to operationalize insights into marketing decisions is a major obstacle.
4) Hiring marketing data scientists is one way companies are addressing skills gaps, and departments with these roles tend
This document discusses how predictive analytics can help sales and marketing organizations overcome challenges posed by growing multi-channel marketing strategies and big data. Predictive analytics provides the ability to analyze historical sales and marketing data to determine how customers are likely to behave in the future. This allows companies to improve key operations like customer retention, acquisition, cross-selling, and price optimization. The document outlines best practices for building predictive models, including understanding business needs, preparing data, modeling, and evaluating results. It also highlights the benefits of WebFOCUS RStat for predictive analytics and a success story at a discount retailer.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Why an AI-Powered Data Catalog Tool is Critical to Business SuccessInformatica
Imagine a fast, more efficient business thriving on trusted data-driven decisions. An intelligent data catalog can help your organization discover, organize, and inventory all data assets across the org and democratize data with the right balance of governance and flexibility. Informatica's data catalog tools are powered by AI and can automate tedious data management tasks and offer immediate recommendations based on derived business intelligence. We offer data catalog workshops globally. Visit Informatica.com to attend one near you.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
This document discusses the development of a data strategy for an organization. It begins by introducing the presenter and organization. It then covers why a data strategy is needed to address common data issues. The strategy should define what the data team will and will not do. Developing the strategy requires gathering information, consulting other teams, and linking it to the organization's mission. Key aspects of the strategy include objectives, principles, delivery areas, and ensuring it is concise enough to be accessible and remembered.
The Role of Data Governance in a Data StrategyDATAVERSITY
A Data Strategy is a plan for moving an organization towards a more data-driven culture. A Data Strategy is often viewed as a technical exercise. A modern and comprehensive Data Strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The people aspect includes governance, the execution and enforcement of authority, and formalization of accountability over the management of the data.
In this RWDG webinar, Bob Seiner will share where Data Governance fits into an effective Data Strategy. As part of the strategy, the program must focus on the governance of people, process, and technology fixated on treating and leveraging data as a valued asset. Join us to learn about the role of Data Governance in a Data Strategy.
Bob will address the following in this webinar:
- A structure for delivery of a Data Strategy
- How to address people, process, and technology in a Data Strategy
- Why Data Governance is an important piece of a Data Strategy
- How to include Data Governance in the structure of the policy
- Examples of how governance has been included in a Data Strategy
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
The document discusses data governance and why it is an imperative activity. It provides a historical perspective on data governance, noting that as data became more complex and valuable, the need for formal governance increased. The document outlines some key concepts for a successful data governance program, including having clearly defined policies covering data assets and processes, and establishing a strong culture that values data. It argues that proper data governance is now critical to business success in the same way as other core functions like finance.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
The document discusses the challenges and opportunities of data-driven marketing based on a global survey of over 2,200 marketers. Some key findings include:
1) Marketers want an integrated view of customers by combining online and offline data sources, but many struggle with data integration challenges.
2) While most marketers feel pressure to be more data-driven, over 40% give their department's use of data low grades of C or below.
3) Marketers recognize opportunities to better leverage data insights, but lack of processes to operationalize insights into marketing decisions is a major obstacle.
4) Hiring marketing data scientists is one way companies are addressing skills gaps, and departments with these roles tend
This document discusses how predictive analytics can help sales and marketing organizations overcome challenges posed by growing multi-channel marketing strategies and big data. Predictive analytics provides the ability to analyze historical sales and marketing data to determine how customers are likely to behave in the future. This allows companies to improve key operations like customer retention, acquisition, cross-selling, and price optimization. The document outlines best practices for building predictive models, including understanding business needs, preparing data, modeling, and evaluating results. It also highlights the benefits of WebFOCUS RStat for predictive analytics and a success story at a discount retailer.
What are you measuring - 3 approaches to data-driven marketingJulie Doyle
Three association marketing professionals discuss how they use data-driven marketing approaches:
1) They analyze various types of member data like online interactions, purchase history, and demographics to guide marketing decisions.
2) Data is used to prioritize marketing goals by measuring the impact of initiatives on key metrics like registrations and downloads.
3) Associations educate themselves on data analysis through experimentation, reading industry publications, and having dedicated staff with analytics expertise.
ClickZ/Fospha: The State of Marketing Measurement, Attribution, and Data Mana...Clark Boyd
This report covers:
The data challenges marketers are confronting today
The business impact of a complex (and oft-misunderstood) data culture
The role of marketing intelligence software in a modern organization
How to define and use metrics like customer lifetime value
The features marketers wish their current technologies had
How to assess your own company’s data maturity
A new approach to agile, accessible marketing measurement
This document provides an overview and guide to data management for modern marketers. It discusses the importance of data management and outlines strategies for collecting cross-channel customer data, defining target audiences, and activating meaningful marketing across channels. The guide emphasizes centralizing data from various sources, conducting data audits to understand goals and identify gaps, and using unified customer profiles to deliver personalized experiences.
The document discusses key trends in data management identified by global research. It finds organizations are increasingly focused on understanding customers as individuals to offer personalized service. However, inaccurate and incomplete data undermines customer experience for many. Experts recommend using data to develop a single view of each customer by linking all available information. This would allow real-time insights and responses tailored to individual customers, improving relationships and sales. Achieving accurate and comprehensive customer data remains a challenge for most organizations.
The document discusses how advanced analytics are disrupting marketing by enabling more targeted and personalized strategies. It provides an introduction to an e-book compiling essays from data analytics experts in different fields and industries about how they are applying big data analytics. The essays are grouped into five sections covering topics like how analytics are changing businesses, new technology platforms, industry examples, research applications, and marketing strategies.
Avention 7 Common Challenges Companies Have With Business DataAvention
Companies that effectively use data-driven sales and marketing tools are six times more likely to drive profitability. Integrating data from internal and external sources can provide valuable insights for sales teams. Some common challenges companies face with data include having information that is too shallow, having too much data without a plan for management, and only using basic prospect information. Solutions involve incorporating additional external data, designating a dedicated data management team, understanding what information sales and marketing teams need, recognizing behavioral triggers that can help salespeople, and using analytics solutions to identify key business signals and drive results.
In December 2017, the Winterberry Group in partnership with DMA and IAB’s Data Center of Excellence, published “The State of Data 2017,” which revealed that in 2017, U.S.-based marketers, publishers, and other data users invested $20.29 billion on third-party audience data and related services and solutions.
This follow-up report published by the same groups, is aimed at showing how those organizations are applying those investments to capitalize on the value inherent in data as a potential driver of decisioning, messaging and superior customer experiences across all advertising and marketing functions.
Predictive marketing is a data-driven process that uses customer data to build predictive models and send personalized messages. It helps identify in-market buyers earlier, improve engagement over the customer lifecycle, and increase conversion rates. The document discusses how predictive marketing works, leveraging various data sources to send targeted messages. It also provides best practices such as starting small, testing predictive approaches, and maintaining human touch.
Adweek 2019 Data-Driven Marketing at the CrossroadsMark Osborne
Survey of over 300 Marketing Leaders for trends and insights on data-driven marketing, includes trends in technology investment, challenges to implementation of data-driven marketing strategies, prioritization of objectives, challenges with improving the customer experience, impacts of privacy and compliance and forward looking predictions
The document discusses how big data is changing marketing by providing unprecedented tools to understand consumer behavior with more precision. Marketers who use big data at least 50% of the time are more likely to exceed their goals and see benefits like improved ROI and insights into customer behavior compared to those using big data less. While executives believe they are using big data sufficiently, the data shows room for more use of big data in marketing decisions. Machine learning systems that can quickly generate insights from changing consumer data will become increasingly important for marketing success.
The document provides guidance on best practices for using data in marketing campaigns. It emphasizes that a continuous cycle of data planning, analysis, management, delivery and reporting should drive the campaign process. Marketers need to ask questions about current data, data collection tools, integrating different data sources, adhering to legislation, and developing an overall data strategy. Building a data strategy involves researching the market, educating stakeholders, enhancing existing data, and exploiting data to its full potential.
This document discusses how data science can help solve problems in marketing. It provides examples of common marketing problems such as customer segmentation, predictive modeling, personalization, optimization, and A/B testing. It then explains how data science techniques like analyzing customer data can help companies develop more effective marketing strategies by providing insights into customer behavior and preferences. Specifically, data science allows companies to identify customer segments, predict future behaviors, deliver personalized messages, maximize marketing efforts, and test strategies. Overall, the document argues that data science is a useful tool for marketing because it can help companies make more informed decisions by analyzing customer data.
The document discusses predictions from 10 thought leaders on where data-driven marketing insights will have the biggest impact in 2016. Common themes included a greater focus on measuring the entire customer journey, better integration of disparate data sources, and using data to better predict campaign outcomes and improve customer experience. Experts also predicted more personalized messaging tailored to individuals using marketing analytics, and a focus on metrics to measure and improve customer engagement, retention, and lifetime value.
This document provides an overview of marketing trends for 2014, including search, data, real-time marketing, and social media. Some key points:
- Search is diversifying beyond just keywords to understand context and meaning. Providers value diversity, freshness, and relevance of content.
- Data is more available than ever, and companies that use data analytics are more productive and profitable. 2014 is the time to start analyzing collected data.
- Real-time marketing involves both planned responses to current events and optimizing efforts based on what's happening now. Preparation and legal approval are important.
- Social media integration is increasing, and community management will be important to connect with customers and bring feedback into organizations. Low
The document discusses 20 marketing trends for 2022. Some of the key trends include:
1. Consumer values and expectations have shifted drastically due to the COVID pandemic, requiring brands to strategize and create new strategies to meet these changes.
2. Marketers must focus on building their first-party data strategies and personalizing experiences as third-party cookies are being phased out.
3. Research is becoming more democratized, with insights being generated through collaboration across organizations rather than isolated reports.
4. Testing and optimization are becoming ingrained in marketing organizations through increased investment in testing technology and dedicated teams.
The document discusses how marketers can improve their digital campaigns through analytics. It argues that most marketers focus on reporting metrics rather than using analytics to improve campaigns. To achieve success, marketers must go beyond launch and measurement to continuously reflect on analytics data, react with changes, and repeat the process. Analytics now provide insights into user behavior that can be used to personalize experiences and optimize websites and campaigns for better performance and results over the long run.
Tenha insights através de análises precisas
‣Multi-Touch Attribution
‣Relatórios de Uninstall e Re-Installs
‣Taxa de retenção acumulada desde o dia da instalação
‣Compare vários KPIs simultaneamente para uma análise mais profunda
‣Janela de lookback ilimitada
‣Veja o LTV dos usuários orgânicos
‣Encontre informações importantes para otimizar suas campanhas
Os 10 mandamentos da otimização no FacebookLucas Modesto
1) O documento fornece 10 mandamentos para otimizar campanhas no Facebook, focando em objetivos, pacing, fase de aprendizagem, audiências, posicionamento, lance, eventos, anúncios, testes e aprendizagem e apêndice.
2) Alguns pontos-chave incluem alinhar os KPIs com o objetivo da campanha, garantir entrega uniforme do orçamento, esperar a fase de aprendizagem concluir antes de fazer alterações, usar audiências maiores para dar mais liberdade ao algoritmo e
Personalize sua estratégia de mídia do YouTubeLucas Modesto
Este documento fornece um guia sobre como usar a ferramenta Reach Planner para planejar campanhas de vídeo no YouTube de maneira eficaz. Ele discute formatos de anúncios, soluções para atingir objetivos, recomendações de uso e uma demonstração prática. O documento sugere que uma combinação de formatos que priorizam alcance, exposição em conteúdo popular e formatos para engajamento podem otimizar campanhas para atingir altos níveis de alcance e visualizações.
Índice de Maturidade Digital dos BrasileirosLucas Modesto
1) O documento apresenta os resultados de uma pesquisa sobre o Índice de Maturidade Digital dos brasileiros realizada pela Google e McKinsey, mapeando as habilidades digitais dos brasileiros em cinco dimensões: acesso, uso, segurança, cultura digital e criação.
2) Foi observado que as desigualdades no domínio de competências digitais espelham desigualdades de gênero, raça e idade no país, com mulheres, jovens e pessoas de baixa renda tendo menor índice de digital
Dicas de produtividade dos especialistas em reuniões do GoogleLucas Modesto
Este documento fornece dicas de especialistas em reuniões do Google para tornar as reuniões mais eficientes e produtivas. Algumas dicas incluem considerar alternativas à reunião se possível, limitar o número de participantes a sete pessoas, sempre enviar a pauta com antecedência e fazer um acompanhamento após a reunião para garantir que as tarefas definidas sejam concluídas.
O documento discute a origem e evolução do festival South by Southwest (SXSW) em Austin, Texas. Começou em 1986 como um festival de música country indie e cresceu para abranger outros assuntos como tecnologia e inovação. Explica como Austin se tornou um centro cultural alternativo no Texas conservador e como o SXSW capturou o espírito de descoberta e avanço cultural da era contemporânea.
AppsFlyer & Google uniram forças para te ajudar a compreender toda a jornada do marketing de aplicativos e desvendar os segredos que serão os próximos 'game changers' em sua jornada de aquisição e retenção
No "APPrende" você irá conhecer mais sobre estratégias de marketing mobile através do UAC, como analisar seus dados de atribuição e engajar a sua base através da plataforma AppsFlyer, e como melhorar a experiência do usuário em seus anúncios conectando arte e science.
The math behind Smadex
The limits of Fixed CPA acquisition
Smadex analyzes hundreds of first and third party data points, defining a Predicted LTV score for each user characteristic, feeding its algorithm to create a acquisition portfolio strategy reaching each cluster of users according to its expected value to the business and the predicted market Customer Acquisition Cost (mCAC).
This way, you pay for the real valueof each user and you maximize scale, while keeping campaigns limited by your targeted CPA goal .
Most advanced App Marketers are looking for two things: a profitable Customer Acquisition Cost and scale. The typical programmatic algorithm is built around bidding for impressions, trying to get as many as possible as long the CPA goal is reached. This usually means advertisers end up paying more for users that generate lower value to their business and not pushing enough for users of higher value (and higher Acquisition Cost).
How Portfolio-based bidding works
Playbook Criativo: saiba como criar campanhas personalizadas no Dia do Consum...Lucas Modesto
Dia do Consumidor cresce a cada ano, e os dados mostram grandes oportunidades para a data em 2019. Mas como os anunciantes podem criar ofertas mais interessantes e únicas para esse, que já é um dos maiores momentos do varejo?
O Zoo, área criativa do Google para marcas e agências, criou o Playbook Criativo do Dia do Consumidor. Com ele, você conhece oportunidades de comunicação para a data e encontra maneiras concretas de transformar suas ofertas em mensagens personalizadas.
“Datas de varejo são altamente competitivas, mas a disputa entre marcas está concentrada em preço e ofertas”, diz Caio Franchi, diretor criativo do The Zoo no Google Brasil. “Queremos provocá-los a ampliarem a comunicação e a criarem ofertas mais parecidas com histórias, e histórias que sejam relevantes para cada pessoa. O storytelling é mais importante do que nunca para gerar interesse e conectar pessoas a produtos que antes nem consideravam.”
PLAN AND GO 2019 - Building smart strategies togetherLucas Modesto
Este documento fornece dicas e insights para ajudar profissionais de marketing a planejarem suas estratégias de comunicação para 2019, destacando o potencial das soluções do Facebook. Ele discute como as pessoas estão cada vez mais conectadas através de dispositivos móveis e como inspirar consumidores usando diferentes plataformas da família do Facebook de forma integrada.
4 things that brands are doing to win in the new video landscapeLucas Modesto
Back in the 1950s, when TV was first gaining popularity as an entertainment medium, advertisers had it fairly easy. With only three networks and one viewing screen, the audience was highly concentrated. To this day, I Love Lucy still holds the record for the highest Nielsen average for a TV season—67.3. Families around America tuned in weekly for a season that started with Lucy battling a conveyor belt at a chocolate factory and eventually welcomed Ricky Jr. to the world.1
Because of this concentrated TV viewing audience, advertisers knew when, where and what the whole country was watching without the need for sophisticated technology, data collection, or analysis.
Today’s television viewing landscape is very different. While TV screens still account for 91% of our viewing time,2 we’re now able to watch great video content wherever, whenever and however we want. According to Nielsen, traditional TV watching has declined 44% for viewers 18-24 years old and 32% for viewers 25-34 years old over the past five years.3 Meanwhile, streaming video is on the rise. In 2017, 59% of American households had a streaming video subscription, compared to just 38% in 2014.4
Mobility Index 2018 - Metodologia PontomobiLucas Modesto
O Mobility Index se propõe a medir o grau de mobilidade das 325 marcas do mercado brasileiro. A pesquisa analisa a presença destas marcas nas diferentes soluções mobile para consumidores finais, a estratégia aplicada ao negócio de cada uma e como elas estão estruturadas em relação as características analisadas.
Modelos de Atribuição em Publicidade DigitalLucas Modesto
O documento discute os desafios da fraude na publicidade digital móvel e como a plataforma Adjust tem trabalhado para resolvê-los ao longo dos anos. Inicialmente, eles implementaram filtros para rejeitar atribuições de IPs associados a datacenters ou proxies, economizando milhões para anunciantes. Posteriormente, adicionaram proteções contra spam de cliques e técnicas mais sofisticadas como SDK spoofing e click injections. A Adjust continua aperfeiçoando suas soluções para manter o crescimento das taxas de fraude sob cont
This document provides an overview of audience segments that can be targeted for advertising purposes across various platforms and categories. It includes demographic segments like age and gender, life events segments, in-market audiences for different product categories, and affinity audiences for things like beauty, food, home, media, shopping, health, travel and automotive interests. Platform availability may vary by segment and country.
David vs Golias como o aplicativo hopper esta ganhando o mercado dos gigantes...Lucas Modesto
Simon é o head de aquisição de usuários na Hopper, travel app mais instalado nos USA em 2018. Com um forte foco em automação e priorização, Simon construiu uma pequena equipe técnica que é capaz de executar campanhas hiper direcionadas em escala nos maiores canais de UA.
O AppsFlyer Performance Index, que determina o padrão da indústria, está de volta na edição VII, classificando as principais performances de fontes de mídia mobile durante o primeiro semestre de 2018.
O que há de novo na Edição VII:
Categoria deep-dive:
Estamos animados em compartilhar os índices de gênero cobrindo Casual, Midcore & Estratégia, e Cassino & Apostas. Em jogos de não-apostas nós agrupamos as categorías Vida & Cultura, Utilitários e Apps de Compra.
O índice de crescimento:
Para entender melhor as mudanças regionáis no mercado de mídias, apresentamos o índice sobre o crescimento ao longo do tempo.
Rankings da parte de baixo:
Aproveitando o crescimento Massivo, Austrália e Nova Zelandia, são as novas áreas adicionadas ao índice, o que faz o índice cobrir 9 regiões pelo mundo.
Desafios do negócio - O Facebook como aliadoLucas Modesto
O documento discute os desafios do varejo no Brasil e como o Facebook pode ajudar empresas a maximizar vendas no fim de ano. Em três frases:
1) O varejo brasileiro enfrenta desafios como baixo crescimento econômico mas o e-commerce continua crescendo.
2) O consumidor brasileiro usa cada vez mais o mobile para tomar decisões de compra, se inspirando no Facebook e Instagram.
3) O Facebook pode ajudar marcas a estarem presentes na jornada de compra dos consumidores, desde a desc
1. O documento analisa as tendências e expectativas dos consumidores brasileiros em relação à Black Friday de 2018. 2. As compras de categorias como alimentos, bebidas e produtos de limpeza ainda são majoritariamente realizadas em lojas físicas, porém há grande potencial para crescimento das vendas online nestas categorias. 3. Os anúncios em folhetos, televisão e online influenciam bastante as compras, sendo os folhetos e televisão mais relevantes para consumidores mais velhos e anúncios online mais importantes para
1. The document discusses how disruptive companies succeed by giving people what they don't know they want in new ways. It outlines a three stage process for disruptors: prove it, sell it, and scale it.
2. The stages involve first demonstrating business value, then structuring the business for efficiencies on platforms like Facebook to drive growth, and finally innovating tactics and business models to sustain scale.
3. Case studies are provided of companies that optimized for these stages on Facebook to lower customer acquisition costs, increase conversions and sales. The document stresses the need for constant innovation to maintain scale.
Capstone Project: Luxury Handloom Saree Brand
As part of my college project, I applied my learning in brand strategy to create a comprehensive project for a luxury handloom saree brand. Key aspects of this project included:
- *Competitor Analysis:* Conducted in-depth competitor analysis to identify market position and differentiation opportunities.
- *Target Audience:* Defined and segmented the target audience to tailor brand messages effectively.
- *Brand Strategy:* Developed a detailed brand strategy to enhance market presence and appeal.
- *Brand Perception:* Analyzed and shaped the brand perception to align with luxury and heritage values.
- *Brand Ladder:* Created a brand ladder to outline the brand's core values, benefits, and attributes.
- *Brand Architecture:* Established a cohesive brand architecture to ensure consistency across all brand touchpoints.
This project helped me gain practical experience in brand strategy, from research and analysis to strategic planning and implementation.
Basic Management Concepts., “Management is the art of getting things done thr...DilanThennakoon
The managers achieve organizational objectives by getting work from
others and not performing in the tasks themselves.
Management is an art and science of getting work done through people.
It is the process of giving direction and controlling the various activities
of the people to achieve the objectives of an organization Management is a universal process in all organized, social and economic activities. Wherever
there is human activity there is management.
Management is a vital aspect of the economic life of man, which is an organized group activity. A
central directing and controlling agency is indispensable for a business concern. The productive
resources –material, labour, capital etc. are entrusted to the organizing skill, administrative ability
and enterprising initiative of the management. Thus, management provides leadership to a
business enterprise. Without able managers and effective managerial leadership the resources of
production remain merely resources and never become production. Management occupies such an
important place in the modern world that the welfare of the people and the destiny of the country
are very much influenced by it.
1.2 MEANING OF MANAGEMENT
Management is a technique of extracting work from others in an integrated and co-ordinated
manner for realizing the specific objectives through productive use of material resources.
Mobilising the physical, human and financial resources and planning their utilization for business
operations in such a manner as to reach the defined goals can be benefited to as management.
1.3 DEFINITION OF MANAGEMENT
Management may be defined in many different ways. Many eminent authors on the subject have
defined the term "management". Some of these definitions are reproduced below:
In the words of George R Terry - "Management is a distinct process consisting of planning,
organising, actuating and controlling performed to determine and accomplish the objectives by the
use of people and resources".
According to James L Lundy - "Management is principally the task of planning, co¬ordinating,
motivating and controlling the efforts of others towards a specific objective",
In the words of Henry Fayol - "To manage is to forecast and to plan, to organise, to command, to
co-ordinate and to control".
According to Peter F Drucker - "Management is a multipurpose organ that manages a business and
manages managers and manages worker and work".
In the words of J.N. Schulze - "Management is the force which leads, guides and directs an
organisation in the accomplishment of a pre-determined object".
In the words of Koontz and O'Donnel - "Management is defined as the creation and maintenance
of an internal environment in an enterprise where individuals working together in groups can
perform efficiently and effectively towards the attainment of group goals".
According to Ordway Tead - "Management is the process and agency which directs and guides the
operations of an organisation in realising of established aim
AI Best Practices for Marketing HUG June 2024Amanda Farrell
During this presentation, the Nextiny marketing team reviews best practices when adopting generative AI into content creation. Join our HUG community to register for more events https://events.hubspot.com/sarasota/
Efficient Website Management for Digital Marketing ProsLauren Polinsky
Learn how to optimize website projects, leverage SEO tactics effectively, and implement product-led marketing approaches for enhanced digital presence and ROI.
This session is your key to unlocking the secrets of successful digital marketing campaigns and maximizing your business's online potential.
Actionable tactics you can apply after this session:
- Streamlined Website Management: Discover techniques to streamline website development, manage day-to-day operations efficiently, and ensure smooth project execution.
- Effective SEO Practices: Gain valuable insights into optimizing your website for search engines, improving visibility, and driving organic traffic to your digital assets.
- Leverage Product-Led Marketing: Explore strategies for incorporating product-led marketing principles into your digital marketing efforts, enhancing user engagement and driving conversions.
Don't miss out on this opportunity to elevate your digital marketing game and achieve tangible results!
Evaluating the Effectiveness of Women-Focused MarketingHighViz PR
Women centric marketing is a vital part in reaching one of the most influential groups of consumers. Here is a guide to know and measure the impact of women-centric marketing efforts-
The digital marketing industry is changing faster than ever and those who don’t adapt with the times are losing market share. Where should marketers be focusing their efforts? What strategies are the experts seeing get the best results? Get up-to-speed with the latest industry insights, trends and predictions for the future in this panel discussion with some leading digital marketing experts.
INTRODUCTION TO SEARCH ENGINE OPTIMIZATION (SEO).pptxGiorgio Chiesa
This presentation is recommended for those who want to know more about SEO. It explains the main theoretical and practical aspects that influence the positioning of websites in search engines.
Empowering Influencers: The New Center of Brand-Consumer Dynamics
In the current market landscape, establishing genuine connections with consumers is crucial. This presentation, "Empowering Influencers: The New Center of Brand-Consumer Dynamics," explores how influencers have become pivotal in shaping brand-consumer relationships. We will examine the strategic use of influencers to create authentic, engaging narratives that resonate deeply with target audiences, driving success in the evolved purchase funnel.
Build marketing products across the customer journey to grow your business and build a relationship with your customer. For example you can build graders, calculators, quizzes, recommendations, chatbots or AR apps. Things like Hubspot's free marketing grader, Moz's site analyzer, VenturePact's mobile app cost calculator, new york times's dialect quiz, Ikea's AR app, L'Oreal's AR app and Nike's fitness apps. All of these examples are free tools that help drive engagement with your brand, build an audience and generate leads for your core business by adding value to a customer during a micro-moment.
Key Takeaways:
Learn how to use specific GPTs to help you Learn how to build your own marketing tools
Generate marketing ideas for your business How to think through and use AI in marketing
How AI changes the marketing game
Breaking Silos To Break Bank: Shattering The Divide Between Search And SocialNavah Hopkins
At Mozcon 2024 I shared this deck on bridging the divide between search and social. We began by acknowledging that search-first marketers are used to different rules of engagement than social marketers. We also looked at how both channels treat creative, audiences, bidding/budgeting, and AI. We finished by going through how they can win together including UTM audits, harvesting comments from both to inform creative, and allowing for non-login forums to be part of your marketing strategy.
I themed this deck using Baldur's Gate 3 characters: Gale as Search and Astarion as Social
Lily Ray - Optimize the Forest, Not the Trees: Move Beyond SEO Checklist - Mo...Amsive
Lily Ray, Vice President of SEO Strategy & Research at Amsive, explores optimizing strategies for sustainable growth and explores the impact of AI on the SEO landscape.
Dive deep into the cutting-edge strategies we're employing to revolutionize our web presence in the age of AI-driven search. As Gen Z reshapes the digital realm, discover how we can bridge the generational divide. Unlock the synergistic power of PPC, social media, and SEO, driving unparalleled revenues for our projects.
From Hope to Despair The Top 10 Reasons Businesses Ditch SEO Tactics.pptxBoston SEO Services
From Hope to Despair: The Top 10 Reasons Businesses Ditch SEO Tactics
Are you tired of seeing your business's online visibility plummet from hope to despair? When it comes to SEO tactics, many businesses find themselves grappling with challenges that lead them to abandon their strategies altogether. In a digital landscape that's constantly evolving, staying on top of SEO best practices is crucial to maintaining a competitive edge.
In this blog, we delve deep into the top 10 reasons why businesses ditch SEO tactics, uncovering the pain points that may resonate with you:
1. Algorithm Changes: The ever-changing algorithms can leave businesses feeling like they're chasing a moving target. Search engines like Google frequently update their algorithms to improve user experience and provide more relevant search results. However, these updates can significantly impact your website's visibility and ranking if you're not prepared.
2. Lack of Results: Investing time and resources without seeing tangible results can be disheartening. The absence of immediate results often leads businesses to lose faith in their SEO strategies. It's important to remember that SEO is a long-term game that requires patience and consistent effort.
3. Technical Challenges: From site speed issues to complex metadata implementation, technical hurdles can be daunting. Overcoming these challenges is crucial for SEO success, as technical issues can hinder your website's performance and user experience.
4. Keyword Competition: Fierce competition for top keywords can make it hard to rank effectively. Businesses often struggle to find the right balance between targeting high-traffic keywords and finding less competitive, niche keywords that can still drive significant traffic.
5. Lack of Understanding of SEO Basics: Many businesses dive into the complex world of SEO without fully grasping the fundamental principles. This lack of understanding can lead to several issues:
Keyword Awareness: Failing to recognize the importance of keyword research and targeting the right keywords in content.
On-Page Optimization: Ignorance regarding crucial on-page elements such as meta tags, headers, and content structure.
Technical SEO Best Practices: Overlooking essential aspects like site speed, mobile responsiveness, and crawlability.
Backlinks: Not understanding the value of high-quality backlinks from reputable sources.
Analytics: Failing to track and analyze data prevents businesses from optimizing their SEO efforts effectively.
6. Unrealistic Expectations and Timeframe: Entrepreneurs often fall prey to the allure of quick fixes and overnight success. Unrealistic expectations can overshadow the reality of the time and effort needed to see tangible results in the highly competitive digital landscape. SEO is a long-term strategy, and setting realistic goals is crucial for success.
#SEO #DigitalMarketing #BusinessGrowth #OnlineVisibility #SEOChallenges #BostonSEO
From Hope to Despair The Top 10 Reasons Businesses Ditch SEO Tactics.pptx
Building an integrated data strategy
1. Published
November 2017
How to build an integrated
data strategy for your marketing,
from audience insights to action
The Data-Driven Marketer’s
Strategic Playbook
2. The Data-Driven Marketer’s Strategic Playbook Contents 2 of 40
The new challenges for enterprise marketing
Let data be your guide
Train to transform
The three pillars of your integrated strategy
Pillar 1: The right data
Pillar 2: The right culture
Pillar 3: The right technology
Conclusion
Introduction
04
08
12
18
37
03
Contents
3. If you’ve ever felt like you’re riding a rising flood
of data, but still can’t find the customer insights
you need, you’re not alone.
It can be a real challenge to see the customer
clearly amidst those rushing currents of
customer data ― from mobile apps, television,
in-store visits, websites, and every device in
every hand in the world. Until now there has been
no way to truly gather and integrate omnichannel
data from online and offline sources to
understand the full customer journey.
But recent advancements have revealed a new
approach to gaining deeper audience insights:
building an integrated data strategy. It can help
you see the journeys of every member of your
audience and, more importantly, deliver to them
the customized and relevant messages and
experiences that get results.
We’ll discuss this integrated approach in this
playbook. It’s based in part on interviews with
digital marketing experts and analytics leaders
at a variety of companies, from global healthcare
giants to online-based businesses to financial
services firms.
We have also relied on The Customer Experience
is Written in Data, a 2017 research report created
by Econsultancy in partnership with Google.
Econsultancy surveyed more than 700 marketing
executives at organizations with revenues of
more than $250 million to find out how well they
were using data to guide marketing strategy and
business decisions.
The Econsultancy report focused on how
marketing leaders ― those who significantly
exceeded their top business goal in 2016 ― did
things differently. To summarize the findings:
“Marketing organizations paving the way have
recognized that there are three things that go
better together in today’s world: data, that is
well-integrated to provide a more complete
view of each customer; teams, that increase
collaboration, communication, and sharing of
data and audience insights; and technology,
that unifies analytics and advertising stacks
so marketers can deliver more relevant,
engaging customer experiences and value
to the business.”
Even if you’re not a market leader, there’s
good news: There are now many ways for
any organization to integrate data to better
understand its audience, and act quickly
on it to improve advertising and the
customer experience.
Let’s take a look at how you can not only
tame the tides, but drink deeply from your
business data.
Introduction 3 of 40
Introduction
Casey Carey
Director of Marketing,
Google Analytics 360 Suite and DoubleClick
The Data-Driven Marketer’s Strategic Playbook
4. PA RT 1 .
T H E N E W C H A L L E N G E S F O R
E N T E R P R I S E M A R K E T I N G
Data, data, everywhere…
and not a drop to drink.
5. The new challenges for enterprise marketing
The new challenges for enterprise marketing 5 of 40
of marketing decision makers
said they still struggled to
access or integrate the data
they had needed that year.61%
As 2016 ended, 61% of marketing decision
makers said they still struggled to access or
integrate the data they had needed that year.1
At the same time, only 22% of marketers said
that they lacked the right analytics tools to do
their jobs.
The problem, in other words, lies not in
technology but in the data itself. Companies are
struggling with too much information, too many
sources, and too few ways to use all their data
together to improve the customer experience.
The Data-Driven Marketer’s Strategic Playbook
6. Today’s end-to-end customer experience is almost always a cross-device
experience. Increasingly, that includes voice search assistants or devices
from the Internet of Things. Nearly 90% of marketers, across all types of
organizations, now say that understanding these user journeys across
channels and devices is critical to their success.2
“We get all different types of data feeds from all different types
of platforms,” says Stasha Rosen, senior product analyst at the fashion
and lifestyle website Refinery29. “And it’s essential that we reconcile
them with each other to be able to draw apples-to-apples comparisons.
That can be a real challenge for us or for anyone.”
Trying to swim in a continual flood of cross-device information can be
further complicated when trying to navigate larger or more complex
organizations. And even when that information is available, it has to be
connected in a way that makes sense.
“Having hundreds of millions of terabytes of data
that isn’t actionable really does nothing for me.”
Rob Roy
Chief Digital Officer,
Sprint
In order to gain a complete picture of your audiences, customer
experience, marketing and advertising performance, you may need to
connect multiple stakeholders and data sources. In the Econsultancy
study, leaders were 26% more likely to say that their data and analytics
strategy identifies data owners or key points of contact.
The cross-device challenge
6 of 40The new challenges for enterprise marketingThe Data-Driven Marketer’s Strategic Playbook
7. If the technical challenges of data are large, so are the cultural challenges.
They often keep organizations from adapting to keep pace with evolving
consumer demands.
Once you’ve harnessed the data coming in, you need to analyze it and get it
out ― filtered and actionable ― into hands of decision makers across your
organization. That requires good old-fashioned communication: Turning
complex information into clear recommendations and visualized data that
tells a story and offers usable insights. The road to this kind of growth is
paved with obstacles. Leaders must figure out how to:
All these challenges are why marketing directors and CMOs need a new strategy
for data. They need new ways to integrate data from all their sources ― and to
analyze and understand a more complete view of their audience.
Overcome the fear of failure
Anyone who’s ever worked in an organization of any size can
understand the problem here. Success may be rewarded but
failure is toxic, right? Why risk it? Yet the 2017 Econsultancy
survey shows that this can change. Executives from leading
companies are 55% more likely to say that their marketing
organizations are comfortable with risk.3
Create room to fail
and you create room to innovate and grow.
Get comfortable with ambiguity
Don’t let “analysis paralysis” set in. Great strides have been
made in integrating data, but there will always be outliers.
Empower people to try new ways to experiment and learn
how to bridge gaps in data. Leading marketers — those who
significantly exceeded their top business goal in 2016 — are
45% more likely to say their organizations are quite open
to change.4
Classic culture issues
7 of 40
Break down silos
It’s not just the marketers or analysts in the trenches
who feel the pain of siloed customer data: 86% of senior
executives (SVP or higher) across all types of organizations
agree that eliminating organizational silos is critical to
expanding the use of data and analytics in decision-
making.5
That’s good news: Everyone is on the same page
and responsible for helping make change happen.
Trust data over whims, gut reactions,
and even past experiences
Just because we’ve done it before or it feels right or we like
the sound of that idea, it doesn’t mean it’s the best move for
your business. What does the data say? Even if there are
gaps in your data, can you still get good directional insight?
Is the data perhaps predicting a surprising outcome that
contradicts your intuition? Data-informed decisions pay off:
Nearly two-thirds of leading organizations say that their
executives treat data-driven insights as more valuable than
gut instinct.6
1
3
2
4
The new challenges for enterprise marketingThe Data-Driven Marketer’s Strategic Playbook
8. Data is a key
transformation tool
for all departments. It
has become a core way
of working ... I can’t
imagine a marketing
function without this
capability, attitude,
and infrastructure.”
7
“
PA RT 2 .
L E T D ATA B E Y O U R G U I D E
Vice President, Financial Services
9. Great marketing will always need a veteran hand on the
steering wheel of strategy. But just as a GPS helps with
navigation, today’s data and technology can direct you where
you want to go so much faster.
This is a powerful reason to rely on an integrated data strategy
as your foundation for uncovering audience insights. If the
managers of a team in one office are seeing different data
from those in another office or in the C-suite, you’re driving
down a foggy road indeed.
“While the vision is there, at many companies decisions are
still primarily based on gut,” says Jeff Rasp, director of U.S.
digital strategy at Bayer Consumer Health. “Decisions in the
past haven’t been fully informed because marketers have
been looking at all their data sources separately. It takes
integrated data for marketers to make those decisions truly
based on data and impact.”
In response, Bayer is building its own source of truth: a
shared pool of integrated data that aggregates not only all
the data from its analytics platform, but also television data,
competitive data, and social data. In other words: all the
things that didn’t come together in the past. Now Bayer can
make informed decisions based on the combined impact of
channels, not just a siloed view of each.
Let data be your guide
9 of 40Let data be your guideThe Data-Driven Marketer’s Strategic Playbook
Nearly 2/3 of leading
organizations say that
their executives treat
data-driven insights
as more valuable than
gut instinct.
Econsultancy and Google,
“The Customer Experience is Written in Data”,
May 2017, U.S.
2/3
10. 10 of 40
One of the best things your business can do is to uncover
your most valuable customer segments and look at
how they behave. With the right data you can create
personalized messages and experiences for different
customer groups, such as audiences with the highest
potential lifetime value, or even for individuals based on
where they are in their journey. It’s easy to set up ads for,
say, people who looked at mountain bikes on your site
but left without putting anything in their cart.
Organize
Once your data house is in order, you can really start to see
a more complete picture of your audience. That lets your
marketing team do more as they:
Even a few years ago, last-click attribution was a big
step forward. Today it would be a big step backward for
marketing leaders. Data-driven attribution can not only
show you the customer journey, but answer questions like
“What’s really contributing to our conversions?” and “How
can we better allocate our budget instead of saying ‘This
is what we did last year?’”
Measure
Good data lets you go beyond ads to create a better
website experience. Why should a first-time visitor to your
retail clothing site have the same experience — or receive
the same offer — as a loyal user who visits every month
to check out a particular brand of shoes? Audience data
can help you create a custom experience with tailored
visuals and more powerful messages for each.
Design
With today’s always-on consumer, marketers face
an even bigger challenge when trying to answer the
perennial question: How do I reach the right person, at the
right time, with the right message? The truth is, today’s
digital analytics can deliver data and audience insights
to help you optimize experiences in near-real time.
As visits are made, as purchases happen, as messages
are seen (or not seen), your messaging, ad placements,
and customer experiences should be adjusting
as the data flows in.
Reach
Let data be your guideThe Data-Driven Marketer’s Strategic Playbook
11. 11 of 40
The Econsultancy report bears this out. “The [market
leader] strategies themselves reflect their reliance
on data; they are 48% more likely than mainstream
respondents to say that marketing strategy is strongly
data-driven.” And nearly 7 in 10 leading marketers say
that their companies use data to support decision-
making at all levels.8
Never trust my gut?
Your gut is still important; just be sure you’re
feeding it a diet of solid data.
“We like to say we want to be
data-informed, not necessarily
data-driven,” says Stasha Rosen
of Refinery29. “We educate
our team to make sure that
people don’t become slaves
to the metrics.” In particular,
you want to avoid analysis
paralysis — getting so lost in
the data that you can’t or won’t
make choices until the data
seems to line up perfectly.
“Intuition still matters,” says Rosen. “If you wait
until you’ve reached 99% certainty in the data to
make a decision, then that’s probably too late.”
7in10Nearly 7 in 10 leading marketers say that
their companies use data to support
decision-making at all levels.8
Let data be your guideThe Data-Driven Marketer’s Strategic Playbook
12. The best strategy
in the world won’t
help much if your
team can’t execute
and measure it.
PA RT 3 .
T R A I N T O T R A N S F O R M
13. 13 of 40
Train to transform
In the Econsultancy survey, 3 out of 4 marketers
agreed that lack of team education and training
on data and analytics is their biggest barrier to basing
more business decisions on data insights.9
Better training starts with a real desire to transform
the entire organization. What is needed is both a top-
down and a bottom-up belief that data should drive
decision-making. That means trusting the data — and
the analysts, too.
“Our analytics team focused just on report-pulling
only two or three years ago,” says Monika Rut-Koroglu,
director of digital analytics and optimization for FXCM,
a retail online foreign exchange brokerage. “This has
completely transitioned over recently, with the team
becoming marketing strategy drivers. Analytics plays a
very important role in all our marketing efforts: driving
marketing strategy, validating benchmarks, evaluating
and providing data insights. Actionable insight is key for
the team and for the company.”
Leading marketers are
more than twice as likely
as the mainstream to say
that they routinely take
action based on insights
and recommendations
from analytics.
Econsultancy and Google,
“The Customer Experience is Written in Data”,
May 2017, U.S.
2x
Train to transformThe Data-Driven Marketer’s Strategic Playbook
14. 14 of 40
Leading marketers were
55% more likely to say
that their generalists
get enough training to
effectively use data and
analytics resources.
Econsultancy and Google,
“The Customer Experience is Written in Data”,
May 2017, U.S.
55%
Give everyone the training they need
If you’re setting out to break down silos in your own
company, the carrot usually works better than the stick.
At first, only the data and analytics team may get the
full picture of how analytics can lead the way to better
strategy. But the more people see how an integrated data
strategy provides better audience insights that benefit their
team, the faster the groundswell of adoption happens.
Create a training plan to educate people about the tools
and opportunities that are available. Don’t ignore the
generalists and junior members of your team: Leading
marketers in the Econsultancy survey were 55% more likely
than mainstream companies to say that their generalists
get enough training to effectively use data and analytics
resources.10
“Any time we give trainings on what we’re doing, we record
them and put them on a platform where all employees can
find them as needed,” says Jeff Rasp of Bayer. “If someone
asks ‘Do we even have something like this?’, we can send
them to that video, as a kind of one-to-one training on
demand. That’s helping us leverage those tools more
inclusively across all our brands.”
About that groundswell of adoption: Often the best way
to break down data silos is to offer team-level support
rather than company-wide edicts. At FXCM, the analytics
team pulls data reports from disparate sources, then
tries to find as close to an apples-to-apples comparison
as possible to validate trends they’ve spotted in the data.
They then go back to various departments to talk people
through the analysis and insights, gather feedback, and
build consensus. This team-by-team approach can align
stakeholders and win their support for larger company-
wide shifts in strategy and marketing campaigns.
Train to transformThe Data-Driven Marketer’s Strategic Playbook
15. 15 of 40
Breaking down data silos (and organizational ones) takes time, of
course; it’s a big commitment. Of those who have done it, five common
ingredients emerge as necessary to truly get everyone in an organization
into the same data-first mindset:
Your top executives set the tone for your company culture. If you want more
people using data and analytics to guide daily decisions, then your CEO has
to make data a top business priority. That could mean undergoing a full
data-driven transformation to shed legacy ways of working and move to new
technologies and processes. Or, it could mean setting goals for using data to
inform strategic initiatives. Alignment across the C-suite, especially with the
CMO, is vital. As always, team strategies should match corporate strategies,
so that focus can be instilled in each team that ladders up to top leaders.
1. Get the C-suite in sync
Train to transformThe Data-Driven Marketer’s Strategic Playbook
more likely to say that being
a more data-driven marketing
organization is a top goal for their
CMO/marketing leadership.
Leaders are
21%
Mainstream Leaders
67%
51%
more likely to say that
being a more data-driven
organization is a top goal
for their CEO.
Leaders are
32%
Mainstream Leaders
54%
65%
Econsultancy and Google,
“The Customer Experience is Written in Data”, May 2017, U.S.
16. more likely to say that their
organizations are quite
open to change.
Leaders are
45%
16 of 40Train to transformThe Data-Driven Marketer’s Strategic Playbook
Know where you start. Even though the world (and marketing) move at a fast
pace, it helps to document things so you can tell what effect your changes in
ideas and programs have over time. Be sure to document and socialize your data
and analytics strategy company-wide so that it can be understood and executed.
3. Be clear on your data strategy
Promote change? You bet! But organizations that put too many rules,
must-dos and red tape in place stifle the birth and spread of new ideas.
It’s tough to innovate your way through walls, after all. When employees
are encouraged by leaders to change and take risks, they feel empowered
to experiment and innovate. Or, in the words of Sprint’s Rob Roy: “If we’re
not failing, we’re not pushing the envelope hard enough.”
2. Be open to change and risk
more likely to say that their data
and analytics strategy is useful
for decision-making at all levels.
27%
Leaders are Leaders are
more likely to have a
documented data and
analytics strategy.
35%
Mainstream Leaders
62%
40%
more likely to say that their
marketing organizations
are comfortable with risk.
Leaders are
55%
Mainstream Leaders
48%
69%
Econsultancy and Google,
“The Customer Experience is Written in Data”, May 2017, U.S.
Econsultancy and Google,
“The Customer Experience is Written in Data”, May 2017, U.S.
17. 17 of 40
If your own analysts have simply been “report pullers” in the past, you may
want to shift perceptions by giving them new roles and even new titles, like
data storyteller or strategic analyst.
Analysts who can make the data come alive with stories and business context
are a wonderful resource; they can convince marketing managers or other
skeptical collaborators of the value of your new integrated data strategy.
And the more that analysts have the time and firepower to tailor their insights
to each team, the more they can help them reach their biggest goals.
5. Create new roles for analysts
Train to transformThe Data-Driven Marketer’s Strategic Playbook
Getting rid of silos is one thing; keeping them from coming back is another.
To keep communication flowing, look for ways to encourage, enable, and
sometimes formalize channels for collaboration across departments and even
within teams.
4. Work together — and keep talking
more likely to strongly agree
that collaboration across
marketing and analytics teams
is essential to driving results.
Leaders are
29% of marketers agree that
collaboration across marketing
and analytics teams is
essential to driving results.
Across all respondents
93%
more likely than others to say
they have sufficient analyst
resources to accomplish
their goals.
85% of marketers agree that lack of
education/training on data and
analytics is the biggest barrier to
more business decisions being
made based on data insights.
75%
Leaders are Across all types of organizations
Econsultancy and Google,
“The Customer Experience is
Written in Data”, May 2017, U.S.
Econsultancy and Google,
“The Customer Experience is
Written in Data”, May 2017, U.S.
18. The three pillars of your
integrated strategy
PA RT 4 .
So far we’ve discussed some of the challenges and ideals of
integrated data. But what does it take specifically to get the
typical organization onto the right path? The Econsultancy
study and our interviews with business leaders revealed three
pillars for making it happen: the right data, the right culture,
and the right technology.
19. 19 of 40
Why don’t more companies understand their user journeys? Many still struggle
with data blindness, not knowing what data they have or how it fits together.
Marketers who know their data from origins to integration are best poised for
success in the years to come. Truly understanding your data (and the customer
journey) this way starts with executing key steps in your data strategy.
Pillar 1: The Right Data
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
1. Manage the data pipeline
More data is better, yes ― as long as that data is both
relevant and reliable.
What first-party data do you have, and where does it come
from? Do you have feeds of sales data, website interactions,
or other customer data? Is your data clean, accurate and
accountable? Can you see your original data, or is it owned
by an agency or another partner?
There is no magic data Roomba that will clean all your data
automatically. But technology does help automate some
tasks and it can greatly reduce the burden of having to stitch
together all the data points and confirm their validity.
“One of my responsibilities is identifying the core data sets
for the company, and making sure that we distribute those
to the analysts throughout the company in a clean and
workable fashion,” says Stasha Rosen of Refinery29.
“An interesting trend for the publishing industry is that
we’ve been slowly moving from owned platforms to more
distributed platforms. 10 years ago we were primarily the
Refinery29.com website. But now our content is becoming
divorced from the means of distribution,” says Rosen.
“Any given piece of content is no longer just a page on our
website, but it can be sliced and diced and distributed in
different ways.”
“That kind of distribution is optimized for the user, which is
good. It’s a better experience, but it poses more challenges
from a data perspective because it’s introducing a new
source of data that has to be reconciled with all of our other
sources of data,” she says.
Industry leaders are willing to pay for better data. In fact,
marketing leaders are 72% more likely than others to
strongly agree that they are investing in improving the
quality and/or volume of the first-party data they capture,
according to a different study with Econsultancy. And
27% were more likely to have increased investments in
technologies for better sharing of first-party customer data
across team or product lines.11
Once first-party data is in hand, many leaders then look for a
deeper understanding of their audiences by adding third-
party data into the mix.
“Raw data is necessary to make educated decisions,
and many times we are given ‘pre-filtered’ reporting
that meets the needs of the presenter, not us.”
- Director, Automotive Industry
20. 20 of 40
2. Put data in context
When you’re combining data sources, the apples-to-apples comparisons
are something that each company has to configure for itself. “Our data
architecture has to fit our needs,” says Monika Rut-Koroglu of FXCM. “We were
with our old third-party provider forever, but month-to-month data just became
more obsolete. At the end of the day we didn’t know what the data represented
because we didn’t know how it was being collected.” She says:
“We switched to [managing our own analytics in-house]
because we needed more streamlining and transparency.
Now we can create documentation on what exactly we need
to track and why we need to track that.”
“We group our website visitors based on the similarity of their behavior
and deploy our tracking of the website via single tag management container.
All the customers and all the events are being collected in exactly the
same way, in order, across our websites,” Rut-Koroglu says. “That gives
us global transparency and allows us to maintain our tracking systems
mostly flawlessly.”
“This has been our success story: The re-implementation of better data
tracking is the fundamental piece that enables our success today,” she says.
“The biggest portion of our analytics team’s success in driving strategy is that
implementation through data confidence.”
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
21. 21 of 40
3. Adjust Your KPIs
Even with the cleanest data, you also need to know your KPIs and ensure they
are tied to the larger business outcomes you want. In the Econsultancy study,
leaders were 40% more likely than others to say that their data and analytics
strategy identifies the business goals the organization is trying to achieve with
data analytics.
It’s also important not to let a single KPI drive out all other data detail or insights.
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
“Instead of seeking one KPI to rule them all, we really
like looking at oppositional metrics,” says Stasha
Rosen of Refinery29. “We look for two or three valuable
metrics that also keep each other in balance.”
Stasha Rosen
Senior Product Analyst,
Refinery29
At Experian, the consumer services division was focused on conversions: getting
people to sign up for online credit reports and related products. “But we realized
that using only this KPI wasn’t sustainable,” says Jane Yu, senior director
of digital analytics and ad operations. The team shifted their analytics strategy
to focus on a longer-term metric: customer lifetime value.
“We knew making the shift to lifetime value meant understanding and
segmenting our customers on a much deeper level,” says Yu. “That was
a daunting task. We needed to closely examine first- and third-party customer
data from many different sources. This is often messy and scary, and it’s
never perfect.”
Even after they put the right structures in place, Yu says: “We couldn’t just change
our customer segmentation strategy and messaging in order to make lifetime
value our priority — we also had to update our measurement and metrics to
reflect the evolving strategy. To do this, we started optimizing for lifetime value.”
22. 22 of 40The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
4. Give everyone access
Data’s no good if analysts are the only ones who can see it.
The goal is to help everyone use data to make better decisions
and improve results, after all. In the Econsultancy survey,
leaders were 57% more likely than the mainstream to strongly
agree that open access to data leads to higher business
performance.12
But transparency goes two layers deep: everyone needs
access to insights, but they also need to know where the
original data comes from and how to use it.
With democratized data, everyone in the company drinks from
the same data well. (They can bring their own cup, of course.)
Whatever platform you choose, it should serve both the do-it-
yourself marketing managers and strategy planners and your
data scientists and advanced analytics practitioners. In the
Econsultancy survey, organizations with integrated marketing
and advertising technology stacks were 43% more likely to
report that their teams have ready access to data (including
things like multiple seat licenses for analytics) compared to
marketers without fully-integrated technologies.13
Leaders were 57% more
likely to strongly agree
that open access to
data leads to higher
business performance.
Econsultancy and Google,
“The Customer Experience is Written in Data”,
May 2017, U.S.
57%
23. 5. Do deeper analysis
Finally, you’re ready to dig into the data: look for patterns, ask questions, and
use more tools to uncover insights.
If you’re not already involved in machine learning and artificial intelligence, get
ready. This advanced technology learns without being explicitly programmed;
machine learning models can quickly mine huge reams of data for patterns
and anomalies, providing faster speed to insight than ever before. Here are a
few things to look out for — and a few pitfalls to avoid.
Machine learning may sound new, but it has already been built in to many
systems at Google and other companies. Artificial intelligence can highlight
patterns or anomalies that may have previously been hidden. You don’t know
what you don’t know, but machine learning can spot and surface opportunities
that can lead to “aha” moments for marketers. It works best when combined in
a one-two punch with your team’s own thoughtful human analysis.
For more helpful background on machine learning, see
The CIO’s Guide to Data Analytics and Machine Learning from the Google Cloud team
Keep data consistent
Machines can’t draw useful
insights from garbled data.
As noted earlier, data has
to be clean and normalized
from collection through
storage, reporting and
maintenance.
Pay attention to privacy
Maintain user privacy by
using data in aggregate
and anonymized signals.
Leaders in the Econsultancy
study were 31% more likely
than others to say that their
data and analytics strategy
identifies standards and
processes related to data
security and privacy.14
Test your model
To validate your machine
learning model after you’ve
trained it, try testing it with
historical data. Make sure
you use an appropriate
confidence interval for the
business outcome you want.
(Testing doesn’t end with the
first iteration of the model;
it continues after the model
starts making real decisions
with new customers.)
Be creative
Machine learning models
are very good at telling you
who to reach to achieve your
business goals, but they may
not be able to write the most
engaging ads or design your
website for you. Make sure
that your creative team is
involved and ready to make
the consumer engagement
connection between the data
and the user.
23 of 40The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
24. 6. Act fast
Once you’ve taken machine and human analysis as
far as you can, don’t wait around for something more
perfect. Even the best integrated data still has gaps.
Speed is important: Estimate where you need to, use
proxies where you can, then take action.
“Marketers are uncomfortable with estimates,” said
Jeremy Hull, EVP, iProspect, in a 2016 Econsultancy
report. “We’ve labored with the idea that data is so
perfect and that we can track and measure everything.
It’s a fiction and will become more of a fiction as we
have more things that we can’t measure one for one.
The goal isn’t to have perfect data — it’s to have good
enough data to drive insights and make decisions.”
For data analysts, the job is to present fresh data
stories about audience segments and customer
groups with clear, actionable recommendations.
For marketers, the job is to quickly turn those
recommendations into more relevant ad messaging
and creative — and more personalized customer
experiences in apps, websites, and stores.
If you are working with an agency, make sure you’re all
on the same page and using an approved standard.
“When our media agency is managing programs, we
make sure that they’re doing it against a standard
structure and a standard approach,” says Jeff Rasp
of Bayer. He adds:
“Our belief and our methodology is that yes,
there are unique aspects of every brand,
but we try to align around an 80/20 rule:
80% of analytics is standardized and 20%
is unique to the brand.”
24 of 40
80/20
Standardized
analytics
Unique to the
brand
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
25. And take nothing for granted; your assumptions
may be quite wrong. FXCM, for example, had a very
specific funnel and conversion strategy implemented
for years. But when FXCM began managing its
own data again, what they found was “completely
staggering,” says Monika Rut-Koroglu. “The data
showed the customer acquisition strategy was based
on faulty assumptions and that the customer journey
was completely different 90% of the time.”
Once the FXCM team realized this, they took action
right away, using A/B and multivariate testing to try
different scenarios and approaches. “We started
testing in various silos, mainly via specific display,
search campaigns, and website experiences,
to validate a new acquisition approach,” says
Rut-Koroglu. “We’ve seen great results and great
incremental lift. Are we 100% confident we’re serving
exactly the experiences customers want? I’m not
sure anyone ever is, but we have a much better
understanding and can be more confident.”
Having confidence in your integrated data is part of
the equation — the other part is having integrated
analytics and ad technologies needed to take action.
The Econsultancy survey showed that industry leaders
are 52% more likely than the mainstream to have
an integrated marketing and advertising technology
stack. If you don’t have a unified platform, think about
what else may be possible.
“Measuring and tracking lifetime value used to be
an ad hoc process, but now with a single platform
we can dynamically track and update based on new
performance data. … As we continue to develop
this data and model, we’ll be able to apply it to our
marketing directly through [our tools],” says Jane Yu
of Experian.
25 of 40
Lack of trust in data
Not a
challenge
Significant
challenge
Minor
challenge
Critical
challenge
Not applicable /
Don’t know
Lack of specialists in analytics
(e.g. data scientists, dedicated analysis)
Lack of analysis skills among marketing generalists
Insufficient analysis and insights from data
Slow response from analysts/data team
Lack of alignment in goals/objectives
20%
18%
17%
17%
15%
15%
34%
29%
31%
34%
31%
33%
28%
30%
30%
32%
35%
29%
17%
20%
19%
15%
17%
21%
2%
2%
3%
3%
3%
1%
Some of the human challenges of analytics include
building trust in data, training team members, and
making sure everyone is agreed on goals
and objectives.
In your opinion, how do these human challenges
negatively impact your organization?
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
Sometimes data challenges
are people-related
Econsultancy and Google,
“The Customer Experience is Written in Data”, May 2017, U.S.
26. Our 2016 Culture of Growth eBook talked about
the champion, a CMO or other C-level employee
who supports testing and experimentation and
delivers the resources needed to move ahead.
That can mean budget, talent, developer
time, or (maybe most importantly) a sense
of urgent priority.
The same kind of C-level vision and support is
present in companies where a data and analytics
strategy is core to marketing. But vision alone
isn’t enough, of course: It has to carry through
to action.
“The reward structure for your organization
has to be set up to actually applaud and focus
on things which are not traditionally the shiny
object,” says Josh Spanier, Senior Marketing
Director, Global Media at Google.
“We have to create a process and reward system
which celebrates these different wins.”
Here are some simple questions to ask
to see where your company stands in the
transformation.
Pillar 2: The Right Culture
Is a data-driven culture or
transformation articulated in
the highest company goals?
Are other orgs besides
marketing aligning their goals
and incentives accordingly?
Where do analytics and
digital media fall in our
organization?
26 of 40The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
27. 27 of 40
The center
of excellence
Distributed team Hub and
spoke model
Really harnessing data and putting it to use may require certain leaders
within the company to reevaluate how teams are structured — or formalize
points of alignment and collaboration across certain functional areas, such
as brand marketing, digital media, and analytics departments. In particular,
marketing may have the audience insights needed to guide the entire
customer relationship, moving it beyond branding and into the front lines
of corporate strategy.
Not all leaders approach data-driven marketing the same way. But most
seem to use one of three organizational models:
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
28. Many multinational leaders use a center of excellence model, where a central
digital point person or team works to establish and document guidelines and
processes. Often a point person or activation team is created within each brand
or business unit to ensure follow-through.
This model can be especially useful for companies without huge budgets, or
for major corporations with many smaller offices scattered around the globe. In
those situations, it can be difficult to have a robust data science group in every
market — difficult both financially and in terms of finding the necessary talent.
There’s a tradeoff involved: Try to do too
much globally from a central data team
and you gain agility but lose connection
to the local markets. But decentralize
too much and you can lose quality
or risk having key data stay siloed
geographically.
A center of excellence team can often supplement remote offices with top-flight
help, while the offices provide a connection to the local market.
Bayer is one company building on the center of excellence model. “Digital
remains a center of excellence and this allows us to standardize tools,
platforms, and best practices to then socialize across the division,” says Jeff
Rasp. “But once we establish those practices we pass them to an activation
team, which makes sure that there’s compliance across the division.”
THE CENTER OF EXCELLENCE
29. With this model, there is no real overarching analytics presence. Instead,
analysts are embedded within individual teams and functions throughout
the organization.
The great advantage of this model is that
it allows analysts and local teams to test
and make fast, nimble strategic shifts on
a monthly, weekly, or even day-to-day
basis. They also get to know the team’s
business better.
DISTRIBUTED TEAM
“Our organizational structure for analytics is quite distributed,” says Stasha
Rosen of Refinery29. “We have analysts embedded in teams throughout
the company. We identify the core data sets for the company at a high level,
and then make sure that we distribute those to the analysts throughout the
company in a clean and workable fashion.”
For Refinery29, the distributed model also applies to creation: “We’ve succeeded
in creating a more iterative design process based on testing and really careful
data analysis. That’s been an exciting transformation that helps us really focus
on users and what they prefer.”
30. This is a hybrid approach, taking the best parts of the center of excellence
and a distributed model. The expert core team establishes consistent, shared
guidelines, tools, and processes. Then, the people embedded with each
brand team or functional organization are accountable for implementing best
practices and feeding insights and optimizations back to the central core.
This blended organizational structure also allows for greater alignment of
objectives and business goals.
Sprint uses a “quasi” hub and spoke model, according to Chief Digital Officer
Rob Roy. He first built up a center of excellence through his digital team,
then worked to teach, promote, and influence people within Sprint’s various
organizations to champion that digital hub. A close partnership developed
with the customer relationship team, then it extended to other arms
of the business.
“We worked closely with the network team, as well as the prepaid group to do
analysis on things like how much we should price phones, elasticity of price,
number of handsets that move, and the type of customer that buys it,” Roy
says. “And once we showed those teams some very interesting and actionable
data, the teams’ leader took it to the CEO, unbeknownst to us. It was very well-
received and once he saw it — then the floodgates opened.” More support and
interest in making data-informed decisions followed.
Whichever model they use, most industry leaders have the same goal:
empowering local teams to innovate and explore, with the freedom to make
changes and take risks.
HUB AND SPOKE MODEL
31. Another key question: Will you handle all data and analytics in-
house, or outsource some or all of your data management and
related operations to an external agency or other partner?
Where does your data come from?
Who leads on KPIs?
Old and new KPIs tend to bump into
each other as data-friendly cultures
grow. It’s a good idea to have the
team that integrates the data lead the
discussion on how various KPIs and
metrics are calculated. That’s true
not just for paid media but for owned
media like websites, e-commerce
platforms, and social media. In
the Econsultancy survey, leading
companies were 38% more likely
than others to say that their data and
analytics strategy includes how they
define KPIs for owned properties.
31 of 40
FXCM has chosen to do it all in-house. With a relatively small data
team, hands-on analytics drives daily decisions.
“Talking with people from different
industries, this seems to be the biggest
change within marketing teams: having a
front-row analytics team that is driving the
strategy,” says Monika Rut-Koroglu.
Not only is FXCM’s team able to act on data faster, they’re able
to understand it better. Rut-Koroglu says: “Our team has
a fundamental knowledge of how data is being collected and
processed. They understand both the limitations and opportunities
that come with our data; there’s never a question of ambiguity
or misunderstanding. That transparency has been extremely
important to the success of our marketing campaigns. The team
also has great knowledge of the business, who we are servicing,
and what the corporate objectives are.”
“We’re also fortunate in that we don’t have to go to IT to
implement analytics changes,” she notes. “Parts of our
web team act as ‘marketing IT,’ so we can turn things
around a lot faster than companies where they
have to formally go to the information technology
department and fight to get the resources to
implement or change the tracking.”
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
32. As another solution, many other companies outsource some or all
of their data collection, analysis, or activation to agencies or other
third parties. That choice may be based on channel priorities in a
particular region, a need for specialized technical expertise, or even
a need for a fresh perspective. Put another way, a number of brands
have a vision for how data can help them meet their business goals
but need help with execution.
One example of a strong partnership is with restaurant-booking app
OpenTable and global advertising agency PMG. “OpenTable has an
aggressive goal to lead the market. So, to them, this meant not only
exceeding those consumer expectations, but also thinking ahead of
the competition,” says PMG Founder and CEO George Popstefanov.
“We helped OpenTable segment their customers by customer
lifetime value, which captured more than just the value of a single
dining reservation. This segmentation then enabled them to deliver
a customized experience to those high-frequency customers
that matched their dining preferences. Capturing the value of a
relationship versus the value of a single reservation, OpenTable
was able to evolve their marketing goals and benchmarks to more
accurately reflect that longer-term value of a customer.”
Whatever path you take, the point of your strategy should be to
integrate data across platforms to better understand your customers
and the true marketing impact on your core business objectives. For
those who do outsource, it’s important to be clear at the start that
your company, not the agency, owns the data.
32 of 40The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
Programmatic Lead:
Some digital marketing teams hire a
new person to lead their programmatic
efforts as they manage more of their
own data in-house. This specialist role
is responsible for managing the data
pipeline and the relationships with key
point people who are the day-to-day
users of technologies in the marketing
and advertising stack.
Jeff Rasp introduced this role at Bayer
when he spotted an opportunity to
differentiate their digital efforts. That
person leads more media buying
in-house, with real-time access to
data and insights.
Data / Analytics Storyteller:
Some organizations have hired a new
data storyteller. Think of this person
as a messenger: one who helps to
simplify complex data analysis, shares
insights in the context of brands and
business units, and serves it all up
for marketing managers or C-level
audiences short on time.
As many more
organizations go through
digital and data-driven
transformations, new
jobs are gaining traction
to help lead the change:
33. When you set out to train employees in data analysis and action, you’ll
probably do all the logical things: set up classes (and make sure everyone
attends), post docs and videos, provide training on your data and marketing
platforms. That’s all good.
But it’s also important to address the “three lacks”:
Better Training
33 of 40
Lack of confidence
We all have a natural fear of failure.
Data storytelling is an art. It’s hard
to learn and hard to do. But here’s the
good news: If technology can help you
by surfacing insights automatically,
you’re halfway to a good result anyway.
Lack of trust
Why should I stick my neck out?
That’s the eternal human question.
Emphasize to your team that you’ll back
them up and encourage them to keep
a clear trail of the data that led them
to a particular test. (“Trust but verify,”
as Ronald Reagan once said.) When a
test succeeds or fails, that trail of data
will be a valuable learning tool for the
next go-round.
Lack of time
This often takes the form of pressure
to launch new features or execute on
existing product needs. Who has time
to think? You know the drill here: Finding
time is always a problem in business,
but people who have zero time are
guaranteed not to look at the data.
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
34. 34 of 40
OK, you’re there: You have your integrated data and analytics strategy in
place. You have your well-trained, collaborative team. Now for the final piece
of the puzzle: your technology solution.
Compared to other marketers, organizations with fully-integrated marketing
and advertising stacks are:
Of all the Econsultancy study respondents, 55% said that the lack
of data integration presents a significant or critical negative impact
on their organization. That’s where the magic of a unified stack comes
in: It integrates your marketing and analytics technology with your ad
technology so you can truly put your insights into action.
It means, for example, that your search buying team and TV buying team
can better coordinate their messaging to bid on the most conversion-
friendly keywords at the precise moments a client’s TV ad spots are airing.
In addition, businesses can save money and time by having their buying,
selling, and analytics tools all in one platform.
Pillar 3: The Right Technology
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
more likely to use audience-
level data to personalize
customer experiences.
47%more likely to use customer-
level data to segment and
reach individuals.
41%
more likely to use digital
analytics to optimize the
user experience in real time.
59%more likely to use attribution
to evaluate how channels work
together and to allocate budgets.
56%
Econsultancy and Google,
“The Customer Experience is Written in Data”, May 2017, U.S.
35. 35 of 40
And it means that you can better observe and analyze consumer interactions
with your website, and attribute each visit to a display ad viewed or a brand
engagement on social media. More than that, you can look at behaviors and
interactions with your site to identify, say, audience segments for people likely to
buy related products, or people who need a nudge to purchase what was left in
their shopping cart. Then you can apply those lists to your media buys so you can
remarket to them on other channels.
Marketing leaders today are in a position to drive themselves in ways that used to
require endless requests to IT. Many companies now have a web or digital team
that serves as “marketing’s IT.” With an integrated marketing and advertising
stack, the marketing org can feed audience insights back into their campaigns
and customer experiences at a quicker pace.
To circle back to our opening framework, marketers can use integrated
technology platforms in four key ways.
Organize data
Bring it all together to build
a full view of the customer.
Design compelling
creative
Develop messaging
customized to each audience,
using data-driven creative
and other techniques.
Reach and deliver
Find the right audience in the
right moment, with minimum
waste, and at the best
possible price.
Measure and optimize
Integrate analytics like cross-
channel attribution with the
measurement stack. Then
use newly-gained customer
insights to get better faster.
The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
36. Whatever the technology, the relationship between the
CMO and CIO or CTO is still key. After all, marketing
data can become a strategic asset for the entire
company. When the CMO and the CIO or CTO are key
collaborators, marketing data can be combined with
other first- and third-party data sources to help everyone
conduct more complex analyses and uncover deeper
insights — and then use what they learn to drive bigger
business outcomes.
That’s one of the great strengths of having your own
integrated technology: You get a clear, unbiased look at
what’s working and what’s not working.
That makes transparency, and an integrated data
strategy, all the more important.
Leading marketers are
58% more likely than the
mainstream to strongly
agree that first-party data
is a strategic asset that
informs their decision
making.15
Econsultancy and Google,
Marketing and Measurement Survey,
North America, March 2017
58%
36 of 40The three pillars of your integrated strategyThe Data-Driven Marketer’s Strategic Playbook
37. Data, data everywhere … and now you’re in command of it all, reading the tides
and sailing your ship like an admiral. Or if you prefer, standing like a pirate
astride a new treasure chest.
That’s the power of an integrated data strategy. With online and offline data
pulled together, you can truly understand the full customer journey and find
better ways to reach and serve those customers. That’s good news for them,
and better news for your business.
We hope these ideas and guidelines will help you tame those tides. Good luck!
Tying it all together
37 of 40ConclusionThe Data-Driven Marketer’s Strategic Playbook
Sources:
1. Google Surveys, U.S., “2016–2017 Marketing Analytics Challenges and Goals,” Base: 203, marketing executives who have analytics or data-driven initiatives,
Dec. 2016.
2-10, 12-14. Econsultancy/Google, “The Customer Experience is Written in Data”, May 2017. [n=677 marketing and measurement executives at companies with
over $250M in revenues, primarily in North America; n=199 leading marketers who reported marketing significantly exceeded top business goal in 2016, n=478
mainstream marketers (remainder of the sample)].
11 & 15. Econsultancy and Google, Marketing and Measurement Survey, n=514, marketing and measurement executives at North American companies with over
$250M in revenues; n=133 leading marketers who reported marketing significantly exceeded top business goals in 2016, n=381 mainstream marketers (remainder
of the sample), March 2017.
38. Research reports
The customer experience is written in data:
Why and how the most successful brands are putting data
at the center of marketing strategy
Driving growth with measurement in a mobile world:
New attitudes and approaches to analytics
and measurement
Measurement and growth:
How leading brands are connecting measurement
with business goals
An audience of individuals:
How leading brands are investing in a first-party future
Technology and product information
Google Analytics 360 Suite
DoubleClick insights on data-driven creative
A brand marketer’s guide to programmatic buying
Articles, blogs, and webinars
Better together: Why integrating data strategy,
teams, and technology leads to marketing success
(via ThinkWithGoogle.com)
Want to be a leading marketer? Go with data, not your gut
(via ThinkWithGoogle.com)
Three ways to get data out of silos and into
your marketing strategy
(via Google Analytics Blog)
Marketing with a heart of data
(via Google Analytics Blog)
Marketers: Get your data house in order
(in partnership with MIT Sloan Management Review
Custom Content Studio)
How to build a culture of growth
(via Google)
For more on building a data strategy — or on Google analytics
and advertising technology — check out these resources:
Additional resources
38 of 40Additional resourcesThe Data-Driven Marketer’s Strategic Playbook
About the Google Analytics 360 Suite
The Google Analytics 360 Suite offers powerful and integrated analytics solutions for today’s biggest enterprises. Measure and
improve the impact of your marketing across every screen, channel, and moment in today’s customer journey. It’s easy to use,
and makes data accessible for everyone so the “aha” moments are simple to discover and share. Move from insight to impact
faster with the Google Analytics 360 Suite, and as a result, make the most of every consumer connection.
Find out more
About DoubleClick
DoubleClick connects the right people in the right moments to make digital advertising work better. Through its industry-leading
suite of integrated mobile, video, programmatic, measurement, creative, and search management solutions, DoubleClick
empowers brands, publishers, ad networks, and agencies to realize what’s possible with digital.
Find out more
39. Leaders vs. the mainstream: How does your organization stack up?
39 of 40
Measurement
Leading marketers
Tie marketing metrics and KPIs to larger business outcomes
— for example, customer lifetime value or profit.
Mainstream marketers
Measure marketing results at the campaign level or in functional silos.
Why it matters
Leaders are 33% more likely than the mainstream to say that their
data and analytics strategy explains how the organization defines
and measures the touch points in the customer journey.1
Ready to build an integrated data strategy for your company? Here’s how those who are doing
it successfully compare to more mainstream businesses that are lagging behind.
Do your marketing metrics align with your
topline business goal?
Do you know what data is being combined
and calculated for your metrics?
Do you have a strategy to measure all touch
points in the consumer journey?
Data
Leading marketers
Use an integrated platform to consolidate, organize and share
consistent data across teams.
Mainstream marketers
Keep data in siloed teams, each of which uses its data only
to inform its own strategies and decisions.
Why it matters
Leaders are 57% more likely than the mainstream to strongly agree
that open access to data leads to higher business performance.2
Have you taken inventory of all your data
sources and identified owners or points
of contact?
Have you organized your data and identified
gaps in first-party data that need to be
supplemented with other sources?
Have you put data into context and
created apples-to-apples comparisons
to standardize data?
Audience
Leading marketers
Have an integrated data strategy that enables them to create
audience segments, based on lifetime or potential future value
to the business.
Mainstream marketers
Segment customers by demographics and market to averages.
Why it matters
Leading marketers are 1.5X as likely to use a consumer-centric
metric, like customer lifetime value, to measure success.3
Have you identified and prioritized audience
segments — and applied those priorities to
your advertising and marketing?
Do you have a model to understand the future
value of customers and segments?
How does that value information inform your
marketing strategy?
1 & 2. Econsultancy/Google, “The Customer Experience is Written in Data”, May 2017, U.S. (n=677 marketing and measurement executives at companies with
over $250M in revenues, primarily in North America; n=199 leading marketers who reported marketing significantly exceeded top business goal in 2016, n=478
mainstream marketers (remainder of the sample), May 2017.
3. Bain Marketing Survey 2016.
Leaders vs. the mainstreamThe Data-Driven Marketer’s Strategic Playbook
Questions to evaluate how
your organization compares
40. 40 of 40
4. Econsultancy and Google, Marketing and Measurement Survey, n=514, marketing and measurement executives at North American companies with over $250M
in revenues; n=133 leading marketers who reported marketing significantly exceeded top business goals in 2016, n=381 mainstream marketers (remainder of the
sample), March 2017.
5 & 6. Econsultancy/Google, “The Customer Experience is Written in Data”, May 2017, U.S. (n=677 marketing and measurement executives at companies with
over $250M in revenues, primarily in North America; n=199 leading marketers who reported marketing significantly exceeded top business goal in 2016, n=478
mainstream marketers (remainder of the sample), May 2017
Leaders vs. the mainstreamThe Data-Driven Marketer’s Strategic Playbook
Technology & automation
Leading marketers
Use modern technology, including products and platforms informed
by machine learning, to increase speed to insight.
Mainstream marketers
Use process automation backed by fixed rules or human-derived
insights.
Why it matters
Leading markers are 48% more likely than the mainstream to be
increasing investments in capabilities, like machine learning.4
Experience
Leading marketers
Use data to personalize marketing across online and offline
customer experiences.
Mainstream marketers
Deliver a one-size-fits-all experience to customers.
Why it matters
Organizations with integrated marketing and advertising stacks
are 47% more likely to be using audience-level data to personalize
customer experience as marketers without fully-integrated
technologies.5
Attribution
Leading marketers
Go beyond the last click with data-driven attribution.
Mainstream marketers
Use last-click attribution.
Why it matters
Organizations with integrated marketing and advertising stacks are
56% more likely to be using attribution to evaluate how channels
work together and to allocate budgets as marketers without fully
integrated technologies.6
Do marketing teams have the flexibility and
authority to use automation and machine
learning to treat segments differently
according to LTV?
Are you getting full use out of the technology
capabilities you have in place?
Have you integrated your marketing and
advertising technologies so you can act
on audience insights?
Are you using customer and context
data to deliver a seamless and fast
mobile experience?
Do you currently deliver a consistent
customer experience across online and
offline touchpoints?
Do you optimize the customer experience
based on audience data/insights
in near-real time?
Do you have a single-channel solution for
attribution to analyze conversion patterns?
Do you have a cross-channel view
of attribution that assigns credit to each
stage of the customer journey?
Do your teams take actions by updating
bids, budgets and strategies based on
attribution results?
Questions to evaluate how
your organization compares