Integrated Campaign Performance: Multi Touch Attribution
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This document discusses integrated campaign reporting and multi-touch attribution. It covers tracking performance across digital channels, understanding multi-touch attribution, and how integrated reporting can enhance understanding of digital marketing campaigns. It also provides guidance on implementing campaign tracking to enable integrated reporting and multi-touch attribution, including establishing processes, defining necessary attributes, and using tags to link digital media to web analytics.
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Integrated Campaign Performance: Multi Touch Attribution
- 1. Integrated Campaign Reporting + Multi-Touch Attribution Brandon Ralls Director, Digital Intelligence Lab © 2011 Webtrends, All Rights Reserved.
- 2. Introduction web mobile © 2011 Webtrends, All Rights Reserved. social | 2
- 3. Background • Agency Perspective • Analytics Consulting web • Digital Marketing • Data Visualization mobile © 2011 Webtrends, All Rights Reserved. social | 3
- 4. Topics for Discussion 1) Performance across digital channels 2) Multi-touch attribution (MTA) 3) Integrated reporting 4) Implementing campaign tracking web 5) Client stories mobile © 2011 Webtrends, All Rights Reserved. social | 4
- 5. Topic 1: Performance across digital channels How do I begin to understand campaign performance across web multiple digital channels? mobile social © 2011 Webtrends, All Rights Reserved. | 5
- 6. Digital Landscape web mobile © 2011 Webtrends, All Rights Reserved. social Source: Forrester Research, Inc. | 6
- 7. Ways to Engage • Landing page • Hero image • Specific CTAs • Videos • Whitepapers web • Promotions • Lead gen forms mobile • Downloads • Special offers © 2011 Webtrends, All Rights Reserved. social • Printable coupons | 7
- 8. Complex Agency Network Media • Planning • Buying • Trafficking web Creative • Messaging • Asset creation mobile Development • • Site development Tagging & tracking © 2011 Webtrends, All Rights Reserved. social | 8
- 9. Complex Agency Network web mobile © 2011 Webtrends, All Rights Reserved. social | 9
- 10. Complex Agency Network Challenges • Silos of data • Disjointed story web • • Different cadences Different formats mobile • Difficult to rationalize © 2011 Webtrends, All Rights Reserved. social | 10
- 11. User Behavior Our Objective Link specific media placements to actions on our site and determine what attributes influence behavior Visitors Media Site Actions web Search Form Display Share Social CTA Video Purchase • • • • Impressions Responses Response % $ per Response • • • • Platform Channel Publisher Tactic mobile • • • • Page Name Visits Bounce % Engage % • • • • Location Category Name Type social • Placement • $ per Engage • Creative © 2011 Webtrends, All Rights Reserved. | 11
- 12. Digital Ecosystem web mobile © 2011 Webtrends, All Rights Reserved. social | 12
- 13. Topic 2: Multi-Touch Attribution (MTA) What is cross-channel, or web multi-touch attribution? mobile © 2011 Webtrends, All Rights Reserved. social | 13
- 14. MTA Overview First Click Last Click Equal Weighted 100% 0% 0% 0% 0% 100% 33% 33% 33% 15% 35% 50% • Basic • Most common • Moderate • Most web approach approach sophistication sophisticated • First interaction • Last interaction • Each interaction • Each interaction receives 100% receives 100% receives equal proportionately weighted mobile • Not accurate • Not accurate • Good directional representation representation perspective • Most accurate representation social Low High Sophistication Sophistication © 2011 Webtrends, All Rights Reserved. | 14
- 15. Example Scenario Browse Paid Search 1) Research Display Banner 2) web Organic Search mobile Purchase 3) © 2011 Webtrends, All Rights Reserved. social | 15
- 16. Example Scenario: First Click Browse Paid Search 1) 100% Research Display Banner 2) web 0% Organic Search mobile Purchase 3) © 2011 Webtrends, All Rights Reserved. social 0% | 16
- 17. Example Scenario: Last Click Browse Paid Search 1) 0% Research Display Banner 2) web 0% Organic Search mobile Purchase 3) © 2011 Webtrends, All Rights Reserved. social 100% | 17
- 18. Example Scenario: Equal Weight Browse Paid Search 1) 33% Research Display Banner 2) web 33% Organic Search mobile Purchase 3) © 2011 Webtrends, All Rights Reserved. social 33% | 18
- 19. Role of Channel Introduce Engage Convert Touch type helps us understand role each channel plays: Paid Search First Touch Secondary Touches 15% 25% 45% Last Touch Display 45% 10% 25% Video 10% web 25% 5% Web TV 15% mobile 5% 10% Social Media © 2011 Webtrends, All Rights Reserved. 5% social 45% 15% | 19
- 20. Topic 3: Integrated Reporting How can integrated reporting with MTA enhance my understanding of my digital web mobile marketing campaigns? © 2011 Webtrends, All Rights Reserved. social | 20
- 21. Decisions Media Spend Visitors Media Site Actions Search Form Display Share web Social CTA Video Purchase • Impressions • Platform • Page Name • Location • Responses • Channel • Visits • Category mobile • Response % • Publisher • Bounce % • Name • $ per Response • Tactic • Engage % • Type • Placement • $ per Engage • Creative © 2011 Webtrends, All Rights Reserved. social ROAS | 21
- 22. Key Areas to Focus AUDIENCE: Who you are sending? CHANNELS: Where you are sending them from? web CREATIVE: What are they seeing that is driving their response? mobile CONTENT: What do they do when they land on your site? © 2011 Webtrends, All Rights Reserved. social ACTIONS: What content drives continued action? | 22
- 23. Sample Integrated Report • Channel performance • Top first touch channels • Top last touch channels • Average touches web • Average latency mobile • Touch distribution • Paths to convert © 2011 Webtrends, All Rights Reserved. social • Role of channels | 23
- 24. Sample Questions Platforms What platforms are users engaging with to be exposed to my media? Should I invest more in emerging platforms like mobile? Channels What is the role that each media channel plays? Are users more likely to engage with certain media channels over others? How do certain media channels drive continued action on the site? Publishers web Are there certain publishers that are driving more qualified traffic? mobile Tactics What specific media tactics are users responding to? Is there something specific about those placements that encourage user response? Creative What specific creative executions are users responding to? Do certain creative types encourage higher response? © 2011 Webtrends, All Rights Reserved. social | 24
- 25. Topic 4: Implementing Campaign Tracking How do I implement campaign tracking to enable integrated web mobile reporting and MTA? © 2011 Webtrends, All Rights Reserved. social| 25
- 26. The World as a Pivot Table Filters Measures web Dimensions mobile Data © 2011 Webtrends, All Rights Reserved. social | 26
- 27. How Do We Do This? web mobile © 2011 Webtrends, All Rights Reserved. social | 27
- 28. Establish a Process If you aren’t proactively capturing data, it won’t magically become available once your campaign goes live. your data web black hole 10110011101001010101… mobile © 2011 Webtrends, All Rights Reserved. social | 28
- 29. Establish a Process PHASE DESCRIPTION OUTPUT TIMELINE Initial Work with agency partners to outline current Measurement Week campaign strategy and timelines. Requirements Discovery 1 to 2 Work with agency partners to establish a PPT template for capturing measurement and Measurement & reporting requirements for each campaign Learning Plan Identify media channels and placement types that are used during campaigns to define a Media Content standard set of campaign attributes to be Tagging Guide Tagging Guide passed to Webtrends Campaign Week Measurement Identify content and action types that are used 2 to 8 web Strategy during campaigns to define a set of tags that Digital Campaign will be used to capture success events and Media Site engagement attributes. Define a process for deploying tags to effectively integrate media + web data – this includes a process for generating data outputs Translation WT File Analytics mobile that will be used to drive integrated reporting Design reporting approach that will meet Campaign reporting requirements – templatize approach Database Data for easy deployment of future campaigns Week Architecture 2 to 15 Development Determine backend data architecture and social Data Processing analysis process to drive required data Engine visualizations Dashboard Develop a data visualization tool that Web Week captures integrated data and cross-channel 8 to 15 Development performance Dashboard © 2011 Webtrends, All Rights Reserved. | 29
- 30. Campaign Attributes Campaign Type: Seasonal Promotion Campaign Name: Back to School 2012 Campaign Goal: Target college students Launch: July 2012 End: September 2012 web mobile © 2011 Webtrends, All Rights Reserved. social | 30
- 31. Audience Attributes Gender: Male Age: 18-24 years old Geo: In the United States Situation: Going off to college Objective: Looking for a new laptop web Focus: Focused on portability vs. processing power mobile Desire: Want something cool and cutting edge Digital Space: Highly engaged in social media Platform: Highly engaged on mobile © 2011 Webtrends, All Rights Reserved. social | 31
- 32. Media Attributes Platform: device where user is exposed to media Channel: types of media you buy Publisher: sites where users are exposed to media Tactic: method for delivering media web Placement: name of the ad that is displayed Creative type: method for delivering message mobile Creative size: size of the actual placement displayed Creative name: version of the ad displayed © 2011 Webtrends, All Rights Reserved. social | 32
- 33. Site & Content Attributes Location: where on the site the action takes place Category: the general category of the action Name: the actual name of the action Type: the type of action performed web mobile © 2011 Webtrends, All Rights Reserved. social | 33
- 34. Webtrends Tags • Base JS tag: standard tag for Webtrends Analytics that generates a log entry • WT.mc_id: Webtrends campaign ID (used to capture media placement IDs) • WT.tsrc: Webtrends traffic source parameter (used to capture organic sources) • WT.z_loc: Custom tag (used to track where on the site an action occurs) web • WT.z_cat: Custom tag (used to specify the category of actions) • WT.z_name: Custom tag (used to specify the name of an action) mobile • WT.z_type: Custom tag (used to specify the type of action) © 2011 Webtrends, All Rights Reserved. social | 34
- 35. Media Metrics Spend: how much am I paying to get my message out there? Impressions: how many eyeballs are exposed to my message? Responses: how many people are compelled by my message? web Response Rate: how efficient is my media at getting people to respond? mobile Cost per Response: how much does it cost me to get a visit to my site? © 2011 Webtrends, All Rights Reserved. social | 35
- 36. Web Metrics Visitors: unique number of people who came to your site Visits: number of sessions on your site Bounce Rate: % of people who landed on your site but did not engage further Visits per Visitor: number of times people return to your site Return Visit Rate: % of total traffic who come back to your site web Visit Duration: length of an average session on your site Views: number of pages rendered on your site Views per Visit: average number of pages rendered in a session mobile Conversion Actions: number of engagement actions performed Conversion Rate: rate at which engagement actions are performed social Cost per Conversion: cost of driving a user to engage AOV (if ecommerce): average size of an order placed on your site © 2011 Webtrends, All Rights Reserved. | 36
- 37. Linking Systems Together • Aligning media IDs to WT.mc_id enables integration • Several dependencies to ensure process works as expected o Ability for agency to pass media ID value used by ad trafficking tool as value in Webtrends parameter o Standardization of naming conventions in the lookup o The ability for agency to provide campaign lookup file Campaign Attributes Media Attributes web Media Metrics mobile Media Campaign Campaign Platform Channel Tactic Site Creative Spend Impressions Responses ID Name Type Red 001 BTS Consumption Desktop Display Roadblock MSN $2250 1,375,432 16,441 760x124 Blue 002 BTS Consumption Mobile Display Takeover Yahoo $5000 4,217,319 127,392 1024x768 003 004 Soundstage Soundstage Flanker Flanker © 2011 Webtrends, All Rights Reserved. Mobile Tablet Display Display Banner Point Roll social Pandora Spotify Rock 365x75 Metal 365x75 $1750 $1975 865,712 773,408 12,401 10,966 | 37
- 38. 1-to-1 Relationship Spend Impress Attract Respond Browse Engage Convert Ad Serving Placement ID WT.mc_id Webtrends web Tool Analytics MEDIA WEB WT DI Lab Attributes Metrics Campaign Attributes Metrics Database Attributes • • • • • • Campaign ID Campaign Type Campaign Name Launch End Platform • • • • • Spend Impressions Response Response % Cost/Response mobile Data Visualization • • • • Location Category Name Type • • • • • • Visitors Visits Bounce % Visits per Visitor Return Visit % Visit Duration social • Channel • Views • Site • Views per Visit • Tactic • Conversions • Placement • Conversion % • Creative Type • Cost/Conversion • Creative Name • AOV • Creative Size © 2011 Webtrends, All Rights Reserved. | 38
- 39. Topic 5: Client Stories How has Webtrends helped others solve these problems? web mobile © 2011 Webtrends, All Rights Reserved. social | 39
- 40. Red Bull Case Study © 2011 Webtrends, All Rights Reserved.
- 41. Business Challenge 40+ campaigns per year $2M digital spend per campaign 5 agency partners creative, dev, display, search, and social 6 weeks average campaign duration • High volume campaign activity • Complex digital ecosystem • Limited understanding of performance • Desire to integrate media + web data through Multi-Touch Attribution © 2011 Webtrends, All Rights Reserved. | 41
- 42. Solution Overview Created a replicable process for measuring campaigns at Red Bull, and developed an interactive web-based dashboard that provided insight into digital media and content effectiveness This included the creation of: • Measurement & learning plan • Tagging strategy • Agency processes • Development of a web-based dashboard • Ongoing analysis & insight © 2011 Webtrends, All Rights Reserved. | 42
- 43. Data Visualization + MTA Web-based data visualization • Streamline reporting • Enhance time to insight • Provide comprehensive view • Actionable through visualization © 2011 Webtrends, All Rights Reserved. | 43
- 44. Business Value Webtrends provided Red Bull with a holistic 75% reduction Number of agency reports delivered picture into campaign performance across all >100% reduction Time to compile campaign reports digital channels to $200K reduction streamline reporting Billable consulting for basic reporting and maximize return on ad spend © 2011 Webtrends, All Rights Reserved. | 44
- 45. Microsoft Case Study © 2011 Webtrends, All Rights Reserved.
- 46. Background © 2011 Webtrends, All Rights Reserved. | 46
- 47. Business Challenge $30M digital spend across various media and social channels 15 international markets running localized content 13 agency partners supporting all aspects of campaign execution • No underlying measurement strategy • Lack of standards and governance across markets • Siloed data between disciplines • Difficult target and loose performance metrics © 2011 Webtrends, All Rights Reserved. | 47
- 48. Webtrends Solution Webtrends provided Microsoft with end-to-end support through campaign planning, vendor management, and ongoing analysis and recommendation Measurement Data Analysis & Strategy Integration Insight • Assisted agency partners with • Designed process for merging • Established reporting cadence to defining campaign objectives media data with web data share data across agencies • Developed Measurement & • Established reporting cadence to • Developed deep actionable insights Learning plan to map out key share data across agencies based on robust integrated data set success events • Integrated behavioral and attitudinal • Helped deploy recommendations • Worked with Microsoft to build data at ad level for deep insight into with agencies, and measured performance benchmarks users incremental impact © 2011 Webtrends, All Rights Reserved. | 48
- 49. Business Value • Unified measurement approach • Consistency in tagging and tracking • Adoption of standardized processes • Automated reporting • Quick time to analysis • Actionable insight and recommendations © 2011 Webtrends, All Rights Reserved. | 49
- 50. Final Thoughts © 2011 Webtrends, All Rights Reserved.
- 51. Items to Remember • Establish a process • Define campaign success • Identify attributes • Map out metrics • Design tagging strategy • Link systems through ID • Create data visualization • Determine paths to conversion • Understand role of media channels © 2011 Webtrends, All Rights Reserved. | 51
- 52. Questions? © 2011 Webtrends, All Rights Reserved.
- 53. Thank you Brandon Ralls Director, Digital Intelligence Lab © 2011 Webtrends, All Rights Reserved.
Notas do Editor
- INTRODUCTIONGood morning everyone. I want to take this opportunity to welcome you all to the webinar, and thank you for attending. I am very excited to share with you my thoughts on effective campaign measurement through integrated reporting. This is a topic that is near and dear to me – as I spend much of my time helping marketers get more insight into the performance of their digital initiatives.
- QUICK BACKGROUNDBefore we begin, let me first introduce myself and provide a quick background on my perspective. For those of you I haven’t had the pleasure of working with, my name is Brandon Ralls. I am Director of the Digital Intelligence Lab here at Webtrends. I have spent roughly half of my career in the agency world providing strategy around digital campaigns – both consumer focused and B2B. Since leaving the agency world, I have been managing consulting practices, and have been focused on using the insight gleaned from my time with agencies to identify specific gaps that exist in campaign measurement, reporting, and analysis. What I have seen is that there are several challenges that marketers face with stitching together the story of how users interact with their brand in the digital space. Part of this is a result of disparate technologies – part is a result of a lack of measurement strategy to enable a holistic view of performance across digital channels. Through the Digital Intelligence Lab at Webtrends, I am focused on developing solutions that change the way marketers interact with data. I believe data doesn't have to be intimidating. I believe in the power of data visualization. Through beautiful, inspiring, and actionable data visualization we provide insight that empowers marketers to make better decisions about their digital initiatives.
- TOPICSWith that said, there are a few key topics I want to focus on during our time together today. My hope is that after this session, you will have some answers to these questions that will guide you toward more effective measurement and reporting of your digital campaigns, and hopefully expand on the insight you are able to gather about how your campaigns are ultimately doing. These questions are:What are the challenges measuring campaign performance across multiple digital channels?What is cross-channel, or multi-touch attribution (MTA)?How can integrated reporting enhance my understanding of digital marketing campaigns?How do I implement campaign tracking to enable integrated reporting and MTA?How has Webtrends helped other clients address this challenge? Keep in mind these are not necessarily “simple” problems to solve. In fact, companies are allocating large percentages of their overall digital investment to drive towards deeper insight. So, let’s dig in, and start changing the way you think about campaign measurement.
- TOPIC 1 The first topic I’d like to discuss: How do I understand campaign performance across multiple channels?
- DIGITAL LANDSCAPELet’s take a moment to talk about the current digital landscape a marketer is faced with, and some of the challenges it creates. It goes without saying that digital marketing has become increasingly more complex over the last few years – both in the strategies that are employed, and in the number of channels that are at our disposal. 10 years ago, it was all about paid search and display advertising. Although these two channels still account for an overwhelming majority of digital spend, there are new channels emerging that are making it difficult to measure how a campaign is actually doing. Social media, video, blogs, mobile advertising, email, affiliate networks, and many other channels create a complex web of interaction that can be difficult to understand if you are not able to stitch them together.
- WAYS TO ENGAGEI wish I could say that it ends there. In reality, we are also left to find what type of content resonates most with our audience once they have responded to our media. This could be landing pages, hero images, specific CTAs, videos, whitepapers, promotions, lead gen forms, downloads, special offers, printable coupons, and more. The list of possible actions combined with the number of digital channels results in a dizzying web of user engagement that needs to be rationalized.
- AGENCY NETWORKIn addition, most of the companies I work with have an equally complex network of agencies supporting media planning, the media buy, trafficking, creative messaging, asset creation, site development, reporting, etc.
- AGENCY NETWORK
- AGENCY NETWORKThe challenge here is that we end up with silos of data that are disjointed, often with different cadences of when data is delivered, and in different formats. The story is often difficult to understand. Having come from an agency, I know that it can be challenging to deliver a message to a client that a campaign is underperforming – especially if we executed the strategy. Oftentimes you will see the analysis of data presented in a way that it minimizes the negative aspects of performance. But, the reality is, the story itself is not really complete. It tends to be either media data ONLY or site data ONLY, but rarely is it a true integration of the two for the complete end-to-end picture.
- BEHAVIOROur objective is to find a way to link the specific media placements that are exposed to users, to the specific actions they are performing on our site. But, it’s not as simple as just stitching the two together – the idea is to provide as much context about what attributes are influencing user behavior. As we work toward an optimal media and content mix, understanding the relationship of what people see, what drives initial response, and how that media messaging relates to content they are exposed to on your site will enable a clearer understanding of how to target specific users through messaging that resonates, and how to drive desired behavior through engagement actions that will intrigue your audience.Remember this important point – it is up to us to create an environment that will drive desired behavior. It is not good enough to throw assets into market and hope that they lead to desired behavior.
- DIGITAL ECOSYSTEMIn front of you now is a simplified representation of the relationship between media and web, and the core pillars of thought that need to be addressed as a part of your campaign strategy. This includes a specific measurement strategy for how you will link these disparate systems together, a data architecture that will allow for consolidation of data across multiple sources, a data visualization that captures the essence of what is going on, and time for ongoing analysis and insight. It is through this solution framework that we are able to optimize both our digital media, and our user experience to maximize our return on ad spend. This visual really captures the essence of the work we do for our clients on the Digital Intelligence Lab.
- TOPIC 2 Now, let’s expand on this notion of integrated campaign reporting, and address the question:What is cross-channel, or multi-touch attribution (MTA)?
- MTA OVERVIEWSo, now that we have a general sense for the challenges we face, and the areas we need to be thinking about, let’s talk for a moment about the concept of cross-channel, or multi-touch attribution (also referred to as MTA). Historically, the approach to attributing engagement to a specific media placement or creative rotation has been done using what we refer to as “first click” or “last click” attribution. First click implies that if a user interacts with more than one piece of media you have in rotation, the subsequent engagement action would be credited to the first interaction the user had with your media. Last click is essentially the opposite – if a user interacts with more than one piece of media, the engagement action would be credited to the last interaction the user had. Last click tends to be the most common approach to attribution with the clients I work with, but has it’s challenges – as it does not really represent the role that each channel played in driving the engagement, or the influence a particular media placement had over the users actions. More recently, the notion of “equal” attribution has been a way of addressing this at a high level. Equal attribution implies that if a user interacts with multiple placements, each interaction is given equal weighting in terms of influence on the final conversion action. It wasn’t the first touch that drove the engagement, it wasn’t the last – it was a combination of all of them. In an ideal situation, a true media attribution model would be developed that could determine specifically what influence each channel had in driving that action, and the weighting would be assigned proportionately (usually via an algorithm). This is the most sophisticated method of media mix modeling – so for the time being let’s focus our discussion on the notion of first click, last click, and equal attribution.
- EXAMPLE SCENARIOI think these concepts are best represented in a sample scenario. An example of this would be – a user is looking to buy a new laptop. He searches for a relevant keyword on Google, clicks on a paid search link to come to the manufacturer’s site. He lands on a landing page that features some new products. He browses through the products, but does not actually complete the purchase process. The user then leaves the site, and a few days later, while browsing the web, is exposed to a banner ad on Wired.com that showcases one of the laptops he was considering. The banner drives a second response to the site. He researches a bit further, but still the user does not convert. Finally, while scrolling through status updates on Facebook, a friend makes a comment about how awesome their laptop is – which happens to be the one he was considering. The user searches for the specific model of laptop on Google, comes to the site a third time via an organic search link and actually purchases the new device.
- EXAMPLE SCENARIO In this scenario, if we were to apply first click attribution, the paid search keyword would be given credit for the purchase of the laptop, and the display ad and organic search would receive no credit.
- EXAMPLE SCENARIOIn the case of last click, the organic search would receive the credit for the purchase, and it would appear as though media is not driving conversion – which is obviously not true.
- EXAMPLE SCENARIOIn the case of equal distribution, each of the three channels would receive equal credit for the conversion, and you could start to understand the role that each channel plays in driving that purchase activity.
- EXAMPLE SCENARIOThis to me is a key point – the ROLE that each channel plays. Does the media channel tend to introduce users to my brand (first click), does it play a role in influencing users to engage (subsequent clicks), or does it tend to support converting users (last clicks). Understanding the role each channel plays, and the relationship of the channels to one another allows us to think about our media strategy, and allocate media dollars accordingly – to ensure an optimal mix of channels, tactics, and placements is in market.
- TOPIC 3 Now that you have an understanding of what MTA is, let’s discuss: How can integrated reporting with MTA enhance my understanding of digital marketing campaigns?
- DECISIONSAt the core of all of this, the idea is that you want to make your media dollars generate a higher return. That means you want to drive more people to your site, at a lower cost per conversion. The elements that feed into that equation are relatively simple: You spend money to drive impressions of media. If media is targeted toward an appropriate audience, and compelling in its message, it will drive response. From a media perspective you want to increase your response rates and lower your cost per response. From a site/content side, once someone has responded to your media, you want them to engage. If users simply bounce from your site, your content did not align to your creative in your media, or the user was not targeted. Either way, this is money thrown out the window. You want to increase engagement rates by having an effective user experience that surfaces relevant content that drives deeper engagement. This will ultimately increase your engagement rates, and lower your cost per conversion.
- KEY AREASThe idea is to capture data that will enable you to make educated decisions about the following key areas:AUDIENCE – Who you are sending?CHANNELS – Where you are sending them from?CREATIVE – What are they seeing that is driving their response?CONTENT – What do they do when they land on your site?ACTIONS – What content drives continued action? By having the user experience linked together from initial impression all the way to final conversion, you are able to begin to understand where people are exposed to your media, what drives response, what specific media drives engagement, and how effective certain combinations of media are at driving conversion. By adding in the ability to look at this data across channels in a multi-touch fashion, you are able to understand the role that each channel is playing in driving the targeted user toward conversion. You can also see which channels are driving inefficient traffic that does not engage – so you can begin to make decisions about where you should allocate your media dollars to be most effective.
- SAMPLE REPORTSample report…
- SAMPLE QUESTIONSHere is a list of sample questions that can be answered with this type of view into campaign performance: What platforms are users engaging with to be exposed to my media?Should I invest more in emerging platforms like mobile?What is the role that each media channel plays?Are users more likely to engage with certain media channels over others?How do certain media channels drive continued action on the site?Are there certain publishers that are driving more qualified traffic?What specific media tactics are users responding to?Is there something specific about those placements that encourage user response?What specific creative executions are users responding to?Do certain creative types encourage higher response? One of the biggest challenges I see in working with clients is not that they have a hard time coming up with the questions they want to answer – it is in coming up with a measurement strategy that enables them to actually answer the questions with any degree of certainty. The unfortunate reality is that without dedicated budget, resources, and time for planning, it will be difficult to get a clear understanding of what is going on. Measurement of a complex environment like this requires coordination between internal teams, external vendors, agency partners, etc. The next section will begin to provide you with a framework for understanding how to approach actual campaign measurement at the tactical level.
- TOPIC 4 I’d like to spend a good amount of time talking through this next section:How do I implement campaign tracking to enable integrated reporting and MTA?
- ATTRIBUTESLet me start this section by saying that many years of working in Excel have completely ruined me. I tend to see the world as one giant pivot table – with a hierarchy of information, the attributes that align to each level of granularity, and the relationships that are present at each level. It is kind of nerdy – I know. But, thinking in terms of hierarchy and attributes is one of the keys to understanding your campaigns. To start to make sense of such a complex, ever-changing digital ecosystem, we have to be able to break it down into more simple components. Let’s talk about topline components, and then break it down.
- HOW DO WE DO THIS?
- ESTABLISH A PROCESS
- ESTABLISH A PROCESSA typical structure I encounter quite often is one agency managing display, one agency managing search, one agency managing social media, one agency managing creative, and one agency managing site development. Working with 5 agencies or more requires a great deal of coordination (as I’m sure many of you can attest to). That is why it is highly recommended to establish a clear process for how this type of integrated tracking is going to be enabled. The components of this process are: Measurement & Learning PlanThe M&L (as we call it) captures the objectives of the campaign, the attributes about media and content, and the metrics that will be used to measure campaign effectiveness Tagging GuideThe tagging guide provides the agencies with visual representation of what media and what content needs tags, and how to deploy those tags. Campaign LookupThis is usually an Excel document that is provided to the agency. This document illustrates what information is captured for each individual media ID.
- CAMPAIGN ATTRIBUTESOne of the first pieces we will need to address is defining our specific campaign attributes. This can include the campaign type – was it brand awareness focused, promotion focused, product-specific, etc. This can also include the campaign name, the goal of the campaign, the launch dates, the amount of time in market, etc. The point here is we start to provide ourselves with bits of information about our campaigns that let us compare across campaigns (not just within a single campaign):Campaign Type – Seasonal PromotionCampaign Name – Back to School 2012Campaign Goal – Target new college students with promotions on latest laptopsLaunch – July 2012End – September 2012
- AUDIENCE ATTRIBUTESThe next piece we will want to address is our target audience. Who are we actually trying to engage with during our campaign? Working through this exercise of defining our audience, we will often map out a list of attributes that align to our target. This can be done through different personas, a series of use cases, etc. The point is, we are narrowing down the attributes that will represent who we want to be talking to, and will help us make decisions about where we should be having a conversation – to ensure we actually are capturing the audience we want to speak with. Here is an example of that user who we were targeting in our previous example about the laptop:Gender: MaleAge: 18-24 years oldGeo: In the United StatesSituation: Going off to collegeObjective: Looking for a new laptopFocus: Focused on portability vs. processing powerDesire: Want something cool and cutting edgeDigital Space: Highly engaged in social mediaPlatform: Highly engaged on mobile
- MEDIA ATTRIBUTESNow that we have captured the detail about our campaign, we can begin to outline the detail for our actual media. This exercise usually involves creating some sort of hierarchy of information about your media that we refer to as a campaign lookup, or campaign translation. As you work with your media agencies, these are the points of information you should have aligned to your media buy. Many times the agency is filling this information as a part of their planning or trafficking process, but we have found that there is often no standardization in naming conventions, and limited client input on what the categorizations should be for media attributes. My recommendation would be to get more involved in this upfront planning prior to campaign launch. Here is a representation of the structure that we tend to use with our clients in a campaign lookup:Platform – a device where the user is exposed to your media (mobile, tablet, desktop, etc.)Channel – the various types of media that you buy (paid search, display, social, video, etc.)Publisher – the sites where users are exposed to your media (Google, wired.com, etc.)Tactic – the channel-specific method for delivering media (banner, keyword, post, etc.)Placement – the actual name of the ad that is displayed to a user (aligns to ad serving tool)Creative type – the method for delivering a message (static, flash, video, expandable, etc.)Creative size – the size of the actual placement that was displayed (usually aligns to display)Creative name – the version of the ad that was displayed (messaging, images, CTAs, etc.) By having this level of granularity with our campaign, we will ultimately be able to drill very deep into the specifics of what elements drove different types of behavior with our audience.
- SITE & CONTENT ATTRIBUTES (20)The next piece is the site-side actions we want to capture. Part of your campaign planning should be aligning the goals of the campaign to specific actions you want your users to take on your site. These actions should be developed in a way that they tell you something about who the person was, or what their intent was on the site. Once these actions are identified, you will want to capture the following relevant information about each action:Location – where on the site did the action take place (home page, landing page, hero, etc.)Category – what was the general category of the action (video, white paper, lead form, etc.)Name – what was the actual name of the action being performed (friendly name)Type – what was the type of action being performed (play, share, click, referral, offsite link, etc.) The goal here is to start to identify patterns in the types of actions visitors from different types of media are likely to perform, and if there are any specific criteria about those actions that make them more relevant.
- TAGSThe tagging structure used to enable integrated campaign reporting is made to be as streamlined as possible. Only a handful of tags are used to capture a great deal of information – since much of the information about the media placements are in the campaign lookup file that maps to the ID. Here is a breakout of the tags that are used: Base JS tag – the standard JS tag for Webtrends Analytics that generates a call to form a log entryWT.mc_id – Webtrends campaign ID (used to capture a specific media placement)WT.tsrc – Webtrends default traffic source parameter (used to capture organic sources)WT.z_loc – Custom Webtrends tag (used to track where on the site an action occurs)WT.z_cat – Custom Webtrends tag (used to specify the category of action a user performed)WT.z_name – Custom Webtrends tag (used to specify the name of an action a user performed)WT.z_type – Custom Webtrends tag (used to specify the type of action a user performed)
- MEDIA METRICSThe last piece of the puzzle is defining relevant metrics – and hopefully performance targets/benchmarks. For media and web, these are usually pretty straight-forward. Let’s start with media:Spend – how much am I paying to get my message out there?Impressions – how many eyeballs are exposed to my message?Responses – how many people are compelled by my message?Response Rate – how efficient is my media at getting people to respond?Cost per Response – how much is it costing me to drive someone to my site?
- WEB METRICSFor web, there are more metrics at your disposal – keep in mind these metrics may be different if you have an ecommerce business:Visitors – the unique number of people who came to your siteVisits – the number of sessions on your siteBounce Rate – the % of people who landed on your site but did not engage furtherVisits per Visitor – the number of times people return to your siteReturn Visit Rate – the % of total traffic who come back to your siteAverage Visit Duration – the length of an average session on your siteViews – the number of pages rendered on your siteAverage Views per Visit – the average number of pages rendered in a sessionEngagement/Conversion Actions – the number of specific engagement actions performedEngagement/Conversion Rate – the rate at which engagement actions are performedCost per Engagement/Conversion – the cost of driving a user to engageAverage Order Value (if ecommerce) – the average size of an order placed on your site Once you have defined all of your metrics, and established basic targets, or performance benchmarks (which could be based on past performance), it is time to start thinking through how you want to connect your various data sources.
- LINKING SYSTEMS TOGETHER (22)For most of the campaigns that I support, my clients are using some combination of the following:Media trafficking and reporting tool – DoubleClick, Atals, Marin, etc.Email delivery and reporting tool(s) – ExactTarget, Epsilon, etc.Site Analytics tool(s) – WebtrendsSurvey tool(s) – ComScore, Foresee, etc. Without the ability to link these systems together, it is nearly impossible to have a true understanding of integrated media performance. That said, we have devised a relatively intuitive process for how we can link information from disparate systems and consolidate into a single data warehouse. Here are basic concepts of the process: Each system creates its own ID for a campaign, placement, and creative. This hierarchical ID structure aligns to the specific attributes we discussed in previous slides. Let’s take for example display media that I am managing through DoubleClick. My agency has set up a media plan that outlines the attributes for a particular ad that goes into rotation. DoubleClick assigns this ad placement a unique ad ID. For each placement that is executed with a different version of creative, DoubleClick assigns a unique creative ID. This combination of ad ID and creative ID aligns to a single unique ad that is in market. The goal is at the time of trafficking to pass this unique ID into Webtrends campaign tracking parameter WT.mc_id. So, for example, a user would be impressed with a display banner. This would attribute spend and an impression to a unique ad and creative ID. Once the user clicks on the display banner to come to my landing site, a response would be credited to the same ID. When the user is redirected to the site, a query parameter would be passed in the destination URL for WT.mc_id that would include the value of the ad creative ID from DoubleClick. Any subsequent onsite behavior would be attributed to this campaign ID in Webtrends Analytics.
- 1-to-1 RELATIONSHIP (23)By having a 1-to-1 relationship between the ID being used in DoubleClick, and the ID being passed in to Webtrends, we are able to attribute all media-specific metrics to the ID in DoubleClick, and then merge that information with all of the site side behavioral data coming from Webtrends that is aligned to the same ID. Our ID that is shared between the systems essentially becomes the key to join the disparate data sets in our database. This process is the same for all media-related tools that drive traffic to our site. The challenge is in identifying the appropriate ID that is used by your media tool to capture the lowest level of granularity in the reporting coming out of that tool, and pass that ID into Webtrends campaign ID (whether programmatically, or on redirect to the site). At a minimum, enabling this process requires some upfront thought to determine an ideal data collection/merging strategy. In most cases, it will also require coordination with your agency who manages your media. In the case of many of my clients, this could mean working with several agencies and/or vendors.
- TOPIC 5 Let’s review a few specific examples:How has Webtrends helped others solve these problems?
- Red Bull’s main challenge is simply the volume of campaign activity that occurs each yearTheclient spends most of their time managing their agency partners from an execution standpointThis leaves little time to actually dig into campaign performance, and even less time for optimizationSince most campaigns only run about 6 weeks, the client doesn’t usually get reporting from their agency until the end of the campaignBy that time there is nothing that can be done until the next campaign goes liveIn addition, the client has limited understanding of how users interact with multiple campaigns across multiple channels and platformsThis lack of understanding means she is not able to get a read on how effective her digital spend is at achieving her marketing objectives
- Webtrends stepped in to create a process that the agencies could follow These processes ensure that campaign goals/objectives are captured, that success measures are identified, and that campaigns are tracked in a way to ensure integration between channelsWebtrends assists with media and site tagging guidesIn addition, Webtrends also created a web-based data visualization solution to provide overall campaign performance, media and web specific performance, and cross-channel performanceThe idea is to help optimize both WHO we are sending to the site and WHAT they are engaging with once they are there
- Webtrends has created a number of solutions to help marketers understand cross-channel (or multi-touch) performanceFor Red Bull specifically, Webtrends created an all up campaign report that summarized media specific metrics, web metrics, and engagement metricsWebtrends also created an interactive channel specific report that showed adoption by platform, channel, publisher, tactic, creative, etc.In addition, custom views were created to help Red Bull understand the role that each channel plays (Introducer vs. Influencer vs. Engager) and what combinations of media are most effectiveTogether, these views allow Red Bull to have a comprehensive view of integrated campaign performance across many digital channels at the click of a mouse
- The impact of this effort has been tremendous from a time/cost savings standpointOver the course of a year, the cost savings associated from efficiencies in report consolidation alone justify the expense of the solutionThis does not even begin to account for the incremental cost savings from being able to drive more efficient engagement through optimized mediaTogether, the cost savings ensure Red Bull is maximizing their ad spend and capturing their ideal audience on a per campaign basis
- This slide sets up the background for the Cloud Power campaignIt outlines the objective of establishing Microsoft as a leader in the Cloud Computing spaceThe target audience is defined as Enterprise IT Decision Markers (a tough nut to crack)The goal of the campaign was to drive awareness and positive perceptionTo achieve this, several messaging/creative strategies were deployed across web/mobile/social
- This campaign was of extreme importance to Microsoft as it was the first opportunity to frame them as a leader in the cloud computing marketThere was substantial investment in the initiative, and over 15 international markets were participatingThis resulted in a complex network of agency partners supporting all aspects of campaign execution (creative, dev, media, mobile, social, globalization, etc.)The challenge was that no single entity was driving an overarching measurement strategy, and no one had thought to create measurement standards to ensure consistent tracking across the international marketsAdditionally, once data was flowing, it was being delivered in very siloed buckets that made it difficult to understand what was really going onBecause the target audience was difficult to capture, and the awareness/perception based success metrics were relatively fuzzy, Webtrends stepped in to help ensure the campaign would be a success
- Initially, Webtrends helped with defining overarching campaign goalsThese goals were then translated into measurable proxies that could be used to get a sense for successThese success events were captured in a Measurement & Learning plan that was shared across agencies and foreign markets to ensure standardizationNext, a process was established for integrating data between media and webThis included the development of a dashboard template to automate the ongoing reporting processThis same dashboard was used across all 15 markets to ensure everyone was measuring success in a consistent fashionEach week, snapshot reports would be provided on campaign success, and each month a full blown analysis would be performedThese reports linked media interaction with web behavioral data, and tied both to attitudinal survey data to create a holistic view into engagement + perception