Closed-loop Marketing Framework

1. LEVERAGING DATA & TECHNOLOGY
FOR CREATING CONNECTED
EXPERIENCES
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Confidential and for intended audience only

2. INDIA’S LEADING ASSET MANAGEMENT COMPANY
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OVERVIEW:
CLIENT BRIEF:
This AMC manages client investment assets of over Rs. 1 trillion (~USD 14bn) for
over 1 million investor folios. The company is today one of India’s Top 10 asset
managers by AUM, with a seasoned team and deep, on-the-ground presence across
over 46 cities and serving clients across over 280 towns in India.
Unify the customer data and
create a data hub to drive
campaigns with better reach and
conversions
Audit and advise on the existing
technology stack’s capability to
achieve the vision of Segment-of-
One
Building automated processes
to ingest and execute highly
personalized communication from
the current recommendation
engine

3. DISCOVERY & FINDINGS
 Starting with a detailed pre-discovery session, we conducted multiple discovery workshops to understand the business processes
 Key findings from the above activity were deciphered as follows:
Invested in
platforms that
builds a strong
tech infrastructure
 There was a lot of scope for
leveraging insights from the
recommendation engine
 The need for protecting and
encrypting due to the
regulatory and compliance
requirements
 One-size-fits-all approach for
campaign execution lacked
the customer awareness and
engagement
 Need for dynamic content to
handle the market volatility
 The channel of
communication was not taken
too much in consideration
before execution of these
campaigns.
 This led to low open rates,
higher unsubscribes and
increase in churn
 Carpet-bombing approach led
to a huge wastage in
campaign execution budgets
 Increase in connect with
customers is required for
cross-sell and up-sell
opportunities
 TAT in sending market/
product related information to
Distributors can reduce
substantially
 The customer began their
automation journey by investing
heavily in a data
recommendation engine that
has capability to share 1-to-1
recommendations.
Industry Regulations,
Under-utilized Assets
and Traditional
Approach for
Customer Reach
Scope for
personalization &
reduction in churn
%
Opportunity for
better conversions
within the same
marketing spends
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4. PROPOSED SOLUTION & IMPLEMENTATION
 We implemented the Martech stack and automated the marketing campaigns for effectively sending communication across channels like
SMS and Emails
 Integrations with legacy systems like client’s recommendation engine for pulling data into the tech platform were setup
 Built a customer single view that is scalable and flexible to accommodate on-the-fly changes in attributes. This enhanced the ability to
personalize communication for every single recipient who is a part of larger dataset
 Moving away from the traditional one-size-fits-all approach for campaign execution, we built a custom ‘Close-loop Campaign
Operations Framework’ that is scalable and measurable at every stage
• Define customer value
propositions
• Define marketing
objectives
• Identify customers/
segments to target
• Define rules and filters
• Define offers,
frequency and
messaging
• Identify content,
channel
• Real-time
Segmentation
• Trigger Campaigns
• Hyper-personalisation
• Map responses to
objectives
• Optimize campaign
rules
• Reports and
dashboards
Customer Value
Proposition
Define
Campaign
Execute
Campaign
Track Campaign
Responses
Closed Loop Marketing
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5. Product Data
Customer Data
Segments
Channels Of
Communication
Customer Single View In Martech Platform
Analytics Data
Distributor Campaign
Cross Sell
Campaigns
Reminder Campaigns
Engagement
Campaigns
Trigger Campaigns
Demographic Data
Industry
Benchmark
Attribution Data
Audience Profile
Delivery Logs
Email Response Data
SMS Campaign Data
Other Channel
Response
Campaign Report
Recommendation
Engine
Product Data
Transactions
Customer Data
Sources of Data
from Client
Distributor/
Investor Data
sFTP / API Email
SMS
Encrypted
Execution
Encrypted
Responses
Other
Channels
PROPOSED SOLUTION ARCHITECTURE
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Source Data Other Data Campaign Workflow Campaign Data

6.  Personalization, Upsell and Cross-sell campaigns are now based on insights from the ‘Big Brain’ i.e., recommendation engine and
Martech stack’s Intelligent predictive algorithms
 Custom development in existing marketing technology stack & introducing AI capabilities to measure the hour-part efficacies has
completely automated process of sending the most relevant campaigns with the right message to the right customers at their most
preferred time
 Managing communication for multiple stakeholders with automated & dynamic & in-the-moment sender personalization for:
o Investors (both direct and via advisors)
o Distributors
RESULTING BUSINESS BENEFITS
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7. 1.
Identified opportunities for the
next communication cycle and
sending campaigns only to the
relevant populations has helped
in reducing the sends by 80%
Mass Fragmentated Targeted One-to-One
Implemented Customer Experience Framework
24 Weeks
MEASURING IMPACT
5. ROI for last FY was over 2X
2.
Conversion rates on campaigns
against the control set has been
very high. The average lift in
conversion rate for last 12
months has been over 3X
3.
The increase in Online
transactions for 12 months
ending July 2020 over the 12
months transactions ending July
2019 has gone up by 9%
4.
With automation using SFMC,
the TAT for sending market
/ product related
information to distributors
(channels) improved from 1
week to 1 day
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