Best practice use case guide


Leveraging data with AI for payment and credit card issuers

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AI – The paradigm shift in customer lifecycle management

Most data sources provide deterministic data – e.g., credit card transactions – which are used by traditional business intelligence to create insights such as purchase probability for a financial product. Marketing departments then use probabilistic data to create campaigns that target certain segments of customers. This approach is leading to challenges such as top customers being targeted disproportionately often and campaigns not being timed optimally per individual customer. In contrast, AI solutions allow for optimizing the omnichannel customer experience by addressing the right person at the right moment on the right channel.

Utilizing first party data with AI can overcome the challenges of the “cookieless future”

Most browsers no longer support tracking by third-party cookies. Google has announced that the Chrome browser will stop accepting third-party cookies in 2023. Marketers will have less information about online customer behavior, and brands will be less able to reach customers with targeted messages – unless they can make customers accept first-party cookies and use artificial intelligence to exploit available data as effectively as possible.
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Contents of our whitepaper

Executive summary
Page 2
Preface and table of contents
Page 3
Introduction customer lifecycle management (CLM)
Page 4
AI – A paradigm shift
Page 5
Data in the customer lifecycle
Page 6
Introducing AI
Page 7
Campaign automation along the lifecycle
Page 8
Applying Machine Learning models
Page 9
Scaling personalized campaigns
Page 10
The holistic CLM model
Page 11
Phase 1: Attract and acquire
Page 12
Lookalike audience and email re-targeting
Page 13
Boost customer acquisition
Page 14
Personalization & checkout funnel optimization
Page 15
Dynamische und personalisierte Check-out-Funnel
Page 15
Phase 2: Activate and incentivize
Page 16
EMOB – customer activation
Page 17
Spend incentivation
Page 18
Upsell to platinum card
Page 19
Up-Sell zur Premiumkarte
Page 19
Cashback and loyalty
Page 20
Services – dunning/receivables management
Page 21
Phase 3: Cultivate and retain
Page 22
Retention and anti-churn
Page 23
Page 23
Status quo portfolio
Page 24
The art of the start with CLM
Page 25
About Acceleraid
Page 26
Michael Altendorf Acceleraid Testimonial

„Machine Learning is the automation of data science. Automated Machine Learning models boost productivity when it comes to personalized customer interactions along the lifecycle and increase scalability. When data is the new oil, payment providers sit on the biggest nearly untouched oil field. Machine Learning will become the keystone of future revenue models of payment providers and card issuers​.“

Michael Altendorf
CEO & Co-Founder, Acceleraid


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