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Identifying personas with micro-segmentation

Applicable Segment(s):


Impacted Function(s):

Marketing, Data

Solution Area:

Real-time CDP

Identifying personas with micro-segmentation


A large American supermarket chain.

The Challenge

The company was driving generic campaigns across the customer base due to a lack of insights into individual customer behavior, tastes, and preferences. This led to poor customer engagement and low conversions from campaigns.

The Approach

  • The company deployed a Real-time CDP. Its intelligence layer, supported by machine learning algorithms, helped create granular customer segments by applying RFM (recency, frequency, monetary) modeling.
  • This helped gain a deep understanding of a customer’s journey, identify products of interest, and utilize propensity models to gauge the likelihood to respond, buy, and churn.

The Result

Armed with the insights, the grocer was able to hyper-personalize marketing campaigns with respect to each customer’s preferences, transactional behavior, lifecycle stage, and promotional activity.

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Identifying personas with micro-segmentation

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