Customer segmentation and profiling helps a grocery retailer increase annual sales revenue by $17M


The client is a leading US specialty food retailer  offering a personalized shopping experience for its clients across 100+ stores.


  • The client was not able to gain an in-depth understanding of shopping behavior and customer preferences without a customer 360-degree view.
  • Conventional mass campaign strategies  increased marketing costs  and led to low conversion rates. 
  • Without a comprehensive customer engagement strategy , the average order value and basket size remained stagnant.


As a first step, to create a customer 360-degree view datamart, data from multiple sources like CRM, POS Data, online purchase data, and Campaign Management System was integrated.

An in-depth exploratory analysis was conducted to explore key insights  about customer demographics, shopping patterns, price propensity, etc. Insights from the analysis helped the retailer to understand key influencers  of purchase behavior, and create different customer profiles and genomes .

Tenzai employed its proprietary 6D Segmentation framework to develop a robust customer segmentation model for the client. The framework considered multiple attributes for segmentation like demographics, location, campaign response, channel preference, etc. 

In the next step, using clustering techniques the customer base was grouped into several unique clusters based on the category purchase patterns and preferences.  

The clustering model was overlaid with other segments like value, frequency, demographics, location, channel, price propensity, dormancy, etc. to create multidimensional microsegments for the retailer.

The customer segmentation model helped  in analyzing diverse customer groups and offer tailored solutions to each segment. The segmentation framework  also provided the retailer with  a better understanding of the current value and future potential for each segment. 

A customer segment dashboard was created to help business users track segment behavior and their performance across multiple KPIs.


The segmentation model was deployed in the customer’s cloud environment and integrated with CRM and campaign management systems.

The client used the segmentation framework to design marketing and engagement strategies specific to each segment. 

The segmentation and behavioral models helped the client to design an engagement calendar with segment-specific objectives and campaigns for the entire year.

The new engagement strategy driven by customer segmentation resulted in optimized marketing spends, improve sales revenues, and enhanced customer profitability. 

Key benefits include

  • A $17 million increase in annual sales revenue was achieved by implementing segment-specific engagement strategies.
  • Within the first year of implementing the segmentation strategy, average basket size (ABS) and average order value (AOV) increased by 12 % and 27% respectively.
  • Post-deployment, the client was able to increase the campaign conversion rates by 20% and – reduce marketing spends by 10%.