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Customer Analytics

Shopper occasions scorecard to segment trips and share of occasions

The retail client is a multi-brand store allowing shoppers the convenience of shopping everyday needs through 50+ stores. They wanted to understand the purchase basket of shoppers to identify the shopping occasion, segment shoppers based on trip type and learn about the attitude and behaviour of shoppers. They also wanted to develop a scoring system to categorize shopper occasions and generate insights on store experience, promotions, store layout and assortment.

What is in the cart?

The retail client used correspondence analysis to identify shopper attitudes and segment them into different occasions.

Correspondence analysis for shopper occasion segmentation

Measure the share of shopper occasion by each segment

Identified motivational drivers and need state that drive these occasions

The retailer is vulnerable to losing shoppers for six out of the twenty shopper occasions owing to competition, assortment and convenience.

Challenges from ecommerce & competitors

The client is a major retailer with 50+ stores across different regions. They have been facing increased competition from ecommerce players, brick and mortar chains and mom and pop stores. They believe a major part of their challenge is driven by their limited understanding of why shoppers visit their stores and the attitudes that drive shopper purchase behaviour. They also want to understand their competitive positioning and benchmarking of shopper occasions.

The first objective is to identify shopper occasions based on product basket. Using these occasions, they want to rank occasions on different metrics to measure attractiveness and challenges. They also want to develop a scoring algorithm to classify, benchmark and monitor shopper baskets. Finally, they want to measure the retailer’s share of occasion types and identify their strength and weaknesses.

Integrated approach for shopper delight

The client improved their understanding of shopper occasions, the attitudes and drivers of shopper behaviour.

We then developed an algorithm to rank shoppers based on their purchase basket. This allowed the shopper to benchmark themselves against competition and review their:

a. Assortments and merchandise

b. Promotion strategy

c. Store layouts

d. Store experience

The study also helped them identify their strength and weaknesses against competitors. They were able to identify new opportunities, prioritise their focus on specific shopper occasions and identify their vulnerabilities in 6 of the 20 shopper occasions.

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