Category analytics focuses in on the optimal way for a retailer to structure the categories in their store, extracting the useful knowledge from data through price elasticity, strike rate, loyalty and substitutability, basket drivers and time bound analyses. 


Category analytics can help to answer business questions such as:  

  • What are the optimal price points for products in my category? 
  • Which products drive people into my store?
  • How loyal are customers to certain brands within the category?
  • What are the influences on substitutability with certain products? (price, flavour, size, functionality, range availability, type of customer etc.)
  • How can I optimise my product range?
  • How do I avoid excess inventory past best product use date?

One of the major obstacles for companies wanting to understand more about their categories is accessing and cleaning the data so it can be analysed.  Once the data has been extracted and loaded, we normally carry out simple ‘sense checks’ to identify any areas of concern within the data.  From here we develop an understanding of the structure and content of the data.  Where necessary, we cleanse or transform the data further, and remove any outliers, thus creating a single, clean data set for analysis.

Next, we get down to the analytics.  Depending on the client’s objectives we look at any of the following:

  • Strike Rate
  • Price Elasticity
  • Basket Drivers
  • Time Bound Analyses
  • Loyalty and Substitutability

Product Loyalty and Substitutability is an important component of Category Analytics.  It looks at how loyal customers are to certain brands and how they’ll react to certain discounts and promotions – effectively what decisions people make, what products they switch back and forth between, how they make their decisions etc.  This is useful because more you understand about product substitutability + loyalty, the better job you can do at ranging and commercial negotiations with suppliers, and the more insight you’ll have into consumer decision making, hierarchies and processes around product.



  • Optimising the range - understand which products drive people in stores, understand loyalty and switching behaviour
  • Avoid excess inventory past product use date (expiry, new season etc)
  • Customer satisfaction – ensure high value customers feel valued (offer special deals on products preferred by HVC)
  • Insights around consumer decision trees
  • Develop a clear proposition around bundled offers or pricing strategy
  • Understand shopper typology at a deep level based on actual behaviour

Industries covered:

  • Retail
  • FMCG
  • Telecommunications
  • Utilities
  • Travel and Tourism
  • Insurance


Price Sensitivity


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