Assortment Planning & Assortment Rationalization

Retailers in all verticals are curious about the magical assortment mix. What’s the right balance between too much and too little? Which products will help reach customer and financial strategies? What attributes are important to my target customers? 

Assortment planning in fashion raises additional questions. How much to buy? What is size profile need by store? How to pack products and sizes for efficient distribution? Where to carry fringe sizes?

These are some examples of business questions data can help answer. Retailers are seeing benefit using data in these areas - better assortments mean stronger customer, sales growth, etc. Better purchasing decisions mean higher revenues, better sell-through, lower mark-downs.

How can We help?


WE CRUNCH DATA TO inform your assortment decisions

We perform deep dive analysis on assortment challenges to help retailers better understand customer demand and support business decisions.

  • Understand assortment strategies and challenges
  • Analyze large and complex data sets, such as customer level transaction data, browsing histories
  • Historical data scrubbing, consumer demand modeling and other advanced analytic methods
  • Deliver attribute insights, decision trees/rules, size profiles
  • Share strategic insights and recommendations

Examples could include depth and breadth analysis, attribute analysis, demand transference modeling, consumer decision trees, sizing strategies, for example.



Whether you are currently using or implementing assortment planning or rationalization solution, Cognira can help you get quality results that meet your objectives.

  • Review user processes and business objectives
  • Update system configuration, improving usability and optimization strategies
  • Analyse data for solutions, including size profile optimization, like-item automation, etc.
  • Refresh and tune system parameters, such as consumer decision trees, demand transference, etc.
  • Customize enhancements

System related services could also include cleansed sales history, attribute analysis and others.

Where else do we help retailers get value from data?

How can you better leverage analytics?

We'd love to help!