Case study

Precise attribute modelling uncovers 6.8% of incremental sales 

By partnering with Retail Insight, a global grocery retailer was able to more accurately identify the key drivers of store performance.

A global grocery retailer partnered with Retail Insight to get a better understanding of the major drivers behind its financial performance. 

Discover how we helped them use the power of precise attribute modeling to uncover key insight and identify new sales opportunities. 

Retail Insight Solutions

Takeaways

6.8%

incremental sales

Range of individuals 

A global grocery retailer wanted its entire Merchandising function to be able to
identify and understand the major drivers of financial performance.

Many decisions were based on individuals’ knowledge and experience, but
without any consistent process, measures or accountability to understand
when, and more importantly why, variance from the plan occurred.

Readily integrated 

We partnered with internal Analytics, Merchandising and Finance teams, to define and prove a hypothesis; that using available internal and external data, it was possible to accurately identify, isolate and quantify the key drivers of monthly store sales performance.


Our structured approach considered four key stages:

  • Framing the challenge to clarify users’ key needs
  • Creating the building blocks by creating a living database of over a thousand potential modelling attributes
  • Developing a reusable and scalable capability by training our Performance Engine to model monthly category store sales and isolate the primary drivers 
  • Validating the opportunity by demonstrating a highly predictive model which explained 86% of the sales variation, without using any historic sales input

Realistic incentives 

Clear diagnostic scorecards prioritised the tactical actions for Merchandising and
Stores to focus on, categorised by those which each party had control over, at
the same time democratising this insight to provide a single consistent view of
the facts, from head office to stores.

Strategically, the ability to more accurately predict category performance
provided insightful support to the annual budget setting process, ensuring that
achievable targets were set across the business and identifying an incremental
6.8%pts of sales opportunity to achieve.

 

Summary

Together, the retailer and Retail Insight identified 6.8% of incremental sales opportunities.

Clear diagnostic scorecards help teams prioritise tactical actions. 

Highly predictive model explains 86% of sales variation without needing any historic sales input. 

The retailer can now set achievable targets across the entire business

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