Retail data value

Data-driven businesses rely on analysis of evidence to direct decisions and actions. A systematic approach to collecting, managing and analysing your retail customer data helps you to make complex decisions with confidence


How can I maximise the value of customer data through innovation?

You and your colleagues collect many data from your retail customers - sales, availability, distribution and maybe service and stock levels? In some companies, the same data is collected multiple times by multiple teams before being fed into standard reports, usually in spreadsheets. With all of that data you would think that data-driven approaches to innovation would be commonplace... but they rarely are. How do you use data to innovate?

The most common challenges are the scale, inconsistency and multiplicity of the data - the very act of multiple teams collecting multiple versions of data from multiple customers results in a data management headache which blocks analysis, insight, understanding and action.

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Without robust, reliable, consistent, well-curated data your colleagues - category analysts, account managers, demand planners, product designers - are left with opinion and guesswork when addressing crucial, complex decisions:

  • How might we optimise our delivery case sizes to better meet customer ordering patterns?
  • Which of our products justify wider retail distribution thanks to stellar sales and which would we trade these for in a "one-in, one-out" shuffle?
  • Which of our promotions performs best and why? What changes could we propose to our customers that would drive incremental sales for us both without damaging the category?
  • Where should we be launching new product variants and how can we monitor their performance in the first days and weeks so that we can collaborate with our customers to adapt to shopper demand?

Too often questions like these are met with a shrug of the shoulders or, at best, a high-cost one-off analytical activity against one retail customer data set... an unrepeatable project that may deliver little, even after weeks of effort.

Modern FMCGs, however, treat data as an asset and take a long-term approach to its management so that they can address complex decisions with confidence. A single copy of curated data is organised consistently across multiple customers and is available to all authorised users at the click of a button.

  • Repeatability - analysis and reports developed for one customer can easily be run against any other customer with little or no effort
  • Consistency - patterns and insights discovered in one region, category or period can easily be explored and tested for in any other
  • Velocity - exploratory analysis can be started during the meeting in which a question is raised and answered within hours, or even within the meeting itself
  • Completeness - curated customer data can be linked once with any other data set - internal systems, market data etc. - to form part of a robust data asset supporting a holistic picture of opportunities and issues

SKUtrak enables all of this through its own interactive dashboards and serves the same curated data for use in your own tools through DataShare. SKUtrak conforms data from all sources to a neutral model so that you can report, analyse, explore, understand, decide and innovate with confidence

SKUtrak customers take informative, insightful, evidence-backed ideas to their retail customers who engage in discussion, consideration and collaboration on a raft of innovations: efficient new ways to package and ship products, creative ways to promote products and develop categories, and flexible ways to launch and adapt to shopper interest with new product development.

Atheon has shaped the way we work with retailers and opened up conversations with them. The SKUtrak platform is well structured in what we need and what we want to see.

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