Leveraging Micro Retail Analysis to Build Macro Sales
By Marcus Gault, Client Services Manager, ACNielsen

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As Account Managers are increasingly driving high value from key account epos data, only now are manufacturers waking up to the true power of store level key account data with applications ranging from merchandising and stocking, to store compliance checking and assisting with sales target achievement.  Store level data is the new frontier for micro-account management and while its analysis requires time, attention and a process to deal with it, it can add millions to a brand’s bottom line.

Making £9m in a year

Take a recent micro-level investigation into sales of a well-known FMCG brand, where the account manager undertook a store-by-store analysis of all stores within a key account across the UK.  The study looked at how and why category sales varied between stores, in order to achieve maximum gains in sales and hence profit.  From the data, it was apparent that there was a wide variance between the under-performing and over-performing stores: in the worst-case scenario, the category made up only 5.6% of grocery sales, while in the highest-performing store, that figure was 11.2%.  The estate average was 7%.

The differences in category performance were found to be based on either in-store presence, layout, or overall category portfolio.  Most notably, however, the analysis found that 10% of the stores provided 55% of the development opportunity – i.e. if the bottom 10% of performing stores were brought up to the estate average of 7%, the category would make £5m more in sales, while if all the underdeveloped stores were brought up to the estate average, the category would make a further £9m.  Indeed, the analysis was such that the Key Account Manager was able to pinpoint exactly where the gaps existed and could see, at a glance, which stores had the largest opportunities and by how much.

Using the data to best effect – the commercial applications

Clearly any opportunities highlighted through store level analysis requires effective execution at the store level. There is a lot of information in this analysis that can raise a multitude of issues and opportunities, and companies like ACNielsen are already developing the tools to process the raw data more easily and efficiently, which will make huge strides in saving key account managers a lot of time in analysing the mountain of information that is being generated.

In the above example, many actions were planned and agreed between the manufacturer and retailer as a result of its analysis.  These included, promotional compliance in all stores and new layouts and range assortments in some stores.  For the manufacturer, brand sales increased in the under-performing stores by nearly 50% in one year whilst the category grew significantly.

That is one example of a well-executed campaign to raise sales.  Broadly speaking, there are 4 levels of commercial application for micro store-level analysis.  They are: 

• Benchmarking individual store performance.

• Monitoring store compliance to head office agreements such as price implementations and distribution agreements.

• Creating store clusters within retail accounts for various analyses such as:

  • Geographic analysis

  • Demographic analysis

  • Sales force analysis, such as commonality of stores

  • Market testing and control clusters

  • Distribution depot clusters

  • Bespoke analysis clusters

  • As a tool for field sales teams 

Perhaps the most obvious case for store level analysis is in compliance of stores to head office agreements.  Through store-level analysis, Key Account Managers can see which stores are implementing distribution agreements or pricing promotions and where there are discrepancies the retailers’ head office can be informed.

As we have already established, another constructive use of store-level analysis is to look at and benchmark individual store performance for your products.  For example, Key Account Managers can analyse their product sales in stores across the UK and work out why there may be vast discrepancies in sales from one store to the next, even in stores of the same size.  

One fish producer, for example, used such analysis to try to work out why he was selling thousands of packs in some stores and only a handful in others.  The cost to his business over the busy Christmas period could have amounted to £10,000 per store per week, but he was able to rectify the problem – a simple case of the fish being poorly displayed in the low performing stores – because he received the almost live data on a weekly basis which meant he could take action right away.

So what does this mean for Key Account Managers?

Well, it means that customers should start realising the opportunities of micro-managing their businesses.  Not just on the practical level of checking that their products are in stores and are priced or promoted correctly.  There is also a strategic level to micro-analysis – that of overall brand performance.

Store level data is already widely available in a variety of formats.  It is up to you to think about how this data can be applied to your brand.

For further information, please contact:
Kim Dunkason, ACNielsen Communications
Tel. 01865 732275
Email: kim.dunkason@acnielsen.co.uk

www.acnielsen.co.uk

Date article published: 30/04/2003