Teaching a man to fish: The true value of in-store training

An article written by our Director Rhys Jones for FMBE magazine, which explores the value of training in-store sales colleagues.

Like most agencies that specialise in technology, many of our clients invest large sums of money in the training of in-store sales colleagues in the hope that this will lead those colleagues to upsell their products to consumers. After all, the old adage of ‘teaching a man to fish’ vs giving him a fish would seem to ring true.

The trouble is most traditional forms of ROI analysis routinely fail to detect an uplift from such activity thereby creating the view amongst clients and agencies alike that training either does not work or is measured by more intangible measurements like a build-up of brand equity or advocacy amongst in-store colleagues.

Whilst the latter of these views is undoubtedly true, our work with a number of our agency and brand partners has indeed shown that training does in fact have a tangible sales benefit, albeit one that uplifts sales in a slightly subtler way than more traditional forms of in-store activity such as active selling or merchandising.

To illustrate this, let’s start by examining the impact of in-store training versus that of active selling immediately during or after the activity took place in store. Indeed, this is often the timescale over which most traditional forms of ‘trial versus control’ analysis are conducted:

From this, it’s clear that active selling massively outperforms in-store training by a ratio of 3.2 to 1, which is obviously where our initial assertion around in-store training not working comes from. However, using such a timescale to observe results fundamentally ignores the point of in-store training in the first place: that is, whilst more modest initially than actively selling to a consumer, training should lead to a more sizeable uplift in sales in-store, but at a fraction of the cost of the visit given store staff are essentially ‘free’ advocates for the brand from an agency or brand point of view.  

Indeed, using a much wider timescale in our analysis than is traditionally used, we found exactly that to be the case.  By statistically testing a range of ‘legacy effects’ for both training and active selling, we found that, on average the effect of training lasts for around 3.1 times longer than that of active selling:   

Factoring this into our uplift calculations, we found that training, therefore, actually generates an uplift that is on a par with active selling albeit over a much wider timescale. However, perhaps more importantly, such an uplift is generated at a fraction of the cost given that the uplift generated by active selling is quite time and resource intensive in that by its very nature it requires agency personnel to be ‘active’ in-store in order to generate the uplift. Training, conversely, simply requires agency personnel to impart their knowledge to store staff; with the bulk of the uplift being created by the essentially ‘free’ resource in-store over a much greater time period. Taking this into account, we found that, in terms of ROI, training actually outperforms active selling by around 31.2% overall:


It’s clear, therefore, that ‘teaching a man to fish’ is a far more economical use of resources than actually fishing for him when it comes to promoting brands in-store: but the industries definition and measurement of ROI needs to adapt to how activity is designed to work, rather than being a ‘one size fits all’ definition.


Time is money: but how much time should you spend in store?

An article written by Rhys Jones, Director of Retail Alchemy, for FMBE Magazine which poses the question around just how much time should clients be spending in store to make the most put of their visit.

A commonly asked question by many of our clients is exactly what amount of time they should be spending in store. After all, as the saying goes, ‘time is money’ and optimising the time you spend in store is crucial to ensuring that maximum possible ROI is extracted from a visit.

But how do we go about measuring the optimum time? The answer, as it turns out, lies within a fundamental economic theory called the law of diminishing returns. First postulated by famous economists like Adam Smith and David Ricardo, the law states, basically, that there will come a point where adding additional amounts of a raw material that is used in a production process will actually cause the incremental gain in output to fall. In classical economics, this fall was attributed to a decrease in the quality of input raw materials as more and more were used, but the same logic can be applied to activities typically undertaken on a field visit in-store.

Take, for example, merchandising activity within FMCG: initially, fixing on-shelf gaps in a store that has many gaps will provide a high rate of return vs the cost of time associated with visiting that store. However, as more and more gaps are filled, there will come a point where the gain in sales from fixing an additional on-shelf gap does not outweigh the cost associated with the additional time required to fill it. Similarly, but perhaps less obvious, is the relationship between time spent running technology demonstrations in-store and the rate of customer conversion to sales as a result of those demonstrations. Too many demonstrations and the quality of those demonstrations suffers: too few and your ability to catch the right consumers at the right time reduces.

Of course, all of this is just a theory without the empirical evidence to back it up. Our work with a range of different clients for tens of thousands of field visits across many different categories has allowed us to prove that just such a relationship exists:

Interestingly, although time in-store varies from client to client, category to category and activity to activity, one overriding theme emerges: that clients, as a whole, simply don’t spend enough time in-store as they should. Our findings suggest that our clients should increase time in-store by anywhere between 7.7% to 46.9% in order to maximise ROI. Quite clearly then, agencies need to give equal thought to optimising time on visit if they are to truly maximise the efficiencies of their operations and in turn deliver maximum value to their clients.


Call file selection 2.0

Case Study published in FMBE Magazine on the importance of call file accuracy.

Selecting the right stores to visit is at the very heart of field agency

Activities. After all, focusing on the right mix of stores can lead to considerable efficiency gains for the agency and therefore maximise the ROI delivered to client.

But how to select the ‘right’ mix of stores? Many agencies rely on the tried and tested methodology that uses one of the many different consumer segmentation methodologies to identify stores that have the ‘right’ demographic group in their catchment. The idea being that selecting stores with the ‘right’ demographic will automatically lead to the selection of stores that will in turn generate the biggest uplift from in-store activity, thereby maximising the potential value for clients.

Whilst such approaches undoubtedly have their place, they often don’t tell the full story in terms how well a store is likely to perform should we choose to visit it. After all, many stores that are situated in a so called ‘good demographic’ areas often fail to perform when visited.

The reasons behind this is simple: focusing exclusively on external demographics ignores the role physical store design, shopper environment and even in-store promotion play in encouraging a consumer to purchase a product at a particular store.

Analysis of a cross section of post campaign results from a range of our clients suggests that this problem may be larger than many realise. Our analysis shows that as many of 47% of stores in a typical call file underperform versus the investment of time spent in store, implying that that time may be better spent visiting the rest of the selected stores more frequently, or indeed visiting previously unvisited stores.

Call File Selection - Pareto Chart


Figure 1: Pareto Chart showing the proportion of incremental sales generated from field visits to store versus the proportion of stores in the call file. Here some 53% of the stores generate 80% of incremental sales, with the remaining 47% responsible for just 20% of incremental volume.

So what’s the solution? Well here field agencies can take a leaf out of the management scientists book and employ a technique called the ‘balanced scorecard’. Developed as a tool to aid business strategic thinking, the balanced scorecard seeks to quantify all aspects of a management decision (be they financial, customer, process or growth related) and weight them according to importance so that a more balanced view than the normal pure financial view can be taken. In the world of store selection, such a scorecard could be adapted to expand the view of the store to take in all areas of the customer journey, from external factors, through to internal store design, product offers, competitor activity and even strategic reasons (e.g. store is a ‘flagship’ store) for visiting a store.

Indeed, this needn’t be a complicated process: such a scorecard can be as simple as working closely with the client to identify the key considerations when selecting stores, assigning some metric to them and then identifying the weights to use for each factor so that the optimal mix of stores can be arrived at.

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