The research

The return on investment (ROI) generated by different types of in-store activity is vast. Information Resources (IRI) has found for example that new in-store fixtures or display stands provide an average increase in sales of £1.60 for each £1 spent on the activity. In stark comparison, in-store sampling, and direct marketing on average provide a return of less than 20p of additional sales per pound spent. Other media found to be successful were the use of in-store merchandisers (people who go in-store to check and correct the fixture layout), and in-store posters, delivering £1.36 and £0.95 per £1 spent respectively.

“My theory for the varying ROI from different in-store activity is that the closer an activity is to the point of sale the better the short term uplift – although more “remote” media (eg TV) will have a bigger long term impact”, Richard Lawrance, Senior Consultant, Information Resources speculates.

To reach these insights IRI’s consulting team compiled a database using information from its recent evaluations of in-store and local marketing media. It highlights the large differences seen in return on investment gained from this type of activity. Activity types analysed included in-store demonstrations, new display stands, frequent re-merchandising activity (changing the shelf layout), in-store posters and direct marketing.

Lawrance explains, “Using this comprehensive and unique database of store-specific sales data, our consultants can group a retailer’s stores into those that have received certain activity and compare this to a group of similar stores with no activity. By factoring out the expected sales trends, we are able to isolate the uplift in sales from the activity in question”.

In addition to this type of evaluation, other store level research by IRI has shown that return on investment increases when the activity is targeted to high potential stores or shopper demographic.

Value of the store level

Realising sales opportunities isn’t easy. But by knowing what’s happening in-store – and there are nearly 2,000 across the leading four major supermarkets alone – you can see the differences between them. The opportunity from exploiting these variations is too good to miss. “The variation in brand share across the chains can be astounding. For example, a major drinks brand with a 52% share of their sub-category in Sainsbury’s, has a share ranging from 33% in one store to 93% in another. If this manufacturer had built their marketing plans assuming the average share, they would be missing the mark in most stores” says Lawrance.

Research by IRI and McKinsey in the US suggests that increasing the sales of underperforming stores to the average can generate an overall 15% increase in sales in some categories. IRI works with many manufacturers and retailers to help them exploit this opportunity in three key areas: • Planning – identifying where the opportunities are and targeting resource • Execution – monitoring if plans are being executed so that remedial action can be taken if necessary • Evaluation – finding out how well the plans worked

The best laid plans

The key to a successful marketing campaign is careful planning. Store level data allows this planning to be targeted where it will have the most impact. To take the example of a major pet food brand, 25% of sales in one of the major multiples come from only 18 stores and half the sales come from just a quarter of stores. This is powerful information when planning any sort of in-store activity.

• Promotions or product launches can be targeted on the top performing stores where the impact on overall sales will be greatest • Why are the top performing stores doing so well? Is it the demographic profile of their shoppers? Is it the local competition? Is there some in-store best practice that can be rolled out nationally? • Action can be targeted on the underperforming stores to bring them up to category average e.g. field marketing, training, localised advertising or planogram revisions Many manufacturers are using this approach to target field sales teams or field marketing agencies to specific stores. Recent research by IRI in the US involved dividing the field sales teams of a manufacturer into two groups during a product launch. One group was empowered with store level data, while the other group was not. On average, the group with store level data achieved 39% higher distribution levels than the group without.

Closer to home several major FMCG manufacturers in the UK have realised significant benefits by focusing on just the stores that contribute most to the business. For example by targeting their field marketing agency to address stocking issues.

As well as targeting, store level data can be used to plan tactically at a more local level. As many of the major retailers are moving away from national planograms, this gives brand owners the opportunity to exploit local variations in demand. Range, merchandising and other marketing tactics can also be modified according to the different competitive environment found in various store formats. Consider one major food brand with a 40% share in most Sainsbury’s stores, but over 60% share in the smallest stores. How will their tactics be different in the smaller stores where they are the only brand compared to larger stores where the fixture is more competitive?

Look and learn

Given that 85% of new product launches fail, it is critical to monitor sales during the first few weeks of a product’s life so that remedial action can be taken if required. Store level data allows this action to be targeted where it is needed. One launch by a major food manufacturer last year showed a significantly faster distribution build in Asda than in other retailers. The reason for this was their ability to access store level Retail Link data to monitor distribution and take direct action where there were problems.

Even where a launch is successful in terms of attaining distribution targets, there are many opportunities which can be uncovered using store level distribution data. One recent confectionery launch achieved over 80% distribution in Sainsbury’s in the first three weeks, and generated over £125,000 of sales in the first 12 weeks. Yet even in this successful launch, 75 of the 100 largest stores suffered at least one week out of stock, and five of these stores did not stock the product at all. If these issues had been addressed, the product could have realised an additional 10% in sales.

Richard explains, “Store level availability data can be used to identify ‘repeat offender’ stores, target field teams, spot patterns and evaluate lost sales. Sales and price data can be used in a similar way to monitor the execution of pricing and promotional plans”.

Maximising your investment

Of course, overall objective of any marketing campaign is to increase sales. According to Lawrance, “A major food brand recently used one of the leading field marketing agencies to maintain stocking levels and merchandising in store. By comparing sales in the stores on the call file with a control group, the sales impact was worth £3.72 revenue for every £1 spent with the agency. This compares favourably with IRI’s benchmark of a £1.36 RROI [revenue return on investment] for merchandising activity.”

Store level data provides an effective way of demonstrating payback from localised activities by comparing sales in a test panel of stores that received a particular activity with a statistically matched control group of stores that did not. This technique has proved highly effective in evaluating activities as diverse as direct marketing campaigns, field marketing agencies, poster sites, local radio advertising, merchandising, POS and localised promotions.