MANAGING INSTORE METRICS
Dr. Muneer Muhamed measures the return on investment of retail marketing
Fast-moving consumer goods (FMCG) marketers spend large sums to influence consumers’ POS purchasing decisions at retail outlets and supermarkets. This investment is necessary to reach customers while they’rein stores and ready to purchase goods.
A question that many marketers fail to ask themselves is whether these efforts accomplish their dual objectives of driving incremental sales and contributing to profitable responses. Indeed, the moment of truth is when customers reach the cash registers.
The answer lies in measuring the ROI of instore marketing investments.
Marketers adopt numerous methods ranging from discount stickers and instore TV ads to influence purchase decisions. Several different research methods measure sales responsiveness and ROI. For marketing events that occur frequently and are routinely tracked, statistical modelling is an effective and reliable measurement tool.
Sales data are available for most retail channels, and include detailed information on product sales and price. By using these in conjunction with known instore marketing activities, marketers can develop analytical models that quantify the sales response associated with each instore activity.
Consumer marketers routinely use such marketing mix models to measure the responsiveness of instore efforts – most commonly temporary price reductions, secondary product displays and instore coupons.
Marketing mix models quantify how each major activity contributes to changes in sales over time. Once measured, the increase in sales resulting from instore activities can be compared to the financial investment to measure ROI. In addition, marketing mix models are used to forecast future sales performance. The use of AI in marketing works best in such situations to drive decision making.
Modelling may not be an appropriate solution when the marketing elements are subtle or long-term in nature. Such is the case with new package designs, and forms of instore advertising and sampling programmes.
Marketers could then design instore experiments to measure the sales response. Divide retail chains into one or more test cells based on the number of marketing vehicles to be measured. Then select a group of stores comparable to the test stores where there’s no promotional plan. Finally, after an appropriate period, marketers can quantify the sales difference between the test and control stores using statistical techniques for evaluating controlled experiments.
When designing such tests, it is best to keep the objectives simple. Attempting to measure too much at once drives more complexity into the measurement and hinders the ability to understand what worked. Purchase cycles and seasonal patterns for products in testing may affect marketing effectiveness. So make sure the experiment has sufficient time to play out in retail stores.
To ensure that the intended instore marketing activities did in fact take place, ensure that periodic instore auditing is built into them. Instore auditors will confirm that relevant marketing programmes were in place at the appropriate time in test cycles.
Sometimes, the intended sales results of tests are not achieved simply because instore marketing events were not executed properly or were implemented only in a few stores. By discovering such errors early in tests, marketers may be able to make adjustments and salvage testing efforts.
When it is impractical or too expensive to test instore marketing effectiveness, consumer testing may be the right thing to do. For instance, if multiple package designs have to be tested, some with and without associated on pack promotion tie-ins, then it may be too costly to produce all the varieties of packaging of interest for instore tests.
It is also impractical to do so given that promo seasons will be short for most occasion specific events. In such cases, consumer survey techniques could be used to gauge their responsiveness. For example, advances in technology enable marketers to present consumers with a variety of realistic packaging or promotion depictions to measure the purchase intent.
Design technology along with consumer choice modelling tools such as conjoint analysis enables marketers to measure the efficacy of a variety of instore marketing scenarios at a relatively low cost. The main issue is identifying how to measure effectiveness – and you may want to seek external expertise in such matters.
Regardless of the marketing vehicles used to drive instore purchase decisions, FMCG marketers should invest time and resources to measure the success of instore marketing efforts. As a result, they will more fully understand what works or doesn’t, optimise spending across all instore marketing options and learn from past marketing activities. The business planning capabilities exist to quantify both the sales response and ROI of most instore efforts. So embrace AI for easier data management!
Sales data are available for most retail channels