How grocery stores make us pay more ( part 2 of 3)

There is a solution but before we introduce it, we should talk about the retailer side of things and what is happening as we speak to try to gage the effectiveness of in store advertising, which in theory should lead to increase sales. Lets start by a few definitions.

CPM , Cost Per Thousand:

is a methodology of selling advertising. a CPM of $10 means that an advertiser must pay $10 for every 1,000 impression made.

ROI , Return on Investment :

is a termed used to figure out if an investment was successful or not. It is determine with a numerical value. To determined the Return on investment there is a simple calculation :

ROI = Gain from investment - cost of investment / Cost of investment

POS Display & POP Display : Point Of Sale and Point of Purchase displays

are displays that are at , close to the cash or in the isle. They are used to “feature” a product.. The two terms are often used interchangeably so we wont try to make a huge difference between both. here re example of POP and POS displays.

SKU: Stock-keeping Unit

is unique identifier for each distinct product and service that can be purchased.

The Issue with grocery stores (in my opinion) is that there is no ACCURATE way to determining the CPM (Cost Per Thousand) and the true ROI of most in-store advertising. However, there is no denying that in-store advertising is where it’s at.

In fact, 74% of purchased decisions are made in-store and 30% of brand decisions are also made in-store. Knowing this, it is no wonder why retailers and consumer brands have been trying to crack the code to in-store advertising. “Cracking the code” would mean increased sales; however, it does not imply a reduction in failure rates.

If advertising could have a double purpose and serve both as advertising and as a market research tool, then great consumer insights could be gained and a possible reduction in failure rates could be observed. In my opinion, this is one of the main reasons why the traditional CPM (Cost Per Thousand) model is flawed, when it’s applied in an in-store environment it does not provide the evidence of the impression, therefore an advertiser is charged without the proof of the exposure that was paid for. . Furthermore, since no evidence is currently provided, it is difficult to truly determine the ROI (Return on Investment) since there is no way to determine that an impression is DIRECTLY responsible for a purchase. I am not saying that ROI (Return on Investment) cannot be obtained in the present situation; simply that it is not optimal.

To add to this less optimal problem, all the data (information) provided is not real time, so reaction can only be taken on past events thus ignoring the current situation. In other words, by the time some information gets analyzed, it’s already too late. To end this, in 2006 a P&G (Procter & gamble) study was proposed to determine once and for all the actual effects of in-store advertising, its effectiveness with various advertising mediums in-store. The $1 million project, which took place over four weeks in May, relied on infrared sensors to track store traffic. To have significant data, the study will need to be replicated in many other markets and environments, making it an extremely costly endeavor. This should demonstrate the need to understand the true effect of in-store advertising.

Traditionally, the way consumer brands and marketers have been monitoring their results is by doing live testing of campaigns and comparing the effectiveness of each, in order to have the campaign with the ultimate result. For example, let’s imagine a new Crest toothpaste. Two stores are selected, store “A” and store ”B”. Both have similar demographics and consumer traffic. Both also have the same advertising. In Store “A” the toothpaste is $1.29 and in store “B” it’s $2.29. At the end of the research period, sales from both stores are compared. Surpassingly, Store “B” had more sales. It is therefore determine that $2.29 will be the price of the new toothpaste. I’ve simplified enormously and have made a ton of assumptions; hopefully you understand the basic premise.

This methodology of market research is well established as an accurate way of doing market research. It should be noted that similar focus group test are made before launching a product, the issue is that consumers in focus groups are not always honest and the information gathered does not always represent the reality. One of the main issue with these methodologies is that when it comes to in-store advertising, the variable affecting the perception and relationship between product and consumer is so grand that ultimately the results lead to a 70% to 85% failure rate. In other words what affects the purchase of a product is not only it’s price and where it’s sold but it is also the price of all other products, the advertising of all other products, the stocking of all other products etc.

The fact that this month, Company “A” (Crest) has a POS (Point of Sale) display at the cash and Company “B” (Colgate) the competitor, has a display in the isle, will have a different effect than if Company “B” (Colgate) has a display at the cash and Company “A” (crest) in the isle. Furthermore, every SKU (Stock-keeping Unit) in the store also has negative, neutral or beneficial effect on Company “A” (crest) advertising message and by the same, extends Company “A”’s (crest) brand and sale. WHY? Because every product is competing for the consumer’s golden $$$.

In fact, this challenge is so important that P&G (Procter & Gamble) created the position of Director of First Moment of Truth (FMOT), to produce in-store displays that can command a shopper's attention.

But what happens when other firms are doing the same strategy? My theory is that as shoppers, we build a relative “immunity.” Please read my article, titled “Advertising game theory metrics, The Impossible game” for my personal takeon the matter.

To further illustrate the issue with in-store grocery advertising and the CPM (Cost Per Thousand) model let’s compare it to television. In television, if a brand wants to advertise a new feminine product

they can choose the channel, time slot and even know what kind of show is playing at the time their ad will come on. For instance, it would make no sense to advertise while a typically male dominated show is playing. That logic, however, cannot be applied in a grocery-store environment. Ads cannot be up Mondays and Thursdays between 6 pm and 9 pm when the proper target market visit. Let’s assume that the target market represents 1000 customers that visit the grocery store 2 days a week. How is it justified that the CPM (Cost Per Thousand) price is then on the 6000 unique visitors the store receives every week? That is like saying that an ad during American idol should have the same worth as an ad during prison break or desperate house wives. It does not have the same worth; it does not have the same market.

Furthermore, if we ignore the over pricing and assume that the price is based on the 1000 visitors that fall within the target market, the question is, what is the true audience? For instance, Nielson uses the People Meter (PPM), a tool that is used to measure the viewing habits of TV and cable audiences. No such tools currently exist for grocery stores. Therefore there is no tangible data on statistically representative impressions.

As a result of the current model, consumer brands learn about very little consumer insights, since the advertising does not return live data. Since no live data are offered proving the value of in-store advertising and its different implementations. POP, POS, floor ads, etc. cannot be properly assessed.

Therefore, certain in-store advertising implementation may be dramatically undervalued or overvalued. In any case, the sheer amount of advertising that confuses clients and the lack of proper data is, in my opinion, one of the major causes of product failure.

This should be of concern not only for retailers and consumer brands who face lower profit margins but also for consumers since this inefficiency results in higher prices.