April 22nd, 2013

Despite the fact that the consumer packaged goods industry is predictable and stable — or perhaps because of it — there seem to be an inordinately high number of aspiring futurists out there. Industry pundits breathlessly trot out the latest trend for such concepts as shopper marketing, digital marketing, loyalty card analytics, big data and store clustering. Yet despite all of these “seismic shifts” that we are told to expect just around the corner, we still work in an industry that considers strong growth as 4% per year, and normal as 2% to 3%.

What appears to have been missed through all of this investment and research and prognostication is the most important consumer segment in the entire industry: the promotionally motivated consumer.

Despite our best efforts to ignore the fact that trade spending is the largest piece of most companies’ marketing budgets — and it is still growing — we, as an industry, know very little about this extremely important consumer, who ultimately derives the benefit of all of this promotional spending.

Having studied promotional events through scanner data for the past 15 years, my company was interested in rounding out our knowledge of the role of trade and promotional dollars by understanding the deal-sensitive consumer. TABS Group fielded a study among 1,000 representative consumers age 18 and older. Consumers were grouped into buckets — first, based on their level of purchasing consumer health care products and, second, based on how they behave in seeking promotional offers to shop for these products.

Twelve percent of the consumers were not actively engaged in purchasing such categories as vitamins, analgesics, cough/cold and digestion. The remaining 88% fell into Light, Medium and Heavy Deal Seekers, and they are the base of respondents used for the statistics in this article.

An Active Deal Search strategy is one that requires active efforts to find a deal. These include freestanding insert (FSI) coupons, online coupons, switching stores to get the best deal and store circulars. By contrast, a Passive Deal Search strategy is one that provides the better value or deal to consumers without requiring them to make much of an effort to get the value. These include everyday-low pricing (EDLP), private label purchases, value sizes and bonus packs.

Our data clearly shows that it is the Active Search strategies that explain consumer buying behavior, while analysis of their Passive Search strategies provides much less shopper insight. Therefore, we are defining Heavy Deal Seekers only in terms of their levels of using Active Search strategies.

In fact, the degree to which we know how often a shopper uses online couponing or loyalty cards provides a huge amount of information on where they are likely to shop, how much they will buy and what their demographic profile will be.

Let’s go back to the Light, Medium and Heavy Deal Seekers. If we were asked to estimate how many more transactions per household are done by Heavy versus Light Seekers, what would we predict? Would we think there would be any difference at all? After all, isn’t the conventional wisdom that promotions really aren’t incremental, they just load the consumers and take them out of the market? If that is the case, then we would not expect any difference in the amount of purchasing per household done by the three groups.

In fact, Heavy Deal Seekers (those who use at least four of six Active Search strategies) account for 27% of all consumer health care buyers, and they make 62% more purchases of consumer health care than Light Deal Seekers (those who use zero or one Active Search strategies). Further, Medium Deal Seekers (30% of buyers) account for 33% more purchases than Light Deal Seekers.

These numbers measure transaction differences, and of course, the Heavy Deal Seekers will have a significantly lower price per unit than Light Deal Seekers. This difference, though, would knock down the gap to 40% to 50% versus 62% — still a major difference worth further investigation. Figure 1 illustrates the buying rate differences in these groups.

What other group of consumers out there accounts for such a high percentage of both shopper base and sales? Not affluent consumers, not natural and organic consumers, nor large families — no one.

Here we have a definitive cause-and-effect relationship that is corroborated with scanner data and loyalty card data analysis, yet no one in this industry seems to know or care about this dynamic. Maybe we should ask J.C. Penney chief executive officer Ron Johnson if he wishes he had a deeper understanding of the size and importance of deal-sensitive consumers.

Just to prove the point for the skeptics out there, let’s flip the data to ensure that we are seeing causation and not correlation. Now we group the consumers into four buckets based on their buying rates of consumer health care categories, from Tier I (34% of buyers, 11% of sales) to Tier IV (14% of buyers, 31% of sales).

From Figure 2 we can see that the heaviest sector buyers use both Active Search and Passive Search strategies in higher numbers than lighter buyers use.

However, it is their level of Active Search strategies that most explain their higher buying level. On Passive Search strategies, Tier III (20% of buyers, 28% of sales) employs just as many passive tactics as the heaviest group, Tier IV. These two groups are differentiated by the additional active measures that are taken to get a better value. In fact, the real pop in the data comes with their level of using online coupons and loyalty card ­promotions.

What interesting and actionable insights can we glean? When the real information and money-making ideas start is when we start delving into understanding the particular shopping patterns of these Heavy Deal Seekers. Here’s just a sampling of the most salient insights:

• They are much less loyal to specific retailers than lighter deal buyers. This probably isn’t much of a surprise.
• Much more of a surprise is that their outlet shopping patterns are significantly different from those of their lighter deal buying counterparts (how they differ will be discussed in a subsequent article).
• They are much more likely to come from the New England or the Great Lakes regions than other parts of the country.
• Women are much more deal sensitive than men, except in their equal use of EDLP and value sizes.
• Higher-income people are much more likely to use Active Search tactics than lower-income people.
• Loyalty cards do not build loyalty and, in fact, the highest users of loyalty cards are among the least outlet-loyal shoppers. These are the quintessential deal seekers. Knowing and understanding this, we can see what a skewed view of the world we get if we only rely on “loyalty” card data for our shopper insights.
• Heavy Deal Seekers are not choosing high/low promotions over EDLP or vice versa. They use both in large numbers. They treat these as different tools in their deal search arsenal as a way to derive a better value per unit.
• The most preferred promotional tactics vary significantly depending on the region of the country.
• As much as everyone wants to usher in the new digital era of marketing, the “old school” tactics of FSIs and circulars are still more preferred by these buyers than online coupons or loyalty card offers. Online and loyalty card offers, however, are much more efficient at pinpointing the deal-sensitive ­consumer.

Humans are economic animals, and a high percentage of these animals find it worthwhile to invest time and effort in lowering their overall spending for consumer health care by using promotional offers. The data strongly suggests that increases in the number of these offers will stimulate even more purchasing among these buyers. Again, this is corroborated by reviewing scanner data. The most obvious example is the consistent and significant growth in vitamins, particularly at retailers that promote the category aggressively and ­frequently.

Misguided paradigms are not easily broken, however, and we see in vitamins and in many other categories a desire of manufacturers and retailers to pull back on this heavy promotional activity. This is despite repeated communication and actions by consumers indicating that they like these deals and that they respond to them positively.

So are we, as an industry, truly shopper-centric? If so, then some open-minded thinking is in order, and companies need to take a new view as to the role that promotional offers play in the overall behavior of the ­shopper.

KURT JETTA is founder and chief executive officer of TABS Group Inc. He can be contacted at kurtjetta@tabsgroup.com.

Dr. Kurt Jetta, Ph.D. Dissertation

I could devote pages on end to a review of all of the interesting dynamics in those statistics as well as the results from the smaller manufacturers, but I will focus on what I conclude from just looking at the Top 15.  I will also add a few bits of commentary on the Tier 2 winners ($500MM+).  Here are just a few of my observations:

1.  It is the norm vs. the exception that the Tier I manufacturers underperform the market.  We have seen this pattern of Tier I underperformance for the majority of the past five years.  These companies tend to be so diversified (e.g. Pepsico, Nestle, P&G, and Unilever are in dozens of categories) that any positive trends in one area are often neutralized by declines in another.  Nestle is a particularly notable example of this dynamic:  growth in every sector but one (Frozen) achieved +2% growth or more.  Declines in Frozen, however, leveled the Vendor growth to just +1%.  This fragmentation and neutralization dynamic is the reason for Kraft splitting into high-growth, snack manufacturer Mondelez vs. large, stable and diversified Kraft Foods.
2. Given that these firms are not drivers of growth, retailers hurt themselves by reductions in non-Tier I vendors and brands.  In 2012 the growth was driven by companies less than $2B in sales (+4%).  The major growth companies (e.g. Green Mountain, Roll Global, Chobani, Starbucks and Driscoll’s) tended to be focused on one or two product categories.  On a smaller scale, a company such as Kind Snacks posted +137% growth from a single minded focus on Nutrition Bars.  It wasn’t until some major retailers loosened up their vendor reduction policies that Kind had a chance to shine.
3. The Top 15 have low hanging fruit that they typically choose not pick.  Stronger and more frequent promotions on their power brands would certainly add 2-3 points to their topline, and could be profitable if they structured their promotional deals correctly (see my theory on retailer price promotion that proves the incrementality of retail promotions).  Another area of opportunity is larger sizes.  Top 15 companies are susceptible to buy into the notion that larger sizes (i.e. Bonus, Value, or Family Sizes) of their power brands are not incremental to the brand or category.  TABS Group analytics haven proven repeatedly that a large size (not a Club Size, mind you, that’s a different issue) of a power brand (e.g. Hellman’s Mayo, Kellogg’s Pop Tarts) at only 20% incremental will deliver more incremental sales to the category than a low-selling, niche item that is 100% incremental.
4. All of the work with respect to Decision Trees, Loyalty Marketing and similar “fad” analytics (Big Data anyone?) are alchemy, at best, and outright lies at worst.  If we read the industry literature on all of the efforts and investment and insights derived from loyalty card data or market structure analysis, it most often comes from sources at the Top 15.  These companies are investing disproportionately in these areas, yet there is no obvious ROI being derived:  their growth rates are well below the industry total (0% vs. +2%).   The resistance to larger sizes in Point #3 is one by-product of the Decision Tree pseudo-science that almost always places Size as a very low importance attribute to consumers.  So in the case of Value Sizes (and Trial Sizes, for that matter), in empirical results – Value Sizes incremental at the brand and category level – contradict the decision tree models.  This, by definition, means the models are invalid.

So in summary when we have Top 15 results such as these there are only two paths for the underperforming companies to take:  get smarter with their analytics investment or reduce the investment and bank that money.  What these companies are doing now isn’t working.  Our philosophy and our entire business model at TABS Group is that you can do both:  you can generate incremental sales and profits by using innovative metrics and software that simplify and improve your analyses, while at the same time  reducing your data and analytics investment.  At some point this realization will seep into the collective mindset of the industry.  TABS Group is poised to respond to this megatrend when it happens.

About The TABS Group

The TABS Group is a privately owned company headquartered in Shelton, CT, with offices in Chicago, IL, Boston, MA, Los Angeles, CA, Dallas, TX, Boca Raton, FL, and San Luis Obispo, CA.

Kurt Jetta founded the TABS Group in 1998 as a service with a better way to conduct Sales and Marketing analytics in the Consumer Products Industry.  TABS has developed unique and affordable processes to strip out time and cost from the analytical process. Their methodologies are robust, proven, and put to work daily for dozens of clients across a variety of food, personal care, household, drug, and general merchandise categories.  Additional information is available on the company’s Web site, www.tabsgroup.com.

1.  Nielsen US AOC (All Outlet Channel) Data 52 weeks ending December 22, 2012