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Achieve riskless profits: the Analytical Business Solution: an analytical breakthrough that will change the way Manufacturers and Retailers Promote!


On the one hand numerous industry studies show that an overwhelming majority of manufacturers believe these promotions are unprofitable, difficult to manage, and damage their brand image over the long haul. On the other hand, other industry and academic studies have documented that the level of spending--both in absolute terms and as a percentage of marketing spending--has continually grown over time. The sales managers at these companies know that the promotions are a reliable source of short-term retail sales increases. The marketing managers reluctantly acknowledge that the effects of these promotions are more measurable than other forms of marketing investment--the "devil you know" dynamic.

The goal of this paper is to remove this ambivalence towards price promotions. Specifically, it will demonstrate that these promotions generate meaningful short-term sales increases, don't hurt the brand sales or image either in the mid or long-term, and provide the opportunity to make profits for both manufacturers and retailers. In fact, not only are the profits meaningful, but they can be riskless. You read that correctly ... a high percentage of brands have the right conditions to generate profits with zero capital costs. To grab these Riskless Profits, though, there are several structural and measurement barriers and faulty paradigms that all parties must overcome. This paper will lay out those barriers, provide the model for riskless profit generation, provide real world examples of where the theory has become reality and provide easy next steps for the reader.


Any organization truly serious about generating Riskless Profits needs to remove the flawed paradigms and conventional wisdoms about RPP (see Exhibit A). Even if we magically whisked away all the counter-productive paradigms in the market there are still legitimate barriers to broader manufacturer participation in RPP. Specifically, it is the retailers with control of these events: retailers control the final price discount, the margin requirements, the ad costs, the event timing and, most important the qualitative factors of these events (e.g. ad location, ad size, consumer message, etc ...). Obviously, with manufacturers subsidizing a large portion of promotion events, they have some influence on promotional execution. However, a retailer having the final say on promotional execution adds a level of profit uncertainty to manufacturers that inhibits their optimal use of RPP. Furthermore, an academic study by Srinivasan et al in 20046 showed that, in general, manufacturers derive more financial benefit from RPP than retailers. This imbalance is a significant factor in retailer promotional requirements becoming more stringent over time and thus a significant factor in manufacturers becoming even more negative towards retailer promotions. An oft-cited goal of category management professionals is the desire to increase manufacturer-retailer collaboration. In order for collaboration to occur, however, there needs to be a high level of trust between parties. One thing that greatly facilitates trust is that both parties are certain that each has access to the same information when making collaborative decisions. It is at this point where we reach perhaps the greatest structural barrier in the process: that is, margin information is asymmetric. Manufacturers have greater visibility to the total profit picture in the entire value chain than do retailers. Manufacturers know their own profitability, and they also know the retailer profitability. Retailers know their own profit structure, and usually not their vendor's. Here we see that retailers will be reluctant to fully engage in a new process to make Riskless Profits until they have better visibility into the entire value chain and are comfortable that they are not incurring a disproportionate amount of the promotional discount subsidy to consumers.



In addition to all of the structural barriers to RPP, there are measurement barriers as well. That is, what is the standard of measurement to decide whether promotions a) generate incremental sales and b) make money? To get to that answer, one needs an accurate estimate of baseline sales, i.e. retail sales in the absence of retailer promotion. Jetta and Rengifo (20097) documented that the current industry models of baseline sales--which are based on two academic models (Wittink et al--19888 and Abraham and Lodish--1993 (9)) are flawed in that they exhibit an excess amount of week-to-week sales volatility. More importantly, the baseline estimates are highly correlated to promotional activity. In other words, we see phantom spikes in the baseline estimate during weeks of promotional activity (see Exhibit B). Jetta (2008) showed that baseline sales estimates spiked by as much as 20% with the current industry model. By definition, baseline sales should be a relatively stable estimate of sales in the absence of promotion.

One other measurement issue for baseline sales estimates is that--even if the current estimates were accurate--collecting this data is very expensive to gather and is only available in the Food, Drug and Mass channels. The syndicated data services - Nielsen and IRI--have multi-million dollar infrastructures to collect information on display and feature advertising support. These costs are passed along to their customers. However, there are no baseline estimates available for such huge retailers as Wal-Mart, Sam's, and major category-killer outlets like Petco or Staples. For some CPG manufacturers, sales in non-tracked channels accounts for over 50% of their sales. Without an easily accessible baseline estimate, promotionsal effectiveness in these channels cannot be measured. Fortunately there is a new option available in the industry that enables manufacturers and retailers to accurately measure their promotions, and then structure future events that guarantee mutual profitability. The improved baseline estimate laid out in Jetta and Rengifo (2009) has been commercialized by TABS Group with the TABS Accurate Baseline[TM]. This model is more accurate than the industry standards because it reduces weekly sales volatility by over 80% and it eliminates the "phantom spikes" that CPG manufacturer are used to seeing in their current baseline estimates. We can see this revised model in Exhibit C.



Two other appealing qualities of the TABS Accurate Baseline are that the model relies only on Unit Sales to derive the baseline sales estimates. This means that the TABS Accurate Baseline model is available to any retailer, in any channel, that has scanner data. It also means that the data is much cheaper to deliver since it does not require a costly data-gathering infrastructure. In summary, the TABS Accurate Baseline eliminates a key measurement barrier to profitable promotions with a less costly, more extendable and more accurate estimate of sales in the absence of retailer price promotions.


To fully realize Riskless Profits, one must first accept that promotional sales lifts are truly incremental to the brand, category and retailer. There is no brand switching, there is no post-promotional dip in the short or long-term and there is no cross channel switching (Exhibit A). This theory was proven in Jetta (2008). We also need to assume the removal of all the structural and measurement barriers that impede optimal promotional execution and profitability: retailers and manufacturers share margin information, baseline sales can be measured accurately, and baseline sales estimates are available to all retailers with scanning data.

The last critical assumption is that we need to be certain of a reliable, lower-bound estimate of the sales lift for a specific promotional execution. That is, we need to know, with a high degree of certainty, what is the worst lift we can expect. The only way to build that with certainty is to analyze hundreds of events for a specific product across various retailers and various price points. The TABS Accurate Baseline model makes this possible since it generates these calculations in minutes. Once the lower-bound estimate is established, we can test for the potential to make Riskless Profits. We call this the presence of an Arbitrage Opportunity Condition (AOC).

Without going through an exhaustive mathematical derivation (10), the formula says that an AOC exists if the expected promotional sales elasticity is greater than a specific hurdle rate. This hurdle rate is a function of retailer margin percentage (m), product cost as a percentage of retail price (v), the manufacturer's share of the value chain profit (1-m-v), the consumer discount on Ad ([d.sup.A]) and Ad cost as a percentage of average baseline sales at the discounted price (A/[[d.sup.A]E(R)]).

This equation formally identifies not only the Arbitrage Opportunity Conditions, but it also formally explains why these conditions exist only for subclass of brands. First, the Ad Cost as a percentage of discounted weekly retail sales means that only manufacturers of a certain size can take advantage of AOC. A high Ad Cost as a percentage of sales (usually 1.0% of annual discounted sales) places an unattainable barrier to small brands. Second, 1-v (the value chain margin) must be

AOC exists if: g/d = E(|[[epsilon].sub.m]|[d.sup.A]|) [greater than or equal to] [alpha] + A/[d.sup.A]E(R)/1 - m - v - [alpha][d.sup.A]

sufficiently high to ensure there is enough margin left after the promotional discounts for both parties to make money. Typically, durable goods have less than a 50% value chain margin, and, therefore, have an almost impossible hurdle to achieving AOC. By contrast, the majority of CPG brands have high value chain margins, and therefore, high potential for achieving AOC. The final condition is that a brand needs a sufficient promotional lift to offset the cost factors like Ad Costs and profit margins. Brands or specific promotions with low sales lift will not generate enough incremental units to offset the promotional costs.


Those with 20+ years in the CPG industry may find it easy to dismiss this argument for Riskless Profits using retailer price promotion. After all, the formula is asking you to set aside all those years of conventional wisdom and faulty paradigms. You then have to work your way through some legitimate structural barriers, like sharing margin information with your retail partners, to get to the AOC. Finally, you may find after all of these efforts you may not have sufficient critical mass in sales or promotional lift or profit margins to achieve the promise of Riskless Profits. That's why TABS Group is here; we are the experts in consumer analytics, and we are the inventors of the Riskless Profit model. With a minimal investment in time and money we can tell you if your brand has the potential to make Riskless Profits through retailer price promotion.

To learn more please call Kurt Jetta at 203.225.9157 or email him at


1. Accurate Estimate of Baseline Sales

2. Predictable Level of Sales Lift

3. Relatively High Promotion Responsiveness

4. Ad Costs are less than 1.0-1.5% of Annual Sales

5. Retailer and Manufacturer have full visibility to value chain margin

6. Manufacturer subsidizes promotion discount proportional to their margin in the value chain

7. Manufacturer covers all Ad costs

8. Relatively high value chain margin (50% or more)

9. Product's everyday price is a low percentage of a consumer's household income

10. All Promotional payments are handles after the promotion is over

(1) Retailer Price Promotion is defined as a temporary price reduction at a retailer for a fixed amount of time. It is accompanied by some form of communication about the reduced price, usually through Feature Advertising or In-Store Signage.

(2) Jetta, Kurt (2008), "A Theory of Retailer Price Promotions Using Economic Foundations: It's All Incremental," Ph.D. Dissertation, Fordham University, Department of Economics.

(3) Nijs, Vincent R., Marnik G. Dekimpe, Jan-Benedic E.M. Steenkamp, and Dominique Hanssens (2001), "The category-demand effects of price promotions", Marketing Science, Vol. 20 No. 1, pp. 1-22.

(4) Pauwels, Koen, Dominique Hanssens, and S, Siddarth (2002), "The Long-Term Effects of Price Promotions on Category Incidence, Brand Choice, and Purchase Quantity," Journal of Marketing Research, Vol. 39, 421-39.

(5) DelVecchio, Devon, David H. Henard, and Traci H. Freling (2006), "The effect of sales promotion on post promotion brand preference: A meta-analysis," Journal of Retailing, Vol. 82 (3), 203-213.

(6) Srinivasan, Shuba, Koen Pauwels, Dominique Hanssens, and Marnkik G. Dekimpe (2004), "Do Promotions Benefit Manufacturers, Retailers, or Both?" Management Science, 50 (5), 617-29.

(7) Jetta, Kurt and Erick Rengifo (2009), "A Model to Improve the Estimate of Baseline Retail Sales, Working Paper."

(8) Wittink, Dick R., Michael Addona, William Hawkes, and John C. Porter (1988), "SCAN*PRO: The Estimation, Validation and Use of Promotional Effects Based on Scanner Data," working paper, ACNielsen.

(9) Abraham, Magid and Leonard Lodish (1993) "An Implemented System for Improving Promotion Productivity Using Store Scanner Data," Marketing Science, 12(3). 248-269

(10) For a full derivation of the AOC, see Jetta (2008) on Pgs 109-116.

             MYTH                                FACT

There is a sales dip after a     There is no academic consensus an the
high-low price promotion,        issue, and the vast majority of
                                 practitioners rarely see this dip.
                                 Jetta (2008) proved that this dip
                                 does not exist in CPG [except for
                                 out-of-stock situations].

Retailer Price Promotion (RPP)   The Theory of Retailer Price
causes brand switching           Promotion (Jetta -- 2008) proved that
                                 brand switching does not occur in

RPP causes Cross Channel         See above. Channel switching does not
Switching.                       occur.

RPP has negative long term       Numerous academic studies -- Nijs et
effects on brand sales and       al (2001) (5), Pauwels et al (2002)
image.                           (6), Del Vecchio et al (2006) (7),
                                 and Jetta (2008) -- disprove that

Manufacturers can't make money   If we can predict the worst lift
with RPP                         possible from a price promotion by
                                 simple math we can construct a
                                 condition -- in many situations --
                                 where both retailers and
                                 manufacturers can make money.
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Date:Apr 13, 2009
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