Syndicated Data Sources: Part 2

Part two of this lecture is limited to a discussion of one supplier of single-source data: IRI and its BehaviorScan product.

The technology for creating single-source data is relatively straightforward: universal product codes (those bar codes on products), checkout scanning equipment (for recording when a shopper has purchased one of those products), computers (for processing massive amounts of purchase data from many shoppers), and a marketing information system (to take that data and convert it into a format that managers can use to make decisions).

Although strictly behavioral data, single-source data can be used for many purposes, such as new product test marketing. The turnaround time for data from single-source suppliers is faster than from traditional test markets and other methods. As a result, single-source data can help to refine marketing mix strategies/tactics or to decide about terminating a newly introduced product in a more timely way. Single-source data can be used to reposition existing products. Trends in select markets with modified marketing mixes could be compared to national trends, which would help to decide about modifying or repositioning an existing product. Single-source data is useful for evaluating the efficacy of ad copy execution, ad spending, and the ad promotion mix.

What does BehaviorScan require? It requires two sets of participants in an electronic panel system: small-city grocers and consumers. The consumers must be geographically isolated, so that their shopping is done locally and they’re not influenced by out-of-market media. Smaller cities also have few grocers, so all of them can be convinced to participate. (In essence, what’s being monitored is a mostly closed shopping system in which most purchases can be tracked.) The incentives for these small-city grocers to participate are free scanning equipment and free inventory data. The expense of scanning equipment and the quality of data available for grocers to make more informed decisions about what they stock make these powerful incentives. As for consumers and why they’d be willing to compromise the privacy of their purchases, they receive gifts for their participation. Annually, each consumer receives a small token gift—something in the $10 to $20 range—as a ‘thank you’ for participating. In addition, for each shopping trip to a grocery store—up to three trips a week—each consumer is entered into a raffle. At the end of the year, names are drawn for that raffle and major prizes are awarded. Thus, there are strong incentives for both grocers and consumers to continue to participate in the BehaviorScan panel.

Again, the reason for smaller markets comparable to Las Cruces—relatively isolated from larger metropolitan areas—is twofold. First, there’s a need to control for out-shopping, which is people from a smaller city like Las Cruces shopping at a larger nearby metropolitan area like El Paso. Before Sam’s Club moved to Las Cruces, I shopped the Sam’s Club outlet in western El Paso. Typically, my wife and I made bi-weekly runs to El Paso to buy hundreds of dollars of groceries. The purchases of people shopping this way will not be detected by the BehaviorScan system, and that leakage of purchase information is a problem. Hence, smaller geographically isolated cities are preferred to minimize out-shopping. Second, with a small number of grocers in a

Page | 1 community, IRI can secure cooperation from all of them, and as a result, minimize purchases unrecorded by BehaviorScan.

Here’s the BehaviorScan system in a bit more detail. Each consumer participant receives a bar- coded ID card that uniquely identifies him or her. Scanning that card at the checkout counter allows that person to be linked to all purchased items. The products are labeled with universal product codes, which also are scanned at checkout. By recording people’s purchases during each grocery store visit, it’s possible to track household purchases over time.

BehaviorScan also permits controlled advertising exposures. Smaller cities often are dominated by a single cable operator. This operator must cooperate in the following way: The operator’s fiber optic network must maintain a parallel channel for each commercial channel it carries; that way, it’s possible, using uniquely addressable cable boxes (analogous to telephones; when a caller dials a seven-digit number, only one phone rings), to electronically switch between the main and parallel channel without viewer cognizance. For example, suppose Proctor and Gamble purchased 30 seconds on NBC on July 1st—from 7:31:00pm to 7:31:30pm—for a Crest toothpaste commercial. At 7:31:00, the cable operator would signal the cable box to switch from the main NBC channel to the parallel NBC channel, which would be carrying a new, yet-to-be- tested commercial for Crest. At 7:31:30, a signal to the cable box would switch it back to the main channel. Then the subsequent purchases of households that viewed and didn’t view the commercial would be tracked. (Note: Proctor and Gamble had purchased the air time, so it could run any FCC-acceptable commercial in that time.) This technology makes it possible to test commercials on households targeted by socio-demographics and/or previous purchase behaviors through a process that’s transparent to viewers. In addition, smaller cities usually have one local newspaper to which many households subscribe. As a result, it’s possible to target specific subscriber households—again, selected for socio-demographics and/or previous purchase behaviors—for specific coupons of a specific denomination. Thus, BehaviorScan-type systems make it possible to test the efficacy of coupons to create sales.

Although the BehaviorScan technology allows for controlled experiments of television and newspaper advertising exposures, it’s beyond this technology to control for radio or magazine exposures. Still, companies can run meaningful advertising experiments that expose one group of households known to purchase a certain type of product to one ad, and a different set of households also known to purchase that product to a different ad, and then tracking the purchases of each group.

So, how could marketing managers use BehaviorScan-type data?

 It could substitute for pantry audit data. Having researchers visit consumers’ households routinely to see what’s stocked on pantry shelves, or asking consumers track their purchases with diaries or handheld scanners, is likely to result in much missing data (i.e., unrecorded purchases). BehaviorScan is an electronic panel with a far higher probability of correctly recording purchase quantities.

 It could substitute for traditional panel data, in which households use handwritten diaries to record all their purchases. I’ve already shown the types of forms panelists need to complete. The complexity in these forms indicates why an electronic panel would be superior. BehaviorScan data avoids such problems as forms, paperwork, and the eventual lack of panelist patience.

Page | 2  It allows experimental manipulation of the marketing mix and tracking of consumers’ responses over time to such manipulation. Such experiments are far more reliable than surveys for modifying marketing mixes.

BehaviorScan has many advantages and disadvantages. I’ll discuss the advantages first.

 BehaviorScan allows for complete store data. Personally recorded reports of what consumers purchased—even those created by hand-held scanners—only reveal what they bought; there’s no indication of available alternatives. Although such data can indicate, for example, that a household bought a 24 oz. jar of Skippy peanut butter during the grocery store visit, it cannot indicate if Jif is normally available, was on sale, or was stocked out. Knowing about the available alternatives, as well as what was chosen, is valuable to marketing managers. Hence, relative to traditional diary panels, single- source systems provide more comprehensive purchase data.

 BehaviorScan-type systems allow for accurate tracking of coupon use. Consider the billions of dollars spent annually to produce coupons, place them in newspapers and magazines, reimburse stores $.07 per coupon for redemption, and refund the coupon denomination to consumers. To optimize that expense, it would help companies to track coupon use. For example, coupon tracking data could help companies optimize coupon denomination; every unnecessary penny that companies rebate to induce a sale is a penny of foregone profitability. It’s even useful to track coupon mis-redemptions. Unfortunately, checkout personnel may be careless about the variety of the product being purchased versus the variety of the product on the coupon. For example, you might have a coupon for strawberry-flavored yogurt, buy raspberry-flavored yogurt instead, yet still receive money for your coupon because the checkout person didn’t read the coupon carefully. Understanding mis-redemption rates also helps companies achieve a truer sense of couponing costs.

 Because BehaviorScan-type systems create an historical record of every participating household’s purchases, it’s possible to run experiments with groups that are matched on historical product usage. In a traditional test market, for example, Purina might run test ads for a new dog food and then over several months discover how sales increased, decreased, or remained unchanged. For BehaviorScan-type systems, consumers’ television boxes are uniquely addressable, their home-delivered newspapers customizable, and their daily purchases are recorded accurately and in complete detail (e.g., store bought, price paid). If historical purchase records reveal which households buy dog food, then it’s possible to identify 2,000 households split them into two groups of 1,000, test some modification of the marketing mix (like advertising or price), and then track changes in those tested consumers’ purchase behaviors over time. Hence, single- source systems provide a rigorous method for testing marketing mix changes.

 BehaviorScan-type systems provide faster feedback about new promotions. Typical test markets require multiple months before companies can draw even semi-definitive conclusions. With single-source systems, that time is reduced to weeks. For new and likely expensive promotions, the ability to make quick but minor tweaks is critical to boosting their efficacy, so faster feedback on the order of weeks rather than months is valuable to product managers.

Page | 3  BehaviorScan-type systems are more accurate than traditional store audits. Store audits require many people with electronic scanning equipment to check quantities on shelves. The problem: things disappear from shelves for reasons other than purchase; for example, shrinkage or five finger discounts (i.e., stealing) and spoilage. A store audit only accounts for items that have moved off store shelves regardless of reason. Because they only record purchases, BehaviorScan-type systems provide far more accurate sales information to companies.

 Consumer-recorded data is more accurate with BehaviorScan-type systems than with traditional purchase diaries. Not every shopper is willing to admit to the purchase of lesser desirable products from a nutritional standpoint. For example, some shoppers may resist reporting that they purchased Twinkie’s, Ding Dongs, or Fruit Loops, and instead will tell you, every time, they purchased fresh salmon or asparagus or brussel sprouts. So there’s a reduced reporting bias, as well as reduced non-reporting bias, with BehaviorScan-type systems.

Although BehaviorScan-type systems can help manufacturers of frequently purchased consumer non-durables—such as foods, detergents, and personal hygiene products—there are some disadvantages associated with them.

 BehaviorScan-type systems only exist in smaller markets. Bias is introduced to the degree to which people who live in bigger cities differ systematically from people who live in smaller cities.

 Setting up BehaviorScan-type systems is an expensive proposition. IRI can monitor only a handful of cities; as a result of the small number of markets, it’s difficult to determine inter-regional differences. It may be that northeastern U.S. markets may respond favorable, but markets in the traditional southern or far western U.S. may respond negatively. Because BehaviorScan runs in so few cities, it’s difficult to identify true geographical differences versus specific-market idiosyncrasies.

 Not all retailing outlets are represented. Consider Las Cruces; it’s possible to buy groceries in Wal-Mart, Target, Kmart, and Walgreens. It’s possible to buy some grocery- type items—such as floor cleaners, light bulbs, and pet food—at many other outlets. Unfortunately, BehaviorScan included no drug or mass merchandise stores in its mix of retailing outlets; hence, purchases in those outlets are missed. That is a major problem for sales data accuracy.

 Because purchases are recorded in a small sample of smaller cities, tracking low- purchase-incidence products may be difficult. For example, pickled pig’s feet isn’t an especially popular product. Given the number of BehaviorScan panelist, tracking the sales of such products may prove difficult.

 Like Nielsen boxes, BehaviorScan’s system of the uniquely addressable box is attached to the primary televisions in a household. As a result, homes with half a dozen televisions and someone watching television #5 may not be exposed to the test ad. In addition, there’s no way to know if anyone is viewing the ad or if the television is running in an empty room. BehaviorScan-type systems only track TV usage, not ad exposure.

Page | 4  BehaviorScan-type systems only provide behavioral data; although useful, non- behavioral attitudinal data also is useful to marketers. Single-source data can reveal that an ad campaign is ineffective at stimulating sales, but it can’t reveal why the campaign is ineffective. To determine how to fix a faulty ad campaign, it’s necessary to ask people about their opinions of those ads. Hence, it’s necessary to supplement single-source data with non-behavioral attitudinal data.

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