When It Comes to Contextual Marketing, Think Like Chip Davis

Welcome to a new monthly column from Jeff Zabin, co-author of "Precision Marketing" (Wiley, 2004) and a director in the Precision Marketing Group at Fair Isaac, a provider of marketing decision management solutions. He can be reached at jeffzabin@fairisaac.com.

Growing up in Omaha, I knew about Chip Davis. His recording studio was located a few miles north of the city, and I saw him perform in concert on numerous occasions in the early 1980s. I liked his music.

But I never would have imagined that he and his band—Mannheim Steamroller—would go on to play sold-out shows across the country while racking up sales of 35 million albums, as many as megastars such as James Taylor, REM, and Pearl Jam.

Clearly, Mannheim Steamroller offers something that people desire: a creative reinvention of traditional melodies steeped in a synthesizer-laden orchestral sound that packs a high-fidelity wallop. The music sells itself. Yet the phenomenal success of Mannheim Steamroller can also be attributed in large part to Davis’s superior marketing acumen.

That acumen was apparent early on. In fact, Mannheim Steamroller got its start by promoting its albums not through traditional music retail outlets but in stereo equipment showrooms, where the band’s state-of-the-art sound became an immediate hit with audiophiles. It was a stroke of genius on Davis’s part, and it succeeded in putting him on the map.

Three decades later, Davis continues to demonstrate his intuitive understanding of how consumers think and to exploit that understanding to sell more albums (along with an assortment of other merchandise in the Mannheim catalog). A good example relates to “American Spirit,” a collection of patriotic songs.

The week before Memorial Day, “American Spirit” went on sale at an Omaha intersection where both a SuperTarget and a Baker’s supermarket are located. The Target store, where the CDs were discounted to $12.98, sold a paltry dozen copies. But the supermarket, where the CDs were priced three dollars higher, sold 50 copies more. It was a simple experiment, the result of which is easily explained: Upon Davis’s insistence, the supermarket put the CDs in the same aisle as the hot-dog buns, a major thoroughfare for shoppers gearing up for their holiday cookouts.

As this example suggests, Davis is a master of contextual marketing. He understands that the way consumers think about buying is oftentimes very different from the way that retailers think about selling. Activities that are logically related in people’s minds—in this case, eating hot dogs while playing patriotic songs—may, in fact, be spread across very diverse parts of a physical store (Target’s grocery and music departments, for instance, are located at opposite ends). For his part, Davis has never wanted his albums to be relegated to a store’s music department. Instead, he says, “we try to put our music in the path of what people do every day."

It’s a marketing slogan that every company should put into practice. If only it were that easy! After all, how can large retailers, saddled with an inventory of products that may number in the tens of thousands, hope to identify the most likely purchase paths of their different customers? Well, for starters, they can open up their reams of transaction data. Information about past purchase behaviors can speak volumes about the clusters of related activities that customers engage in to satisfy a distinct set of needs.

Some activity clusters are obvious, and the frequent item combinations that people make will be no surprise at all. People who want a clean shave are likely to buy both razor blades and shaving cream, for example, while people who want to preserve their memories for all posterity are likely to buy not only a digital camera but also a memory stick, a photo printer, ink cartridges, photo paper, and a predictable slew of other accessories. The likely purchase path over time can be mapped out without too much effort.

In contrast, many frequent item combinations are nonobvious. As such, the relationships that exist between the items may be difficult to discern without the use of transaction data and analytics technology. The newest breed of this technology can allow product associations to be analyzed not just in a market-basket context but also in a purchase-sequence context. This context richness makes it possible to identify different kinds of purchase behaviors associated with different types of products and different types of customer segments.

My colleagues recently deployed this new technology for a major consumer electronics retailer. In many instances, the customer insights were stunning. Where music is concerned, we discovered that people who buy blenders have a higher-than-normal propensity to also buy salsa music CDs. What’s the connection? Margaritas, of course! The retailer responded by putting a collection of salsa CDs in the same aisle as the home appliances. It’s an insight that might prompt Chip Davis to smile—and maybe even launch into a Mannheim rendition of “Ran Kan Kan.”