The Splintered Moment of Truth

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by Yieldbot
Sunday, June 21 st, 2015 -- 3:11 pm

[ Republished from Adweek ]

How Do Brands and Agencies Determine When and Where They’ve Activated Their Shoppers?

A decade ago, Procter & Gamble coined the term “the first moment of truth” to describe the importance of in-store product placement in the customer decision-making process. Those first three to seven seconds it took to notice a product on a store shelf were enough for shoppers to make up their minds about a purchase.

The packaged goods giant could hardly have seen the shifts that would upend shopper behavior. By 2011, Google had come up with the “zero moment of truth” to explain how consumers were now searching for information online and making their brand decisions before entering a store. But today, even that search-driven behavior seems passé. With mobile, social and big-data targeting driving consumer action, it is harder and harder to attribute the specific marketing moments that impact product choice.

“There is no single moment of truth or zero moment,” says Jonathan Mendez, CEO of consumer-intent media engine Yieldbot. “We have so many touchpoints for media and we consume it in so many different ways. Media now fills our gaps– it’s a different dynamic. There are more moments happening. They can take place any place or any time.”

Still, digital channels have hardly eclipsed brick-and-mortar stores. As eMarketer points out, while overall annual U.S. retail spending is approaching $5 trillion, just 7.2 percent of that total comes via ecommerce. TimeTrade’s State of Retail 2015 report found that the physical retail store is highly relevant because “customers are looking to the in-store experience to help them validate their final purchasing decisions.”

This all creates a challenging dynamic for marketers. Consumers are turning to multiple screens for research and buying, whether they’re at home, on the go or in the store. Retailers and brands need to reach them at all these stages of the purchase process. But how do they measure the impact of each campaign if decisions happen at any moment? Not to mention, how can attribution be accurate when there is frequently a disconnect between digital and purchase data?

Attribution typically leverages a set of business rules to allocate the right amount of credit to each channel’s contribution to particular action. Determining what’s right is a highly discretionary process, and one that can be a source of contention within marketing departments. For instance, the mobile team may feel it should get the lion’s share of credit for sales that occur on tablets, while the search engine marketing team may argue that those sales would never had happened if not for its PLA campaigns. Since every channel (email, affiliate, catalog, search, etc.) tends to have a dedicated team associated with it, the incentive is strong to claim as much credit as possible.

“The first step in understanding the customer journey is to take the existing attribution models, which are built on an online shopping experience, and apply them to the offline shopping experience,” says Steve Schildwachter, CMO of digital place-based media company rVUe. “The second has to do with an offline attribution model. I don’t think the industry is there yet.”

That doesn’t mean brands aren’t trying. Earlier this year, Dr Pepper used Rocket Fuel’s Local Lift programmatic solution to run a mobile campaign that could drive measurable, incremental in-store traffic—its first foray into using this solution as an in-store purchase-intent driver. The campaign—to drive foot traffic to 1,000 grocery store locations—succeeded in driving 213,000 store visits at a cost of $0.21 per visit, according to Rocket Fuel, which partnered with Placed to measure mobile ad spend’s impact on real-world actions.

But mobile isn’t the only digital channel available. Turtle Wax wanted to reach motorists and drive them to Target stores, where its new product line, Turtle ICE, was featured in end-aisle displays. The brand partnered with rVue to put together a network of gas station screens for Turtle Wax, all within a five-mile radius around participating stores. In test markets, stores saw 25 percent more Turtle Wax ICE sales.

Intent data—which can help marketers understand and target consumers during the path to purchase—remains one of the key sources that can help clarify attribution. But, as Forrester Consulting recently noted, its use is not without its hurdles. In particular, the Forrester study, commissioned by Magnetic, found challenges in combining first- and third-party data and marketers believed attribution models were too complex to use.

Companies such as MaxPoint help shopper marketers leverage hyper-local display, mobile and video campaigns to drive in-store traffic and sales. “All stores are unique, and the consumers around those stores should be targeted in an individual and unique fashion,” says Matt Knust, VP of shopper marketing at MaxPoint. “The trick is to reach crowds of ideal shoppers while still retaining the precision of a hyper-local campaign.”

This all speaks to the value of actionable store-level information. Data providers such as Catalina have long been collecting shopper history via point-of-sale and other channels. Their knowledge into what individual households buy has become a highly valuable counterpoint to digital and mobile targeting and attribution.

Marketers and agencies continue to grapple with scaling mobile audiences and understanding offline sales impact. “Scaling addressable audiences across mobile screens is a key challenge, but marketers have options,” notes Debbie Wogan, VP, digital advertising at Catalina. “Our mobile technology lets Catalina message consumers on their mobile devices at scale when they’re in their homes using a probabilistic approach. We collect ad calls and ad call locations to match households to devices. This in turn lets us message consumers at home with highly relevant offers from brands.”

Using Catalina data, ad tech company 4Info has created benchmarks to provide mobile advertisers the ability to compare in-store sales lift and return-on-ad-spend to comparable campaigns. The goal: help national brand advertisers solve the challenge of mobile attribution.

Solutions like these are not complete, holistic marketing attribution. That is—in all likelihood—still many years away. But shopper marketers are getting a clearer picture of when these decision moments are occurring.

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