Most CPG companies struggle with sales and share growth due to the fact that consumer behavior is so hard to change. The problem is usually addressed using mass media brand advertising and paying large sums of money to retail partners in the form of trade promotion dollars. Agencies have profited while retailers have come to depend on trade investments for their bottom lines. The budgets for these two categories of sales and marketing expense are not only considerable; they have been growing often at a rate out of synch with sales.
Consider recent news from Procter & Gamble. After years of double digit advertising spend growth accompanied by low single digit increases in sales, the company appears to be banking on digital channels and their direct connectivity to consumers as critical to competing for consumer wallet share. This January 31 article about P&G’s recent financial results illustrates the point:
"Reality appears to have finally arrived at Procter & Gamble, the world’s largest marketer, whose $10 billion annual ad budget has hurt the company’s margins. They told Wall Street analysts that they would have to ‘moderate’ ad budgets because Facebook and Google can be ‘more efficient’ than the traditional media that usually eats the lion’s share of P&G’s ad budget.”
P&G is moving fast; just the other day the company hosted a digital marketing summit of sorts at its headquarters with heavy hitter speakers like Twitter. Other consumer goods makes such as Unilever, Kraft and General Mills appear to be making similar moves to hone in on digital.
While digital channels pave the way for direct consumer connections, in and of themselves they do nothing to create, nurture and grow consumer relationships. After all, CPG has used digital channels for years in its brand marketing, but usually in the form of short term promotions with all of the resulting data remaining with an agency. To do it right, data must be integrated, then analytics uniquely applied to understand the nature of the consumer goods makers’ consumers and shoppers.
This all came to mind when reading a recent New York Times article (thanks Keith) about how Target was able to predict a woman’s pregnancy before her family knew, and direct a targeted offer at her. Much of the Tweet-chat around this raised privacy issues and the "creepiness” factor. Even those in the data mining community chimed in, the majority agreeing it was a good idea rather than a bad one.
Dig past the controversy, however, and I think there are lessons CPG marketers should not just learn, but adopt on a wholesale level as they begin shifting more budget dollars to digital channels.
By analyzing a woman’s behavior based on many data points, a Target analyst was able to predict with confidence she was pregnant. Moreover, knowing that if you win a consumer’s business at key life stage events, a brand stands to benefit from repeat purchase behavior. In other words, grow sales and create loyalty in one fell swoop. At scale, across potentially millions of consumers.
Target wisely embedded its personalized offer amid less relevant offers -- to avoid the creepiness factor -- and it worked. That analyst is now on the speaking circuit, a level of analytical fame not unlike Paul DePodesta from the book Moneyball.
Anticipating or predicting key moments in a consumer’s life – sort of like identifying baseball talent objectively – will become essential for any business to consumer marketer seeking sales growth and a measurable, positive ROI on marketing investments.
For CPG companies with multiple brands in many different categories, digital channels and the binary bread crumbs they generate represent the best source of data needed to underpin these decisions. To do this most effectively requires an integrated view, across channels, brands, agencies, and campaigns -- a challenge few have been able to master without the proper technology foundation. This is a Teradata strength sought out by leading CPG companies.
Teradata now also possesses the Big Data analytical might necessary to understand the consumer path, regardless of data type or scale. See this recent article about how Aster Data recognizes that:
"…consumers interact across many touch-points, social, mobile, search, websites as well as offline channels. Most existing attribution solutions look at multiple touch-points within a single channel, like an ad network or web visitors. With a Big Data Analytics approach it is easier to blend more channels into the mix and find customer connections.”
Armed with data and insights, CPG marketers begin to understand the path to purchase, described in this recent article and accompanying diagram as rather complex. Tactics can be optimized around the path, data collected, and analyzed. It’s then possible to anticipate a consumer’s needs over time and pre-empt product purchase decisions with compelling offers that generate new sales and loyalty. In other words, Moneyball for CPG marketing.