As consumer interactions with technology continue to evolve and deepen, the old, campaign-driven approach to marketing is becoming increasingly obsolete, according to a new report from Forrester Research. "Consumers don't trust your ads. There's no advantage in campaigns when your competitors are just as skilled at the campaign game as you are. While you know how to tune campaigns to help you hit your numbers, they're no longer sufficient," writes Carlton A. Doty, report author and Forrester analyst. According to Doty, consumers are constantly interacting with brands outside of deliberate campaigns—to stay relevant, brands must harness the data gathered through these interactions to build a context marketing engine, a new approach to marketing that will spell "unprecedented levels of customer engagement, increased revenue, and better product experiences," he says.
Campaigns are becoming less effective because consumers prefer real-time marketing and engagement, Doty suggests. On Black Friday, for example, retailers amped up spending on push notifications by 37 percent and online sales grew by 19 percent, with mobile accounting for 40 percent of the total, the report states. As for traditional campaign ads, "no more than thirty-two percent of U.S. online adults trust ads in any channel," Doty explains. Consumers also prefer personalized experiences, derived from interaction data that creates context and analyzed using proprietary algorithms, sensors, and other technologies that reveal insight based on the context to drive it further.
To deliver the kinds of personalized interactions that will eventually replace failing campaigns, marketers need to build a context marketing engine, which the report defines as "a brand-specific platform that exploits customer context to deliver utility and guide the customer into the next best interaction." The context marketing engine is a powerful approach, according to Doty, because it bridges the gap between marketing and customer experience, delivers utility to customers, and provides a constant incentive to engage. The engine also enables "customer-managed" relationships, Doty writes, alluding to a deliberately inverted approach to customer relationship management.
"Contextual marketing flips everything you think you know about customer relationship management.... In CRM, you take customers' information, accept their phone calls, and try to unload them as quickly as possible. In contextual marketing, customers manage the relationship they have with you, and you respond by sharing rather than taking, anticipating customers' needs rather than reacting, and delivering value in the moment rather than just at the point of purchase," he says.
To build an effective context marketing engine, Doty says marketers must first define a marketing strategy capable of unleashing useful interactions. "Start by determining your brand's North Star—a guiding principle that shapes the brand's external identity in people's lives. Then build a marketing strategy that delivers utility and fuels an interaction cycle built around that North Star," Doty recommends.
Marketers must then reorganize their marketing processes to spark the interaction cycle, and adapt their enterprise marketing technology portfolios. "Contextual marketing doesn't come with a stock engine that you can buy off the shelf from a vendor. Assembly is definitely required. You already have several of the essential components in your current enterprise marketing technology portfolio. Before you buy another marketing technology platform, take stock of your current technology assets and how they fit in," he says.
The last piece of the context marketing puzzle is analytics. To accelerate innovation, Doty urges marketers to utilize the analytics tools available, but not in the way that they're used to. While most marketers use analytics after a campaign to analyze the engagement and use the insight to improve upcoming outreach, in a contextual marketing engine, marketers have to apply analytics "on the fly," according to Doty. "Experiment with big data technologies that blend a new cocktail of predictive analytics tools and methodologies to optimize customer decisions and drive business results," he suggests.