Every movement begins with a moment.
“Let me ask you something. What do women want?”
For decades, even centuries, advertisers and marketers have relied on demographics to fundamentally drive their campaigns. Data-driven insights weren’t as easily available to our predecessors, and so they depended on demographic-based assumptions. And while these assumptions did have the benefit of being bolstered by research and data, more often than not, they were nothing more than statistically validated stereotypes about a group of people.
This is how advertising and marketing worked for a long time — and even continues today. Many social media channels offer in-depth data on users — Facebook even recently provided new viewer demographics data for all videos. This reporting may be a more focused and farther-reaching form of the research conducted in the past, but it still falls short of the personalized approach that we can provide with new systems. Because we are now working in an age where data is king.
Today, marketers have more information about individual consumers than ever before — information that people willingly divulge. We are living in an era of personalization and personification — an era of connectivity and instantaneousness. Consumers want (and expect) to be fed relevant advertising based off of the information they choose to make public and accessible to brands. As far as they’re concerned, you already know them, so it’s your job to show them what they want next. Think of Amazon, Netflix and Hulu, which recommend products, shows and movies based on a consumer’s purchase or viewing history and behavior. These recommendation engines are preferred — and now often expected — when it comes to media consumption and purchasing online. Their biggest advantage: they increase revenue. In one e-commerce study conducted by MarketingSherpa, 11.5% of all revenue was attributed to personalized product recommendations.
The principles of these e-commerce recommendation engines can — and have been — integrated into the marketing process to change and improve consumer experiences. Solutions like Moxie’s DecisionIQ, for example, enable us to move well beyond assumptions to truly understand what each audience member wants, believes and/or needs. We can look at the massive amount of data that consumers produce and identify what’s relevant, what really matters and what’s simply noise.
DecisionIQ does not generate its decisions based on demographic data points like gender, race or age,” explains Tracy YoungLincoln, Moxie’s EVP of Analytics. “Instead, it treats consumers like the individuals that they are, catering to each based on his/her personal behavior. We’ve seen that behavior far transcends demographic traits like gender, race and age when it comes to anticipating a consumer’s next step.”
This isn’t the end of marketing as we know it, but it is a crucial moment in our industry’s history. Because we can do something we haven’t been able to do before: find a brand’s most relevant audience. Instead of creating content and releasing it into the media ecosystem, we can be hyper-focused and efficient in sending the right message to the right person at the right time. We now have the ability to receive continuous, real-time feedback from our consumers and can be as flexible and dynamic as their needs and preferences. And best of all, everyone across every agency department can do better, more pointed and more meaningful work.
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