When the concept of 1:1 marketing was first introduced in the early 90s, it was seen as a smart alternative to the “spray and pray” method of mass advertising. Clearly we didn’t know any better.
As techniques and technology have become more sophisticated, marketers have since come to realize old school segment-based marketing is about as personalized as a TV spot. What was thought to be 1:1 in 1993 is just another one-to-many strategy, albeit a less broad one (thousands in a segment vs. millions sitting on their couches).
Today — for the first time ever — we’re truly able to deliver hyper individualized 1:1 marketing. Decades ago you might have known a person was interested in a new car, but thanks to big data you can now tell that what the person actually wants is a VW Passat SEL in Reef Blue with the headlamp upgrade. You can act on that, too.
But what happens when you lack that level of data granularity? Are you forced to serve up content like those days when grunge was at the top of the charts? Not if you follow the lead of two brands who chose to overcome an absence of data by giving consumers a compelling reason to provide info about their interests. While neither example showcases what’s possible with full-on personalization capabilities, these are great case studies of starting with nothing and taking that first step towards a more automated approach based on user history.
McCormick & Company, FlavorPrint
With FlavorPrint, McCormick developed a way to deliver personalized recipes to site visitors without any insights into their historical behavior. The seasonings company simply asked visitors to answer questions about flavor, rate various cooking techniques, and give a thumbs-up or thumbs-down on different cuisines. McCormick then used this on-the-fly profile to push appropriate content on subsequent visits.
L’Oréal Paris, My Beauty Picks
L’Oréal’s My Beauty Picks was meant to transport personalized recommendations from the makeup counter to a computer. Posing the same questions a sales rep may ask, L’Oréal sought to better understand the needs of site visitors — including any beauty issues they were looking to address (wrinkles, frizziness, etc.). As a result, the cosmetics brand was able to repeatedly make individualized product recommendations plus serve up complementary articles and videos.
Using what they learned, McCormick and L’Oréal were able to deliver online experiences that were extremely relevant — all without a vast repository of customer data. When you consider that 56% of consumers said they’d buy a product from a brand that personalizes content, it’s an incredibly smart play. And an especially savvy way to build a database that enables future personalization efforts.
With the “Amazonification” of the Internet, consumers have been trained by Netflix and Google to expect a personally relevant experience wherever they go online. These attempts are solid steps toward that end goal of individual relevance with content, but it’s important to realize much more can be done. Case in point: L’Oréal has taken the data acquired from these and other exercises to launch true personalization campaigns that include emails and, yes, even advertising.
Sometimes though you have to build the airplane while you’re flying it, and that’s exactly what McCormick and L’Oréal did above.
Where’s your brand on the path to personalized content marketing? Which programs and investments have moved you forward the fastest? Let us know in the comments!
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