Watch the introduction video
“Updating a legacy brand is a very risky proposition in the first place. I don’t care how much conventional research you do—and believe me, we do plenty when it comes to this—you are really betting the farm when you set out to reposition a brand that consumers have known and loved for years. It’s Ulcer Time in the best of circumstances. I’ll take every bit of help I can get to improve the odds.”
This President of a very large global packaged goods company’s Health and Beauty Aids division knew the time had come when they had to refresh and reinvigorate a core brand lineup of women’s beauty products. The Board had approved of the basic decision, but it was now up to this executive and the divisional team to execute on it successfully. Budget was not the issue; brand positioning and especially messaging was.
The challenge was steep. Consumers had increasingly described the brand as ‘tired’, “what I’d find in my mother’s bathroom”, “sort of 1980’s”-and worse. All the usual array of vendors were assigned to crack this nut in terms of packaging design, advertising, point-of-sale materials, and promotional campaigns. Shopper Experience was added to the mix as well. But the call came in to machineVantage at the outset of the process.
“I reached out to them because I’d noticed a campaign for one my favorite food products. It struck me as particularly on-target. They had obviously very successfully repositioned the brand, and they’d done it smartly, and with a budget probably one-quarter the size of ours. So I contacted that company to ask how they’d done it. They weren’t a competitor, so the ask was a safe one.”
“What they told me was that machineVantage had applied a whole set of disciplines to get at the right messaging for their product. I knew next to nothing about AI, and certainly less about ML, much less neuroscience! The messageVantage system factored in all the elements of a marketing campaign, all of the brand’s attributes, it assessed what consumers responded to most at the non-conscious level, and their algorithms crunched all that data and delivered the right messaging recommendation. Obviously, it worked. That was all I needed to know.”