We need to "invert the pyramid" of a top-down model so that brands are listening and really want to learn what their customers want, instead of relying on analog trend-spotting capabilities.
Finding new models to sell products and services to rapidly changing audiences across several channels in a rapidly evolving marketplace is tough.
Recently I heard more than my fair share of such talk at various conferences I attended, such as the IRCE B2B conference in Manhattan and the latest Simulmedia Salon event with Mike Welch of AT&T AdWorks and Dave Morgan of Simulmedia. At both events I found the common theme of convergence, but through a different lens, so to speak.
At the IRCE conference, achieving convergence was more about enhancing the omni-channel marketing of products to what the target audience really wants (especially in the age of social media). But, at the other end of the spectrum, at the Simulmedia event convergence was defined much differently. There, the process consisted of marrying various addressable audiences with defined demographics acquired via cable set-top boxes, triangulated with Experian demographics and psychographics data, then marrying the data to mobile devices that are connected to Wi-Fi networks in the same household, so as to get a more targeted "addressable ad."
But selling advanced technologies to a fairly non-technical audience requires that sales associates first understand the technology they are selling, and then are comfortable explaining it to everyone - a rare talent, even today.
I also learned that convergence models that functioned well for a long time are ready to change. When I interviewed Robert D'Loren, the chief executive (CEO) of Xcel Brands (who owns Isaac Mizrahi, Judith Ripka, and the Liz Claiborne NY line), I found that fashion brands view convergence in terms of trend forecasting, and it turns out to a top-down, pyramidal approach.
Here's what I mean. D'Loren addressed my interest in color and trend forecasting for fashion by looking at convergence in fashion brands through the lens of a pyramid structure. His experience was first solidified for him several years earlier in the offices of Peter Max, a well-known POP artist he worked with in the past.
In fact, Peter Max, had a big Lucite pyramid sitting on, or near his desk, about 3 feet high, that encapsulated how information filters down to fashion and social media. On the very top of the pyramid was art, then comes music and film, then comes tech and architecture, and now there is a new layer called "social" (social media), and at the bottom of that pyramid was fashion. So, trendsetting for omni-channel fashion brands (which focuses now on the TV screen to sell) in this context is a top-down approach where brands set the trends for what they want their consumers to buy, rather than supply them with accessories they really want.
I think the real problem with the pyramidal top-down model is that it's very "analog" at its core, with designers working with creative teams at brands who feed them intelligence of what customers want, who are then working closely with analytics data and omni-channel analytics from large retail merchants. What we need is a means to "invert the pyramid," so that designers are listening and really want to learn what their customers really want, instead of relying entirely on the analog trend-spotting capabilities of a handful of a few top designers.
In both cases, convergence, and its analytics, was limited by the inability to better leverage and explain the technologies they have, more and more, come to rely on. Maybe it doesn't have to be this way, and maybe it won't be, sometime in the near future, as newer technologies converge and mature.
Image via Shutterstock.
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For over a decade Marshall Sponder has influenced the development of the digital analytics industry with his WebMetricsGuru writings that focus on social media metrics, analytics and media convergence. He also possesses considerable in-house corporate experience with roles at IBM, Monster.com, Porter Novelli, and WCG while continuing to work with start-ups. Marshall is a Board Member Emeritus at the Web Analytics Association (DAA) and teaches Web Intelligence at Rutgers University and Baruch Business College. Marshall is the author of "Social Media Analytics: Effective Tools for Building, Interpreting, and Using Metrics," published by McGraw-Hill in 2011.
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August 21, 2014