I love movies about great mathematicians, real or fictional. The Imitation Game and Good Will Hunting are great ones, but A Beautiful Mind is my favorite. This movie profiles John Nash, who became a pioneer in game theory and won a Nobel Prize along the way. Because of this, I paid quite a bit of attention to game theory in grad school and constantly looked for applications. Over time I became disappointed, as the models I experimented with didn’t work as well in the real world as in the “games.” However, it seems that many developers and marketers of technology solutions don’t agree with my conclusion that rigid product and customer models (e.g., stereotypes) should be better left for the movies.
While I would love to say that this occurred to me during my work in behavioral analytics, like most revelations, it hit me in a much more overt way. It was brought home as I was talking to a woman about a problem she had been having doing online searches. After running into the problems repeatedly, she decided to stop asking for one-off help and take some classes at a local community college to answer her questions and build her capabilities. Okay, not that unique right? Community colleges are great at improving skillsets, preparing people for universities, etc., yes? Except the woman I was having the conversation with is my mother-in-law, Mom June, who turns 91 this month.
As I continue my work in utilizing behavior in the development of new approaches to problem-solving, the concept of categorizing individuals by single attributes (e.g., age, gender, etc.) becomes more and more ridiculous. However, I constantly see new technology products (I overtly do not use “solutions”) characterized in just this way, often targeting “Millennials” with new functionality, apps and/or services. But as I have said before, if you're developing new technology experiences, "M" better stand for Mobile and not Millennial, because to target any technology to a single attribute is a fool’s errand.
I'm not sure which came first: sales/marketing departments that adopted the Gen X and Gen Y monikers to push products, or developers that really believed that any technology was relevant to a specific age (or gender, or geography). Preferences and heuristics are much more important to understand, as these are attributes that technology can and should address. A case-in-point example appeared on my computer a couple of weeks ago in a recent piece published by Statistica on the demographics of US gamers. It showed that gamers in the US over 50 years old were evenly split between men and women at 13% of each population, or 26% of the total. That even split compared fairly closely with the 27% of gamers who are in the 18 to 35 year-old age group, underscoring the fact that gamers in America look a lot different than the stereotypical young male often cited and marketed to.
As many before me have proclaimed, technology is the great equalizer, so why are we still so fixated on the notion that we need to design technology for age (or other) groups? Why would we self-limit our market? I’d contend it’s because many companies don't actually understand their target market, developing products instead of solutions. This lack of understanding of a true user base was highlighted in a recent Harvard Business Review study showing how implementing social media and web usage strategies led to increased sales at a New York Harley Davidson dealership. The study, though, pointed to another interesting finding beyond the fact that social media can lead to increased sales. It also revealed that the Harley dealership had previously underestimated the size of its potential market and had failed to understand the characteristics and behaviors of its potential buyers. The value of utilizing a social media-powered approach also provided immediate feedback on what worked and what didn’t. Oh, and the dealer’s sales increased by 2,930% in the first week following the employment of its new tools.
I do wonder if some part of this fixation on single or limited attributes is due to the creation of products rather than solutions. This is where an understanding of data analysis techniques can assist, not only in confirming specific characteristics and behaviors in the population, but in understanding the whole population that a specific technology solution may apply to. In fact, I have to wonder whether most products marketed to a specific demographic group are compensating for something lacking in their design. Or perhaps many companies simply don’t understand their target client preferences.
So when you're thinking about a technology or service that you may be involved in developing, marketing or servicing, I encourage you to take inspiration from the likes of Alan Turing, Will Hunting, and John Nash. But after you do, roll-up your sleeves and make sure you understand the real-world needs of your target clients inside and out.
Dr. Jimmie Lenz is an experienced executive, lecturer and scholar in the field of banking and capital markets. Starting his career as an equity trader over 25 years ago, he has held a number of senior management roles within the finance community and has numerous pending patents. (All views in this article are his own).