The laptops are arranged in neat rows, seemingly endless black rectangles each glowing with bright blue screens. I point out to my daughter what the numbers on the little signs next to computer mean. I show her how to evaluate the features – Longer battery life, more RAM, bigger hard drive, larger screen, total weight. With each model comes a trade off, and after a few minutes I can tell she is getting confused. “Look, decide what features are most important to you, and then choose based on that,†I tell her. She nods, then proceeds to look at the back of each computer, and to feel the touch pad on each one.
My daughter finally stops at a mid-priced Sony and nods. Good brand, good choice, I think to myself. I glance at the features – seems like she picked one with a good balance of performance and portability. I tell her she’s a smart kid, figuring out what is best from amongst all those feature trade-offs. “It wasn’t that,†she tells me. “It’s a pretty silver color, not boring like all those others. And I liked the way the keypad felt.â€
Ever think about how we make decisions about what to buy? It’s a typical question that comes to the Emerging Media Lab – brands want to understand how consumers make choices. After all, if we can figure out what influences choice and what doesn’t, it makes it easier to market, right?
Easier said than done, though. Our industry is full of diagnostic tools which reveal what people do: what shows they watch; what magazines they read; what brands they prefer. But we are short on tools which describe why they make those choices. And the industry is weakest at understanding the purchase process itself.
Most clients are interested in understanding decision making, so they con build brand loyalty – how can they get consumers to prefer their brand over others. But a much more interesting question we get is about brand dis-loyalty. What causes those consumers who make thoughtful pre-shopping choices, decide on one brand or model and then end up picking a different model at the very tail end of the process?
Is it whim? Random consumer behavior? Or were other factors involved?
It turns out that the process of decision making has been deeply studied in the social sciences. Check out the research from Gavin Fitzsimon’s University of Pennsylvania study on non-conscious influence on consumer choice, for example. It look at the gaps between what consumers might say influenced their choice, relative to those influences which they may not recall, but can be proved to be influential.
But would that have described my daughter’s laptop preference? Can those same findings apply to decision making in a retail store, or at a restaurant, or at a pharmacy?
The Emerging Media Lab looks at purchase decision-making through several diagnostic lenses, all designed to reveal influence. Think about your own purchases recently, and ask yourself what was influential in your final choice. Not think about all the other media messaging you were exposed to , potentially how little influence most of it provided.
Was it online product reviews that moved you to buy one brand over another? Magazine articles? Traditional advertising messages? Perhaps advice from a friend or a relative?
It turns out that peer-to-peer advice tops the influence for many purchase categories. Recent research shows that over 80% of consumers say they don’t trust most advertising; but more than 70% of them say they trust online product reviews from random strangers on the Internet!
Obviously, to be great marketers, we need good tools to monitor decision making – to map out the process of going from undecided to confident. And we need to be able to reveal the way shoppers get information, and how that research impacted the choices they made at retail. The Lab’s NSM tool does precisely this, across any form of product decision making process, and across large groups of shoppers, to help our clients understand and act on consumer behavior in real time.
So in the case of my daughter, my advice, the impact of previous Internet research (she came in wanting a different brand) and even the role of both the associate in the store and the store’s displays could be mapped and ranked, from start to finish. Pretty cool, huh?
One final note: as we were discussing the computers in that very busy store, two other shoppers were eaves-dropping on our conversation. And I noticed them both picking up the same model she preferred as we walked toward the check out lanes. Do you think the retailer would have guessed an adolescent shopper could have so much influence on other consumers’ shopping decisions?
