With marketers, retailers and web pundits delving into the topic of Big Data, studying their Google Analytics report like it’s the Zapruder film and studying up on their compiler language, how does all that information translate into creating products that people love and that fly off the shelves?
I contend that there are two elements of this, one is Big Data, which shows you a tranactionally-based road map of what’s popular, what people like, what they prefer given an unlimited number of choices, and can show you how people’s purchase decision gets made; and Good Data, which is gained through other means than digital, but has a digital internet component, and can show you WHY people prefer one thing over another, WHY they gravitate to certain elements or items, WHAT MAKES things popular, WHAT their needs might be in their daily lives BEFORE its been created and marketed.
The two are different and both are extremely useful in putting together a cogent innovation program that can generate the new things we all crave and to marketing them effectively and making them popular and successful. One is only “better” than the other under specific constraints and circumstances. I tend to use both depending upon the project, Good data being the best and most useful to drive new product or service innovation, and Big Data the most useful for gathering and testing theorems and intelligence on applications and market positioning for the product once it’s been developed.
True innovation is a brand new, never been seen before element, and therefore Big Data will not be able to provide you with any comparative data because there’s nothing to compare it to. I doubt the folks at Apple tried to sift through transactional data to see if anyone wanted an MP3 player the size of a lighter with a thumb wheel selector, but if you had asked individuals (primary insight research, Good Data), how they listened to music, where they listened to music most often, and how they WANTED to be able to listen to music (while running, exercising, swimming, in the car,), and why they couldn’t do those things with the current gear, those answers might have lead you to create the iPod.
The wealth of Big Data spawned by tracked internet traffic, and the dearth of Good Data based on ineffective feedback loops, automated CS phone trees and do-it-yourself web-based customer service devices have isolated the bigger more established brands, those with a solid customer base, and a culture often lacking in specific innovation paths beyond incremental improvements f the current product line. That isolation will likely have a dampening effect on those firm’s ability to innovate over the next several years and beyond, if internal structural changes to the organization are not made and a comprehensive, skin-thin customer facing transparency established so that consumer input can be distilled into actionable intelligence quickly and efficiently.
Those firms without an effective “Data Loop” to constantly feed the development teams a source of Good Data will slowly stagnate and become copy-cat innovators, while those closest to their own customers will clear a path to new product development that is facile, smooth and relevant on an ongoing basis, fostering innovation in search of customer happiness. Expensive? Not really, when considered against the cost of lost customer base, eroding market share, lack of attention to pirated technology due to inattention to customer need, defense of intellectual property infringement and a host of other ills facing a stagnant brand.
If you think like I do, and want to help your company become a place that fosters innovation, comment below, or contact me via e-mail at firstname.lastname@example.org or on LinkedIn.