Opportunity knocks with big data products

One of the more interesting aspects in the evolution of big data is that it has largely remained in the background for the average consumer. While recent scandals involving Big Brother-esque government spying put big data on the front page, few consumers can articulate how big data has impacted them personally.

For most companies, consumer-related big data has focused on acquisition and marketing. Companies are extensively mining consumer behavior and attempting to correlate it in a manner that allows them to predict behaviors and, ultimately, sales. Interestingly, big data has come of age concurrently with sensor-enabled consumer products, where everything from thermostats to workout gear has embedded sensors and WiFi radios onboard that can gather all manner of data. The companies behind these products are often leveraging these data, but still missing a key opportunity.

Beyond marketing

My wife is a fairly technology-savvy consumer and tends to be on the cutting edge of new mobile apps, especially when it comes to applications that are family- or child-related. When our children were infants, she would diligently track feedings, sleep schedules, and even diaper changes in a baby-related app. When I gave her some gentle ribbing about her data obsession, she noted that she had been able to correlate sleeping longevity (a major "KPI" for any parent) with feeding times. As the babies started to eat solid foods, she could similarly see which would affect sleep or diaper changes.

She complained that she identified these correlations through deduction, rather than the app highlighting these fairly obvious trends. Similarly, many of the consumer devices that gather all manner of data report it to the cloud for marketing analysis, but do little more than rote trend analysis for the consumer who actually purchased the product. Clearly everything from my favorite free diet application to my running watch are reporting data to backend analytics that are likely driving targeted marketing, but none of them perform even basic data analysis that might proactively warn me that I tend to have a few too many cocktails on Fridays, or that my running pace is significantly better in the evening versus the morning.

What's rather surprising is that the necessary infrastructure to offer consumers big data-driven analysis already exists. Most of these data gathering applications already report their findings to a cloud-based server, and in all likelihood the owner of the service is already slicing and dicing data for marketing purposes.

Productizing big data

The products you can derive from your big data resources should be fairly obvious. Put yourself in the consumer's shoes and ask "What would I like to know from these data?" In most cases, the components necessary to intelligently address consumers' concerns are already in place. For example, companies like Google are slowly moving in this direction. For years smart phones have held calendars, clocks, and mapping applications, and Google finally combined the data from each application to tell users what time they should leave their current location in order to arrive at a scheduled appointment. Similarly, applications to locate friends and family were a popular trend, yet only addressed one of the consumer's obvious concerns: where is my friend and when will they get to me, a major missed opportunity.

The opportunities to answer consumers' questions are everywhere. My Nest thermostat is a beautiful device and can be controlled from anywhere in the world, but the company still doesn't answer fairly obvious questions like: "If I adjusted the temperature, how much money would I save on my electric bill in the summer and winter?" or "How about we adjust the temperature to save energy when it's cloudy outside?" Once again, the connected device is there gathering data, historical and forecasted weather data are readily available, and trend and energy usage analysis can be easily culled from the thousands of Nest devices in the field. I'd be willing to pay for the fruits of big data analytics and, when combined and presented in novel ways, big data can become a product in itself rather than just a forecast engine.

When you consider the vast amount of resources many companies have invested in their big data capabilities, it's a wonder more companies are not attempting to provide consumers with analytics-driven products. Instead of using big data only to sell, why not sell the output of your big data itself?