Case Study: Analytics Sparking the Idea and Driving Growth

The mobile application company WinShield, although now defunct, provides an interesting case study into how analytics data can not only build the basis for a product, but can also guide the evolution of a business model throughout a company’s maturation.

Using Data to Identify a Problem

According to the law firm Edgar Snyder & Associates, including data compiled by AAA, in 2012 about 421,000 people were injured in vehicular accidents that involved drivers being distracted by cellphones, and 3,328 of those people were killed.

Buzz around this growing epidemic gained and sustained worldwide attention through organizations such as End DD, MADD, the National Highway Traffic Safety Administration, and even the Center for Disease for Control. When there is publicly accessible data and public furor over an issue, that issue becomes ripe for a disruptive solution.

Analyzing a Problem to Create a Socially-Conscious Solution

The creators of WinShield saw this rising trend in mobile phone-related traffic casualties and devised a way to combat it. WinShield was a mobile application that would initiate when a vehicle started driving, and the app would block all calls, texts, alerts, and push notifications to prevent drivers from becoming distracted.

But the largest demographic for these types of accidents, as cited by NHTSA data, was people from the ages of 16 to their late twenties – a demographic scientifically known for having under-developed risk-reward processes in their brains. Knowing their actions were dangerous was not incentive enough to use the WinShield app. So the creators used this information to add another twist to their app: incentivizing teen drivers with rewards.

Catering to Your Target Demographic

WinShield was then developed to keep track of total miles driven without distractions, and converted these miles into points. Points could then be redeemed for prizes directly through the WinShield application.

Data on popular products and brands for this demographic were used to target a selection of prizes that would entice young drivers into using the application. And because of the available analytics confirming the buzz around this social issue, many brands were eager to donate products in exchange for having their name associated with this social-minded endeavor.

Analytics-Based Growth and Monetization

WinShield now faced the problem most fledgling tech start-ups face: monetizing their otherwise free product. So they looked for ways to utilize the data they were able to gather to monetize WinShield without compromising their core mission of freely accessible safety.

Auto insurance companies base their models for determining premiums on generalized aggregated data with veritably no individualized adjustments (beyond “have you been in an accident, yes/no”). Variables such as gender, age, zip code, and even the color and make of the car, are still the norms for determining premiums for drivers, regardless of individuals’ specific circumstances.

WinShield approached several insurance companies to gauge their interest in a partnership that would yield them data on individual driver’s habits. The insurance companies were interested, but the data WinShield gathered wasn’t exact or expansive enough to alter their current models for determining premiums.

So WinShield investigated producing telematics devices – data gathering modems that are places into a car, and can track highly-specific data points such as average rate of acceleration on which types of roads, number of hard stops, hard, avoidant swerves, and even frequent unnecessary idling as a marker for environmental awareness. When combined with the WinShield app’s data points of average length of trips, times of day, and of course the novel proven lack of distraction while driving, a complete picture of an individual driver’s habits could now be formed.

In addition, an investor and advisor for WinShield identified a further opportunity for this new model – commercial trucking fleets. Rather than a “How’s my driving?” bumper sticker with a 1-800 number, trucking companies could monitor how safe drivers actually were, which could mean immense savings in insurance and costly accident prevention. And if trucking fleets had hard data on the driving records of their drivers, clients would feel more assured and potentially pay higher costs to hire their drivers over other companies.

Monetizing your data, when done strategically, can be an incredibly valuable component of your business model. You can visit Mojisola Odubela’s blog post for a deeper exploration into how to successfully monetize your data.

In Conclusion: Always Look to the Data

This case study illustrates how data can be used to identify a problem that needs solving, how likely markets are to want this solution and the best ways to market it to them, and also how to grow, monetize, and ultimately sell your business. This is why we collect all possible data on problems in the world today – with the proliferation of open information, someone is bound to use this data to propose win-win-win solutions for society at large.