I’m a big fan of adaptation. That is to say that when I learn about something that is working for one business or industry or sector, I like to imagine how it could be adapted to benefit something else. These days, that something else is always Social Impact Assessment. And for today’s post, the thing that is working is User Behavior Analytics, and particularly how the data they are based on is gathered.
While I was reading a recent article from FastCompany (Are User Behavior Analytics The Real Predictors Of Customer Engagement?), I found myself substituting phrases like “market share” and “customer economics” for “community engagement” and “social impact measures.” The article is very interesting, and describes how social gaming companies and analytics firms have taken advantage of the “blessing [of having] unlimited amount of data about their customers at their fingertips” as well as the “curse [of having] to figure out a way to sift through all of that data to figure out what’s meaningful and what isn’t.” That would be champagne problems for mission-driven organizations. I read the phrase “[t]hey used customer data to drive engagement, fuel product development, and improve the user experience,” but adapted it as I was reading to state that “we can use stakeholder data to drive engagement, fuel service development, and improve the social impact.” Here’s one more example of adaptation. Instead of “Understanding and engaging customers requires looking beyond traditional web analytics. To optimize and engage the end user experience across multiple touch points including the web, social sites, and mobile applications, companies must instead focus on user behavior dynamics to analyze and identify deep behavioral insights from their data,” I read “Understanding and engaging stakeholders requires looking beyond traditional impact analytics. To optimize and engage the end user experience across multiple services, activities, and resources, mission-driven organizations must instead focus on stakeholder behavior dynamics to analyze and identify deep behavioral [and impact] insights from their data.”
Did I lose anyone with all that repetition? The differences are key. Developing Social Impact Assessment can seem daunting because it is so important and critical, but also because we don’t have any singularly recognized model from which to work. But maybe we don’t have to reinvent the wheel – at least not completely. Take the example from the article of how Pittshburgh-based startup NoWait engages customers through mobile devices by letting them know when their table at a restaurant is ready, connecting the restaurant to the customer and opening the path for a slew of data to be collected. Mission-driven organizations can find similar paths to engaging their stakeholders by providing them a service that also makes the stakeholder connection to the organization deeper, and the channel for collecting data more open. For instance, I’ll use my favorite non-profit example, literacy and mentoring organization Everybody Wins!. Since our main stakeholders are kids, the service we provide them may not be as appreciated as a restaurant place-holder, so let’s mask it in a game. We build a points-and-reward system based on how many hours a child puts into reading or otherwise interacting with a book (this could be having a book read to them, drawing pictures based on a book, writing their own story changing parts of a book, etc.). On our website, we make an interactive game that leads the child to enter their hours and activities. Kids get fun and reward (and incentive) for reading or otherwise interacting with books, and our organization gets self-reported data on how our program is (or isn’t) encouraging kids to read. We also engage kids more with our organization’s services and with books by making a game out of the data collection system. Finally, we get User Behavior Analytics on how kids are interacting with books, what they like best, how we can better reach them, etc. This is all theoretical, but why not try it out? Why not at least explore it, especially if similar approaches are working in other environments, like the ones described in the FastCompany article?
Now, the real challenge is clocking things other than hours, number of books read, or other similarly quantitative measures. How do we utilize User Behavior Analytics to capture and gauge things like how kids engaging with books helps their broader success in school,helps them to become more interested in learning, advances their creative and analytical skills, increases their ability to communicate effectively with others about books? I can’t wait to hear your input on this!