When I was part of the team that created www.ibm.com, we tracked where people went after they viewed the homepage. The answer in most cases was “somewhere else.” Those who visited exhibited “touch and go” behavior. I was tasked with making the site stickier, and one of my responses was producing the first Web pages featuring Deep Blue, long before the machine defeated Garry Kasparov.
I ended up doing a lot to understand and respond to audience engagement, back in the days before cookies and other sophisticated ways to measure Web behavior. I had an Applause-O-Meter people could use to show, on a scale of one to ten, how much they liked a page. I created serial stories that showed me how deep the viewer interest was in a topic. And, of course, I solicited readers’ comments.
We’ve come a long way in terms of what is now called engagement analytics. There are means to track clients and customers on the Web, sophisticated algorithms for categorizing behaviors and finding patterns, and clever ways to solicit participation (such as free online games, polls, “click bait” headlines, and quizzes that tell you which character you’d be in a popular movie or TV show).
Engagement analytics can demonstrate interest, aversion, obstacles, and attractors, and it can tell businesses which markets to target.
Now it may be headed into a new space, reaching beyond the Web thanks to mobile devices. I recently read an article about engagement analytics (EA) in the e-book world, which discussed data gathered on how far into books people read. In some ways, such testing beyond the virtual world has been around for a long time. In his autobiography The Name above the Title, Frank Capra claimed to be a pioneer in testing films with preview audiences. He mentioned how in one case, the audience reaction saved one of his movies by making it clear that part of the story should be cut.
Restaurants have used limited-time menu items to choose new offerings. Playwrights hold public readings of new works to gauge audience interest. Software is released to beta users. None of this sort of real-world testing is new.
But mixing in mobile devices, which provide rich data in real-time suggests other possibilities. Teachers already shape lessons and are prompted to provide individual help in Flipped Classrooms, where behavior in computer-driven lessons is monitored, but this could move into an area of individual instruction for physical activities like swinging a golf club or playing piano. And we might learn more than how far students are progressing in these. We might get clues that indicate where unexpected obstacles (such as the size of a piano keyboard for people with small hands) exist.
Similarly, compliance with medications and therapies might be improved by sensing when and if prescribed courses of antibiotics go unfinished (a major cause for the development of resistant pathogens) or rehabilitative exercises are abandoned.
The use of household objects (from lawnmowers to coffee makers), industrial equipment, and new inventions could be tracked in detail to indicate where frustration sets in, where steps are done out of sequence, or where we make dangerous choices. The data could be used to take immediate corrective action, provide warnings or suggest training, but what is discovered could also feed into the design decisions to enhance usability.
As we move toward Internet of Things, the potential of engagement analytics can be expected to grow rapidly. Our environments are already filling up with smart devices that interact, which could take engagement analytics to a higher, more holistic plane. Our constructive participation in this world is likely to be facilitated by monitoring, measuring, analyzing, and providing instantaneous adjustments or advice so that our environment can adapt to us or we can adapt to our environment.