For the second year in a row Liberty Mutual Insurance was an official sponsor of the Bank of America Chicago Marathon. The event hosted a record 40,802 runners from around the globe and attracted an estimated 1.7 million spectators.

Our challenge was to turn a straightforward sponsorship into a meaningful opportunity to demonstrate our brand values. Liberty Mutual Insurance needed to stand out among the sea of other sponsors, while raising awareness and engagement. Our goal was for consumers not just to remember Liberty Mutual, but to feel as though they’d experienced the company promise – to support people on the road, whether they’re in their cars, or their sneakers.

Despite having virtually no paid media, nearly ten percent of this year’s marathon runners signed up for the Moving Words platform. More than 3,000 runners—and an untold number of friends and family—communicated in real-time during the marathon. In the process, they were able to experience for themselves Liberty Mutual Insurance’s brand promise of helping people on the road. And they weren’t even driving.

The Bank of America Chicago Marathon lasted just 6 hours. During that window the campaign generated:

Over 80,000 comments from friends and family

More than 160,000 likes

And over 5.2 million impressions

The proof this real-time interaction during the race had an impact? More marathoners crossed the finish line in 2014 than in any other Chicago Marathon.

We knew that official marathon times were gathered by tracking the RFID tags in runners’ race bibs. But so far, these numbers had only been used by the race officials, and in a handful of straightforward tracking apps.

We saw another use for the data, one that could help support both marathon participants, and their family and friends on the sidelines. For the first time, we allowed marathon runners and their friends and family to have a social dialogue during the race itself.

We pulled each runner’s data in real time at different points along the course, and then compared it to their previous results. By comparing the difference in speeds between checkpoints, we were able to tell if a runner was slowing down, speeding up, or staying on pace. And by combining this information with each runner’s target finish time (gathered when they signed up for our Moving Words program) we were able to tell whether a runner’s performance was jeopardizing their finish time, or putting them on track for a personal best.

This level of detail allowed us to translate their data into conversational Facebook messages that were posted on the runner’s behalf during the race. Unlike a race-tracker app, these messages didn’t display pace times, but described how runners were feeling throughout the marathon.

Each runner was able to select a personalized tone. So the resulting posts sounded like they were written by the runners themselves, encouraging more meaningful responses from their supporters in the comments. We then displayed these Facebook comments course-side, targeting runners at the most difficult parts of the race and giving them the specific support and encouragement needed to keep them going strong.