A Reward Gone Wrong
One thing we know about consumers is that they love their rewards programs -- and this is especially true for frequent fliers. Traveling can be stressful, so anything an airline can do for their faithful passengers to create a seamless experience is greatly appreciated. This is exactly what a major airline thought they were doing when they introduced a new policy of charging infrequent fliers for checked bags while waiving that fee for their frequent fliers. The airline discovered through their social media mining program that there was a big surge in negative sentiment in relation to the brand. As with any change, this was not unexpected, but it was surprising that the folks complaining were the very same people they had hoped to please – their frequent fliers.
Drilling down to the verbatim level, we found an undifferentiated mass of comments -- retweets of offers or promotions from owned content providers, and travel stories that might or might not contain some cranky comments about our client’s baggage policy. But the effort of finding these complaints was enormous.
Big Data Hits a Wall
So while the big data technique of social media mining alerted the airline to the existence of a problem, once armed with that focus, it was much more efficient and actionable to simply, directly ask some members of this airline’s private community comprising 300 of their elite fliers how they felt, and why.
And when we did, the responses were targeted and specific:
The new baggage policy is not fair. You say ‘Our most valued passengers’ and put all members in the same category -- something is wrong. You give me (100,000 miles in 2012) the same benefits as my 5-year-old son with a basic card. 2 free bags for elite plus, 1 free bag for others please.It’s not the baggage charge that gets me, as I probably have 20 business flights for every personal one, but it’s now going to be a complete bitch to get any overhead locker space. Just another way to make flying more miserable. Maybe it’s time to go back to an office job.”
In some respects, the briefest but most telling response was this one:
Don’t become a budget player and keep focusing on quality.”
It’s short, but it’s actively prescriptive. It’s written in the voice of a flier who knows and values the airline, and is offering thoughtful, candid and constructive advice. It’s the voice of a consumer who has been enlisted to collaborate with the airline in making it better, to serve as a knowing, active advisor invested in actually solving the problem.
In the case of the grumpy fliers, big data surfaced the problem with the baggage policy but private, active collaboration helped reveal the counter-intuitive reason why: while the baggage policy was designed to make frequent-fliers feel special, it actually served to muddy the waters and stir up negative feelings about flying in general.
Big data analysis is great at finding and displaying patterns and correlations, while collaboration helps forge and understand the deeper connections underlying them. Big data is invaluable in shining a light on the areas worth exploring, but it takes relationships and collaboration to understand how people make meaning of their own experience and to weigh the importance of those narratives.
So next time big data serves you up the WHAT, take a minute to consider how collaboration might help you understand the WHY, in order to generate action and push your campaign forward.