It’s happened to just about everybody who’s ever bought tickets for a concert or ballgame online. You go through a lengthy, multi-step checkout process, only to discover at the last second that your total price for the tickets is $5, $10 or even $15 higher than expected.
“Next thing you know, there’s these service fees attached to my transaction and they’re outrageous,” is how Ming Teng, head of analytics at online ticket broker
Teng was aware of the frustration that customers experienced as a result of the hidden fees, and the company decided to experiment with disclosing service fees earlier in the checkout process. Using data analytics technology from SAS Institute, StubHub was looking for the optimal balance between improving customer satisfaction and not losing potential business.
StubHub’s customers often have a limit on the amount they’re willing to spend on tickets for a given event, Teng explained. Some customers looking for four tickets to a Bruce Springsteen concert, for example, might not be willing to spend more than $75 per ticket.
If StubHub discloses its service fees on the first page of search results, and the fees bring the price of Springsteen tickets above $75, the company just lost the sale. It might, however, win the future business of some of those customers who appreciate the transparency.
On the other hand, if StubHub waits until the last step in the checkout process to disclose its fees, some of those same customers may actually make the purchase, considering all the time they’ve put into the process. They’ll probably resent the last-minute hike in price, however, and decide not to do business with StubHub in the future.
“We are willing to take the short-term hit on conversion in order to appease our customers,” Teng said. “[But] if we’re making tradeoffs to bring a better user experience to the site, we have to look at it from all angles.”
That’s where data analytics comes in. StubHub ran a series of tests, disclosing fees at different points in the checkout process to different customers. Some customers who logged on and searched StubHub for concert or sports tickets saw the fees right away, others at the end of the process, and others at various points in between.
Data analytics software strikes balance of customer satisfaction and profitability
StubHub also polled its customers after they purchased (or didn’t purchase) tickets in order to gauge their satisfaction. Teng and his team then integrated the conversion rate data and customer satisfaction data.
With data analytics software from SAS, StubHub was able to determine the optimal time to disclose service fees, balancing the short-term pain of losing an immediate sale with the long-term gain of creating loyal, repeat customers.
Though he declined to say exactly where in the process fees will be disclosed, Teng said StubHub plans to institute the change on its site in the near future and is actively using data analytics to identify other areas for improvement that will ultimately help the bottom line.
He said analytics has taken on new importance at StubHub now that the company has evolved from a plucky startup to a more established firm.
When it was founded in 2000, StubHub -- like most successful startups -- enjoyed significant growth rates, Teng said. When you start with zero customers, there’s nowhere to go but up.
But in the last several years, customer growth has started to plateau, so finding and keeping potential new customers has become critical. And analytics, Teng said, plays a key role in those efforts.
“It’s really critical to retain customers,” he said.
StubHub is also using data analytics to determine those concerts and sporting events for which it should offer its last-minute ticket sales service. The service involves setting up temporary ticket centers where customers who purchased online just before show-time or game-time can pick up their tickets.
Teng said: “For events where it’s profitable for us and it’s appropriate, we’ll definitely do it.”