As I write this I am on a flight with my wife to Central America for a quick anniversary getaway and then I am off to Miami for Compete's Digital CMO event. As I look around the plane there seem to be a few different types of people:
These people are thinking about different things and focusing on different things as they prep to board the plane and while on the plane. But more important is how these people were feeling when they were preparing for their travels. They surely were in different mindsets, with different priorities and needs depending on which of the groups they fall into.
In fact, with a recent client we found some really surprising results and preferences when booking travel. We recently completed a round of testing (A/B and multivariate) for a "travel-related" website that allows people to book travel. We were looking to increase the conversion of identifying travel and then booking the travel that was found, as well as increasing the average booking value. We hypothesized about what could drive conversion as well as increasing the booking value (I apologize about needing to be somewhat vague, but I need to for client confidentiality reasons).
We started testing a few different areas throughout the research and purchase process around calls-to-action, wording, imagery, and layout. We chose not to test pricing differences in this round. This was not a single test but a series of tests. At first blush we were getting pretty mixed results on our different tests, most not making much of a difference on a macro level.
But then we dug a bit deeper into the data. We looked at weekday results, vs. weekend results (which often can show considerable differences). In addition, we analyzed dayparts, but didn't find anything significant with either of those.
Deeper again, we looked to understand why things weren't moving. We decided to look at where people were searching from. Meaning what city or state were they in when they were looking to book travel. Eureka - we found some amazing things. Many of the tests (not all) were showing considerable differences depending on where people were searching from. Between LA and New York you might think there could be a difference (and there was). But we also found significant differences between people accessing the site from cities as few as 300 miles apart. What was happening is that some versions were working really well in one geography and the same one poorly in other geographies. This caused the test to look like a wash in terms of results when there were some real winners hidden in there.
But we still weren't satisfied; we also looked at a few other things:
Now you can see that there are all of a sudden a ton of different combinations. Did all of them matter? No. But some of the combinations made a material impact. The impact of these changes equate to over $2 million per month in increased revenue (with a higher than normal profit margin when compared to their typical revenue).
Most of this lift has to do with tuning to geographical "tips" or hints that visitors carry with them. But our work isn't done. We are continuing to test, tune, and leverage behavioral targeting techniques to figure out ways in which we can help our client improve even more. All while also focusing on any long-term impact and softer things like satisfaction scores (which have increased slightly).
The impact of local and mobile can mean many different things to marketers. It doesn't need to be complex and you will often be surprised by what you find in terms of differences. If you haven't looked at how people in different geographies are accessing your content and tried to find ways to better communicate with them, you have an untapped opportunity waiting for you.
Give it a shot. Got to run, the flight attendant just dropped off a vacation drink, which I am going to enjoy while watching the business travelers prep for their meetings!
Image on home page via Shutterstock.
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As the Chief Performance Marketing Officer for POSSIBLE, Jason supports the agency's global Marketing Sciences and Media Services programs.
His primary role is to help POSSIBLE teams and clients use data to craft digital strategies that attract, convert, and retain customers - maximizing ongoing ROI across paid, earned, and owned channels. He believes that brands can better serve their customers by understanding audience behavior, and that messaging should be targeted to individual customers through the use of testing, behavioral targeting, and CRM initiatives.
Jason has written extensively about digital analytics, optimization and digital strategy, including an ongoing column at ClickZ.com. He is the co-author of "Actionable Web Analytics: Using Data to Make Smart Business Decisions," which is one of the leading texts in the field of digital analytics. His client roster includes Microsoft, Nike, Nokia, Dell, Ford, Sony, PayPal/eBay, P&G, Alcoa, Expedia, Mazda, Intel, and Motorola, and more. Jason is a frequent speaker at conferences and seminars around the world ranging from the Cannes Lions, Adobe Omniture Summits, eMetrics, SES, ad:tech, BazaarVoice, and many other WPP events.
Follow him on Twitter @JasonBurby.
December 12, 2013
1:00pm ET / 10:00am PT