Traditional landing page optimization can yield big results
There are many opportunities in the endless game of conversion optimization in travel, especially when considering how many different demographics are searching for travel products at any given time.
E-commerce optimization firm Intent Media recently released the results of a study showing that airlines can increase conversions by as much as 25% by “better matching landing pages to different types of trip profiles.”
The sample cohort came from those using Intent’s Ads for Travel product, which places external links in-line on OTA search results, allowing OTAs to monetize non-converting traffic.
The company tweaked the landing page for certain airlines, using already-existing airline assets to customize the landing page according to predictive intent.
Each landing page was customized to a particular trip profile. For example, those projected to be searching for leisure trips were directed to a calendar-style landing page, where they could see fares both on and around the entered dates. The normal landing page would have only included the searched-for dates, without calendar context.
The switch from the traditional, one-design-fits-all landing page resulted in an impressive 20% increase in conversion. By considering the type of consumer – and what journey they are searching for – airlines were able to make more money by converting more browsers to purchasers.
So how could these results apply to the wider travel industry? Tnooz went into detail about these results with Intent Media SVP Rob Schmults.
What implications do these results have for airlines?
For airlines — and advertisers more broadly — the results show the importance of de-averaging. While there is always a best answer on average, as you dig in, what you typically see is a subset of your customers are the ones driving that answer. By removing this group you then expose a new best answer for the remainder.
As you continue to do this you discover there isn’t one best answer, but in fact several. Each just needs to be applied to the relevant portion of your customers.
Not that this should continue indefinitely. You’ll reach a point of diminishing returns where the cost of servicing a group exceeds the value generated by de-averaging. But clearly in the case cited here, we’ve kept it to two. Is there more value if we continued to de-average? I’d expect there is given the volume of traffic and the diversity of why people travel and how they make their purchase decisions.
What can other travel verticals learn from this research?
At its most basic, they can learn the importance of understanding what a given set of prospects might be looking for and they lining up against that use case. You already see some of the more advanced practitioners — folks like IHG — trying to make that happen consistently.
What three things can a travel brand do to ensure that their marketing offers are reaching the right profiles?
First they should flip the thinking around: “what profiles are out there among my prospects?” Start with that. Then figure out “what do I have that’s relevant to each of these profiles? How do I make things more relevant and easy for them so they buy from me?” And then lastly, “where and how can I best reach them so that my offers are in the right place and at the right time?” Nothing particularly new in all that, but it is amazing how often marketers can forget it when blinded by the latest new technology or program.
Just to amplify a point: we’re not talking one-to-one marketing. I think that goes way beyond what creates value for the consumer and thus for a brand trying to market to that consumer.
Even though everyone is different, at any point in time, several people may be acting exactly the same way in terms of what they are shopping for, how they are doing it, and the attributes they care about in coming to a decision. This means that very different people demographically — or even based on CRM data — will look exactly the same in terms of what they want.
Correctly grouping these people has been essentially impossible until recently — the tools and capabilities weren’t around. But now with properly developed and applied predictive models, it’s not only possible, but scalable and cost effective.
How can a brand deploy assets it already has more effectively given these new insights?
That’s exactly the right question. As a brand, developing content and other assets can be very expensive. Some tools out there — like dynamic content generation — help plug the gap. But beyond that, brands should do exactly what the airlines in this study did: look at the assets they already have and map them to the customer needs. From there a brand can evolve to understand where it might be worth it to augment and extend what they have already got to generate even more value
Nick Vivion is a reporter for Tnooz, based in New Orleans, USA.
His passion for travel technology led him to travel around the world shooting travel videos for Current TV and Lonely Planet TV in 2006 and 2007.
He shot on Mini-DV, edited on a white MacBook, uploaded and shared online as he traveled. His moxie for travel video has resulted in over two million views on his YouTube partner channel.
In addition to travel, Nick co-founded of one of the web’s most talked about LGBT media sites, Unicorn Booty, and has gone "blog-to-brick" with a bricks-and-mortar restaurant called Booty's in New Orleans – serving street food from around the world.