After recently complimenting the Adobe research on consumer preference regarding mobile apps versus mobile browser, today I’m stepping it up a notch. Google Travel in the UK, in conjunction with Nielsen, have produced the best insight into the actual behavior of the online travel buyer in quite a while (thanks to regular reader Mario Santoyo for alerting me). After reading this post, I strongly recommend you download the report and really spend some time on each slide trying to understand how it impacts your business.

Before I get into the report, just to be super clear, this is praise solely for the quality of the report and the methodology used; I’m in no way going to touch broader issues related to Google’s strategy in travel – if you want comment on that point, then here is the official Amadeus position on Google ITA. There’s not much I steer clear of on this blog, but that is one topic I’ll happily leave to others.

Nielsen data is far from perfect, but I’d still trust it almost any day over data asking people after the event what they recall having done and in which order they did it. I’ve seen some research showing heavy users of social networks are also the biggest spenders online although I’m still looking for better data than the Morpace report on Facebook usage by age and ethnicity that I made a request for in my last post in order to round out some thinking I’m doing on understanding different aspects of passenger behavior during the online travel purchase process. The Google/Nielsen report below fills in many of the gaps in understanding how consumers buy online travel, but the point I’m making is that this is a quest where sometimes good new data just leaves you wanting even more.

The first chart here is pretty standard stuff showing the bigger spenders are the older consumers coming from households with higher income. But soon after, the insight really starts.

Slide 15

This study apparently monitored the internet usage of around 50,000 UK residents from January – March 2010. During that period approximately 31% visited one of the 490 sites classified as a travel related web site. Of that 31%, 85% requested a quote or price of some type, and a quarter of the 31% actually made a purchase with 10% of that 25% actually making 5 or more online travel purchases during the three month period.

The slide below is fascinating when you compare what other travel products the network (traditional) airline passengers purchased when compared to those that purchased an LCC ticket within the same 3 month window. I’d be interested to know if the 17% buying from an OTA after purchasing the air segment from a network carrier includes white label hotels sites where the airline earns some ancillary revenue. I was surprised to see for people buying a hotel first that 17% went on the purchase from an LCC – either my question about whether air could ever be ancillary to the hotel purchase is already a reality, or there are multiple trips to different destinations being planned and this study is not seeing that.

Slide 19

When I originally write about The Bow Tie Model some of the data came from 2007 Google research. It is very interesting to see that in the last 3 years, the number of searches prior to purchasing travel online has increased from 12 to 18. The diagram below seems more credible to the left of the gray vertical bar (same point as the knot in the Bow Tie) as unless Google/Nielsen are monitoring the actual date of travel from the online purchase (unlikely), the arrow to the right could just as easily be planning for a subsequent trip and unrelated to that first travel purchase represented by the gray bar. This entire research report is designed as a sales tool for Google, but it really drives home in so many ways how search is now so powerful over the travel brands, and is only going to get more powerful.

Slide 22

One of the reasons why I say search will become even more influential is because if you look at the next chart you can see how map sites have come from nowhere a few years ago to become an integral part of the search experience today. And this chart is just those booking air travel. Note that map sites in this study are only counted when they are visited in the same session as a travel site was visited – the influence is still probably overstated somewhat as it is entirely possible someone looks at an airline website without buying, and then in the same session checks directions online for how to get somewhere within their own city. Even so, no-one will argue that the map is becoming a crucial component within the integrated search experience.

Slide 26

Nielsen show that 30% of travel searches contain a brand name within the query. This is made up by 18% brand only, plus 12% using a brand combined with a generic term. At this point airline websites really need to focus and pay attention, as the chart below implies that airline brands are the most frequently typed in brand names during the search, or at least the brand names that correspond to the highest rate of click throughs. For an airline spending so much on branding the website URL, only to have consumers show a strong tendency to type the brand into the search engine must be a bitter pill to swallow. I see this is the biggest impact on the airline direct channel as it is saying to me that no matter how strong your brand, you still need to pay for clicks on that brand name to ensure that the people who intended coming to your airline website actually make it there.

Slide 36

The theme I started in the paragraph above is reinforced here, as when you look at the chart below, it shows that even consumers who start with a generic search terms end up veering more and more towards brand names on subsequent searches – and the more you search, the more days you are into the pre-shopping experience and the closer you are getting to the point where you are ready to pull out the credit card. If people are searching on brand names at the point they are ready to purchase, then it gives the search engine enormous power to sway that consumer at the critical moment and redirect them to another channel or supplier.

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Slide 38

And here is the conclusion slide, for me at least. 31% of consumers (26% for Google plus 5% for other search) in the actual session where they go on to purchase travel, begin that session with a search engine. Very few are typing in airline.com, but as we saw above, a large number of airline travel buyers know the brand they want, search on that brand name, and then if you are lucky, somehow they end up buying from your airline website at the end of this process. This understanding should have profound implications for any e-commerce manager as either you embrace it or fight it, but make sure you understand it and do not ignore it.

Slide 46

One curious thing in the chart above is that I think Google/Nielsen have designed their methodology in this case to significantly understate Facebook who I assume are in the 6% of “Non-Travel Other.” As I understand it, they would only count Facebook in the above example if the user had clicked on a link in Facebook that then directed him to the actual airline website where he made the purchase. I saw the term f-commerce for the first time yesterday, and the one question this study leaves in my mind is where Facebook fits into this picture. Someone who understands advertising on Facebook very well told me recently that the click through rates on ads there are absolutely atrocious, but I’m still interested to better understand the who Facebook phenomenon and that piece of influencing travel consumers prior to purchase.

I am impressed with the way Google in particular, but also Bing, have made themselves such as key part of the online travel buying process in quite a short space of time. I used to think that search played a role mostly  at the extreme left of the Bow Tie, but as this research so clearly demonstrates, search is present during every session, and the power of search to move the purchase behavior of a passenger who may have originally intended to purchase from your airline website is nothing short of amazing.

To read the report in full, click here.

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