NB: This is a guest post by Emmanuel Marchal, director at LikeCube.
How do you differentiate in a crowded online travel space, especially as you know the power of personalization is key to creating trust and make those visitors become repeat customers?
True, one-to-one marketing can yield benefits that will enable you to increase your brand’s loyalty and reduce your reliance on SEO and SEM.
But with so many ways to do it, it's hard to know where to get started and most importantly what is right for your site.
Here are a few tips you might want to consider:
1. From segmentation to machine learning.
The standard approach to personalization, which is CRM based, is through organising, analysing and segmenting the database and then crafting targeted marketing messages delivered at specific groups.
This approach yields benefits given the right amount of investment and skill sets, but may show limitations in addressing the fact that people’s desires aren’t static. The most innovative travel companies are now embracing machine learning to offer a real-time personalized discovery at the individual level. A bit like Amazon books recommendations, but for hotels, trips and restaurants.
Machine learning has the power to surface reviews from liked-minded people and answer questions such as "I liked this hotel in New York, where should I go in Paris". Machine learning solutions leverage data, lots of data, so while you may not plan for it today, it is definitely worth start investing in it today, in terms of data collection.
2. Collect data, all you can.
The data you own is a potential goldmine. So collect it, keep it and make sure it is clean and usable. We typically see two types of data.
The one linked to places, which is any metadata that can describe a place, like place information and description as well as tags, attributes and editorial content. And the one linked to users.
User data can be explicitly given (user generated content) like ratings, reviews, checkins, wishlists. It can also be inferred via search terms, clickstreams and bookings either from your website or mobile application. All this data is worth something in terms of personalization.
So if you don’t collect it today, consider starting now. If you already do, think about what future data you should be gathering (like mobile activity or geolocation) to increase your data personalization capital.
3. Personalization is a journey.
Machine learning techniques are slowly filtering to mainstream, but still have a considerable way to go, because of the challenges in terms of understanding, implementation, performance and scalability.
However, you can start with low-tech personalisation steps, based around tailoring search results and navigation (e.g. using profile and history information), while allowing users to add content (tags, ratings, votes, reviews, etc).
Once you have collected large amounts of user data, you can use cloud-based solutions to convert that into deep personalisation and business intelligence. The nature of your data should drive your solution, rather than the converse.
4. Social graph or taste graph?
The two are complementary. Exploiting the social graph is important for virality, and, with Facebook's likes, a good source of user data. But only few friends have similar taste to ours and, most importantly, we do not have enough friends to cover the places and things we need opinions/recommendations for.
With the taste graph, we can make use of "collective intelligence", not to build trivial average ratings, but to create sophisticated mathematical models of users and their taste that can be used to make personalised predictions.
5. Value to the user first.
Personalization is first and foremost about engaging users in a more relevant discussion. One where they feel they will want to hear more, interact more, while getting to what they are looking for faster.
For example, if a user has booked a hotel, in your next newsletter to that user, you might want to consider their last booking as a reference point to future recommendations. In general, it is always worth asking: “Would I trust this information, would I find it relevant to me?”.
Often, the information is too generic and miss an opportunity to engage. In our experience, the more narrow-casted the message, the better in terms of generating trust and loyalty.
This may mean you may not reach 100% of your audience with personalization, but the one you will reach should have a far greater value than the booking they will do. These will become loyal to your brand and by-pass search engines to find you.
NB: This is a guest post by Emmanuel Marchal, director at LikeCube.