Combine customer data with artificial tech, says Anoma van Eeden, chief marketing officer at Relay42
The way that consumers shop for products and services online has changed dramatically, and it’s largely due to companies like Amazon.
It was among the first of the large e-commerce giants to effectively utilise customer data in order to deliver a more predictive shopping experience, with personalised product recommendations that quickly proved immensely popular.
Since then, we have seen many businesses struggle with the challenge of moving away from generic offerings and towards a truly customer-centric approach, particularly within the travel industry.
Consumers are now fully aware of the benefits of personalised communications offers — in fact, they now expect these offers from all airlines and travel agents as standard — which puts brands under pressure to live up to these demands and expectations.
In order to successfully achieve personalised communications on a large scale, brands need to orchestrate their efforts according to both individual customer preferences and the journey that a typical customer undertakes.
This requires an approach that begins at the initial awareness phase and goes right through to customer retention.
However, succeeding in the travel market through this personalised, customer-centric approach has proved to be a tough nut for many travel companies and marketers to crack.
Indeed, even Amazon themselves made the shock decision to shut down its dedicated travel booking site, Amazon Destinations, in 2015.
Along with high levels of diversification, one reason for this challenge lies in the decision window for customers purchasing airline flights, which is significantly different from most other industries.
If a customer is looking to purchase a return ticket to Los Angeles from London, for example, they will typically be far more vigilant in comparing the prices of several different airlines, and may take much longer to actually make the purchase.
This is also true for the type of trip a customer is looking to go on – customers are likely to spend longer researching long-haul flights than they are short-haul.
With so many different consideration factors at play, it is therefore essential that airlines and other travel companies are able to use data to uncover insights that enable them to engage with customers more intelligently.
If this is done right, with true 1:1 personalisation at scale, it can be an extremely effective way of acquiring and retaining long-lasting relationships with customers.
Just imagine, for example, that the consumer we previously mentioned above is at the very beginning of their purchase journey and goes to his favourite website to book a flight, but he chooses an economy flight to Los Angeles.
Using the first party data a brand has, they can see that he always flies business class to Los Angeles, and so they can send him a trigger in real-time to upgrade to business class with a personalised message. He’s happy that he gets this message and goes ahead with the business class booking.
Thinking like this on a broader level, travel marketers could optimise every marketing opportunity — and deliver value on every customer journey — extending it from a single channel exchange to a multi-channel journey.
This ties in seamlessly with the demands of consumers, who now expect consistent, relevant communications across numerous touchpoints, whether they be online or offline.
However, this does not detract from the fact that achieving personalised communications on this scale within the travel industry is hugely complex and demanding.
The answer that travel marketers have long been searching for could lie in combining all of the data they hold with artificial intelligence (AI) technology.
Through deep learning — one of the most powerful AI methodologies — this technology could be used to streamline the marketing process and create AI driven customer journeys, essentially delivering effective, real-time personalisation at scale.
AI can also play a huge role in moving from an audience-based approach to an individual one.
Thanks to AI’s ability to identify logical patterns among huge amounts of data, the technology can learn from the behaviours of all individual customers, and distil this into signals among the irrelevant noise to create precise journeys, depending on specific rules — regardless of where that individual engages.
There’s no denying it: achieving effective personalised marketing as an airline or travel brand is tough.
Target audiences are vast, and the browsing and purchasing behaviours are unique to the industry.
But if high-quality customer data can be combined with AI technology, marketers can effectively communicate with travellers within the critical decision window, which can in turn increase conversions and further build customer loyalty.