How TUI optimises conversion as travel returns, with predictive machine learning insights

TUI used Predict insights to selectively offer high value coupons to customers, boosting its conversion rate.

Challenge:

To predict customer preferences as travel restrictions change, while prioritising privacy and compliance.

TUI, the largest global travel brand, helps more than 21 million customers worldwide with their holiday arrangements – both online and via brick-and-mortar travel agencies. 

Operating under numerous brands, such as First Choice, TUI collects vast amounts of customer data. To deliver the best customer experience possible, TUI has undergone significant digital transformation over the last ten years. This included pivoting its approach to a first-party data strategy, powered by the Tealium Customer Data Hub.

While travel was put on temporary hold at the height of the pandemic, TUI’s analytics teams used this as an opportunity to take the next step on its customer personalisation journey. As part of this, Tealium Predict proved business critical in the months of recovery to come.

Solution:

TUI deployed Tealium to layer machine learning onto its CDP, using predictive insights to improve conversion rates.

As holidaying gradually returned (with all the bumps in the road associated with the pandemic) TUI already had Tealium Predict in place to predict customer travel behaviour. By working with Tealium through the pandemic, TUI is able to predict which customers are more comfortable with travel in what is becoming a Covid (rather than post-Covid) era, and what type of travel package they might prefer.

TUI’s customer personalisation journey started in 2012, with Tealium’s CDP building a strong data foundation, an agile tag management system, and improving data quality. It’s a journey that has seen TUI’s landing page dynamically adjust to user behaviour, so the customer information and marketing offers get increasingly personalised with each click.

In 2020, TUI took the next step, deploying Tealium Predict to layer data-driven, predictive insights onto the CDP that could further improve conversion. By introducing machine learning, TUI can now predict customer behaviour more accurately and gauge which incentives – from coupons to teasers – will drive the best conversion rates, while ensuring compliance with region-specific privacy regulations.

Predictions are presented as an easily interpretable score, between 0 and 1, reflecting the likelihood of an individual returning to TUI’s website or purchasing a holiday. For example, a score of .99 means the user is extremely likely to complete a purchase in a given timeframe.

Layering Tealium’s predictive insights onto its CDP has been a real gamechanger. The targeted use of personalised coupons has proven instrumental to improving our conversion rates. Here in Germany, it’s a legal requirement to sell a holiday package at the same price both in-store and online, so coupons enable personalisation where it’s needed. With this level of insight, we can prioritise a great customer experience, while remaining compliant with regional legislation, and improving our conversion rates amongst certain prospects.”  Karin Marksteiner, Head of Analytics, Data & Personalisation, TUI Deutschland GmbH 

Results:

With this insight, TUI can not only pinpoint the likelihood of a customer returning or making a purchase, but they can also take proactive action to encourage this behaviour. By focusing its personalisation efforts on the most likely-to-convert prospects, TUI can execute smarter marketing activity – specifically integrating coupons, teasers, promotional codes and deals for website visitors – to achieve a higher conversion rate. 

This has proven instrumental with the return of travel during Covid-19. In a testing sample of 160,000 customers (of which 20,000 were identified as fairly likely to convert), TUI used Predict insights to selectively offer high value coupons to customers, boosting its conversion rate by 400%.

Resource Type: Case Study
Topic: Customer Data Platforms, Machine Learning, Personalization, Predict
Product: AudienceStream Customer Data Platform, TiQ Tag Management
Vertical: Travel
Business Issue: Single View of the Customer (Personalization/Experience)