Highlights from an Analytics and AI in Travel Conference
In March I travelled to the wonderful city of San Francisco for this conference here are the highlights from the two days
Analytics and AI in Travel North America Summit, a conference organised by eye for travel, took place for the first time in San Francisco this year. The summit promised to bring “the Silicon Valley of travel together with analytics leaders”, and was heavily focussed on sharing innovations in personalisation, prediction and reducing data fragmentation across the travel industry. The following post covers some of the highlights from the show:
Organising data science teams
Many of the talks touched on both how to scale and organise data science teams in your organisation. The universal opinion on this was that the data science team must not exist in a silo and should be integrated into cross functional teams. A specific use case and a sponsor must be available up front in order for the models to be successfully implemented. The result of not having this structure is that models are often either not used, or need heavy refactoring to fit the operational use.
Recommendation and personalisation approaches
There were some common themes around how to successfully use data to make recommendations and create personalised experiences. The need to develop fast through iterative experimentation was a common theme. Many of the talks suggested that personalisation should start with small proof of concept experiments starting with best customers first. An interesting point was around the cold start problem in machine learning — where you do not yet have labelled data. It was suggested that a solution to this problem is to start with basic assumptions, start making recommendations or tailored offers, and learn from the data generated to create profiles.
AI impact on travel
There was some discussion around how AI is enhancing both customer and employee experiences in the travel sector both through automation and personalisation. Tata Crocombe, Managing Director of Aitutaki Lagoon Private Island Resort, gave a talk about how he sees AI being used in hotel operational automation. Examples included automating some of the more routine duties in night auditing and applying AI to understand the requirements of stakeholders. Ultimately the main takeaway from this was that we can automate the “boring work” with AI so that “humans can do the fun stuff”.
Overall I found this conference extremely useful mainly from an execution strategy perspective rather than technical implementation of AI and machine learning. It was also interesting to hear about how other travel companies are using these technologies. The conference was reasonably small, I think there were around 150 people there, and this size setting meant that I got to meet and talk to some really great people too.
