Confessions of a data scientist: our in-house metrics man, Chris Doughty, on numbers, nature and performance improvement

Hi Chris. First, can you tell us something interesting about yourself?

Whilst I was studying, during the summer, I arranged a trip to Namibia to work on a nature reserve, which specifically cared for the Cape griffon vulture (Gyps coprotheres). With the impact that technology has upon us in society, it was great being able to feel completely disconnected and learn a lot about the culture and environment. One of the skills that I picked up on the reserve was tracking, observing animal tracks to read into the landscape. This was exciting when finding unidentifiable prints, which later turned out to be a cheetah roaming through the reserve, which certainly made me more cautious. It also proved useful in tracking down traps that poachers had illegally placed on the reserve.

Whilst my travel plans are now much less risky, I still enjoy exploring new places and spotting wildlife. Skyscanner is full of people who appreciate all aspects of travel and it is great to be part of the process that facilitates people’s experiences.

How did you get into data science?

Data science has always been a field of interest. I studied and completed a degree in Behavioural Biology at the University of St Andrews. This involved studying animals’ environments and behavioural interactions at both an evolutionary and a proximate level, a lot of which can provide a framework for understanding several aspects of human behaviour. There is often either a technical or a scientific explanation behind a lot of the patterns observed in digital data.

During my final year at University, I produced a research study that observed the mating patterns in the parasitic wasp Nasonia vitripennis, teaching this knowledge to a computer in order for it to run simulations of the described behaviour.

Upon graduating, I spent four years working in the digital advertising industry putting this knowledge into practice for audience insight, attribution modelling, and consumer research projects. Working for Skyscanner for Business for the past year has opened up an interesting array of data challenges. Travel is something that is applicable to all of us and raises some exciting data projects in relation to behaviour.

Can you tell me a little bit more about the work you do for Skyscanner for Business specifically?

I think it is agreed that the traditional model of a linear purchase funnel is out-dated, especially when it comes to travel. The complexity surrounding travel when it comes to research and purchase provides a significant challenge in processing and analysing this data.

My work all starts as a question. What question are we trying to ask about the product, consumer behaviour, or business? These questions are not only specific and measurable but they also need to be attainable, which means having the right data available. Part of what I do is evaluate our current data to see whether it allows us to answer these questions. If it doesn’t then we collaborate to find a solution that enables it.

The projects surrounding these questions provide us with the information to assess the traffic from our partners, highlight technical problems, understand the behaviour and journey of our customers, and produce products and features that improve the customer experience.

As well as longer term projects utilising our data, it is my goal to ensure that all relevant data is surfaced to all our internal squads. This aids them in measuring the impact and performance of our work.

Each Skyscanner for Business partner that we work with has different content, audience profile, and requirement for driving customers to engage with a travel search product. Whilst this increases the complexity of our business, it means that we are able to process data across a diverse range of websites and work on features and recommendations that best suit these customers. Data is at the core of this decision making and is useful for both service and business projects.

How does data analysis feed back into the quality/build of the Skyscanner for Business suite of products?

Almost all of the data that we process in Skyscanner for Business relates back to the behaviour of the customer. The more we can understand about how our customers are using our products and the journey they take, the better their overall experience. Customers searching for flights will fall into a classification of the trip they’re planning; the way in which a family compared to a business traveller researches will greatly change the flight they’re after and the factors that are most important to them. It is our job to ensure that our Skyscanner for Business products, such as theWhite Label , are configurable for our partners in allowing them to best provide this experience.

The features that we include, remove or refine, fundamentally rely on the data we have so that we can ensure efficient and effective design.