Sampo’s Blog: It is All About Data, but What Data
By Sampo Hietanen, CEO and Founder of MaaS Global
For a while we’ve been hearing that data is the new oil. It sounds catchy, and yes data can be valuable, but raw data is like crude oil. There are different kinds of crude and they are useful first after refined – and refined for the right purpose. Diesel fuel for a bulldozer is different from plastic used in an artificial heart.
When you look at an organization like MaaS Global that wants to reorganize the world’s mobility, it is easy to presume that we are in the transportation data business. Yes, we sit on a mountain of data on how people move and use that every day to improve our service. But while it is important to know what is actually going on, in a space that is constantly developing, it is at least as important to know what people would like to see happening. In other words: a growing company in a growing market is good news, but if that company also knows where the market is headed, it is the one to watch.
At MaaS Global we mainly deal with three kinds of data: data on how people travel, insight into what they want, and experience in what they are willing to pay for. And all of this of course in different geographic locations.
The first, as said, is what one might think of when we look at a Mobility-as-a-Service company. So far we have data on 16 million trips: where, when and how people moved and which package they used. We use this to develop our application, packages, routing, modality split etc. Based on the data we can also run experiments and look how changes in user interface or pricing affect behavior. We’ve also tried introducing new data layers to our service, for example the times and locations of urban festivals. How people have used those, teaches us about what additional services may work on a mobility app and what may not.
Here I must also add that our business is not to spy on people and sell the results. When we collect data, we always choose the least intrusive way. When we handle data, including payment data and personal data, we are extremely cautious. But we do believe in open interfaces, and we do believe that people should own their own data, not corporations.
So, there’s transport data and then there is plenty of other data that is just as important. While the Whim app gives us data on kilometres and directions, it also tells us something about how our customers feel since they can chat with us through the app. This is of course not our only way to stay in touch. Through different channels we receive thousands of messages from our customers telling us what they like, what they don’t and what they want. When we test things based on customer feedback we learn when they mean what they say and when not. For example, we recently received a strong push from our users to add a calendar feature, an integration that would show a planned trip in the user’s calendar, but once we introduced it, practically no one used it. Similarly we learn about price elasticity of new packages and features (people are extremely sensitive to changing price of public transport, but not so much to the price of car rental).
In the end, going live with a package and a price is some of the best testing and data gathering you can do. Last spring in Helsinki we did a pilot that was both a sobering and an exciting return to the original vision of MaaS. In February we introduced the Whim Ride package to a selected group of users. The pilot group was picked so that it represented our core audience of urbanites that move a lot, but also so that it would be demographically diverse and offer us insight into different use cases.
With Whim Ride we did not sell trips, but made a promise that we would offer the users the most convenient way we could find to get them where they were going. For full service that included public transportation, taxis and rental cars, the customers paid 249 euros per month. During the pilot we did not just explore how well our service functioned, but also how the customer’s experienced satisfaction related to the price that they paid.
We observed how much folks used taxis and rental cars in relation to public transport, how rental cars should be available, how adding electric cars to the rental fleet affected the use of rental, and to what percentage of the users was public transport the backbone of their mobility. We also interviewed participants about what modalities they were missing, what their mobility pain points were (taking kids to kindergarten and groceries home for example), how their own values were affecting their mobility choices and what they wanted to know about the workings of the service.
What we learned was kind of a reset to square one in our thinking. It is so easy to get carried away with all possible add-ons, but winning in MaaS is about the core promise. People want a clean routing experience and they want to understand how the route was composed. They also need many different modalities to satisfy personal preferences and needs at a particular moment. When a lot of people move a lot, there must be plenty of options.
To make MaaS internationally scalable, you still need some additional data, and again it may not be what you think of first. When we enter a new city we are presented with a myriad of data on distances and routes travelled. But we have learned that data on transport is much too narrow an approach, when the aim is to change how people move. We need data on weather, on urban structure, on culture and on buying behavior. We have to look at the future of mobility through the eyes of the citizens, not through traffic stats. To this aim, as the first mobility company we recently conducted an international segmentation of mobility customers. It has become the lens through which we look at new markets.
Altogether the 16 million trips made on Whim, the roughly 100 000 messages from users, occasional deep dives like Whim Ride and our international segmentation tool form an understanding, not just of how to best serve customers today, but how to meet their expectations tomorrow. Maybe we should not compare data to oil. Data that matters is much more of a hybrid solution.