Tourlane case study
How Tourlane connected their data dots to get the single customer view
Tourlane offers customers hyper-personalized travel experiences, tailor-made for them based on their individual interests by teams of experienced specialists.
- Tourlane gained a single view of their customers by stitching together and centralizing customer data from multiple sources, including on and offline touchpoints
- With added visibility, Tourlane can predict and manage the balance between supply and customer demand, maximizing the efficiency of their tailored services
- Access to their raw, event-level data enabled Tourlane to understand their complex customer journey
- Using Snowplow has helped Tourlane embed a data-tracking mindset into their culture
Tourlane’s GA-based, out-of-the-box analytics was hindering them from evolving to a data-first, tracking mindset that the company needed. It was simply impossible to join the dots between individual customers and the page views, impressions and conversions they were tracking. They also had no way to match up online data with offline customer events such as phone calls. Eventually, Tourlane decided they needed an alternative solution - either something they could build themselves or pay for - to get granular data to drive A/B tests, attribute marketing efforts and predict customer intent. It was important that Tourlane predict what customers intended to buy in order to balance supply and demand appropriately.
With Snowplow, Tourlane were finally able to centralize data from all their touchpoints and piece together a single view of their customers. Tourlane’s data team could move away from generic, limited data tracking to user-specific insights and a greater understanding of their customer’s behavior. In turn, this meant Tourlane could better predict customer intent, optimize supply and demand and bring data-tracking into the center of the business.
“Snowplow has been helping us centralize our data and build the single customer view since day one. As we get closer to pinpointing precisely, for example, the booking value of a particular segment, and more complex data analysis, Snowplow will continue to be what we need.”
Kevin James Parks,
Data Engineer, Tourlane