Carwow is an e-commerce platform, enabling consumers to buy cars from franchise dealers. The company’s investors include venture firms Balderton Capital, Accel Partners, Episode 1 Ventures and Samos Investment, while last month it received £25m of investment from Mercedes-Benz’s parent company Daimler AG.
The organisation’s director of data, Tim Hesse, explains that Carwow’s aim is to disrupt a market which has not changed much in the last two decades.
“It’s still a non-transparent and bluntly awful experience for the customer to purchase a car, and this is the reason Carwow exists to bring more transparency and enable consumers to understand what car they need and find a great deal using great data,” he tells NS Tech.
The aim is to make it possible to not only find the perfect car, but also to receive a good service from the dealer while doing so. This means Carwow has to cater for the consumer as well as help the dealer network.
“The dealers need to understand what the customer wants, what stage of the enquiry they are at, what they can afford and how likely they are to buy a car in the next two weeks. Meanwhile, we need to ensure we give the customer the best experience, answering queries effectively and actually converting the customer into a purchase,” Hesse explains.
In order to be able to answer many of these questions, Hesse and his team rely on data that goes beyond what is traditionally used by many car dealerships, who usually rely on limited data such as the number of cars that have sold well and the number that haven’t.
“We have actual behavioural shopping data which is common in many other industries; so we can understand how people interact with certain cars, models or trims, whether they’re engaged more on certain stacks of cars or engine types, and what they switch to if they don’t end up progressing on a certain car,” Hesse says.
He believes this is unique to Carwow and helps manufacturers and dealerships better understand customers as Carwow can tell them that the reason their model wasn’t picked was probably because the customer has found a better finance contribution or they just have a more appealing spec level at that price.
The company captures the data between customers and dealers and records conversations through either its message platform or core platform.
Scaling up from scrappy
While Carwow can still be considered a start-up, it now has 220 employees and a presence in the UK, Germany and Spain. Hesse believes the company is going through a transitional stage, moving from a more scrappy work environment to a mature company.
“For data teams in start-ups it doesn’t matter if things scale initially, we just wanted to get some insightful information that we can use to make a decision today as this is hugely empowering for a data function. We didn’t care a lot about whether what we were doing was scalable and if it was a good infrastructure and if we could reuse it,” Hesse explains.
But now that the company is in a its scale-up phase, the mindset has shifted from being fast to being more strategic, meaning there is more thought put into how the infrastructure is built, and how access to data is provided.
The company had been a Tableau customer for a number of years, but Hesse says that it was only in the last year that Carwow has been able to fully exploit the software.
“Now we have access to relevant reporting, finding data is easier, users can interact with data directly and play with the data to get their own insights,” Hesse states.
As the company is in different levels of maturity in its three markets, it has also been easier with its business intelligence (BI) tools like Tableau to transfer learnings and insights across.
“We shifted to Snowflake a year ago which enabled us to scale much quicker, and it’s a lot easier to build a lot of infrastructure and scale it to another territory. The team in Spain thought it was amazing what we had built for them, but we had actually just built it for the UK and transferred it across,” Hesse says.
Now, his team is empowering the whole business to think more strategically and use the data tools on offer, rather than merely finding quick insights to base decisions on.
The combination of Tableau, Snowflake and Fivetran have helped the company to create a good baseline for its BI. Next, Hesse wants to focus more on the data science and machine learning part of his team, so that Carwow can build recommendation engines, and be smarter in how it attributes value to different marketing channels.