The Czech company Carvago operates a very successful online marketplace for used cars from all over Europe. It already offers around 1 million cars to customers from the Czech Republic, Slovakia and Germany. Other European countries are also lined up in the near future.
In order to achieve these goals at Carvago, they need to find used cars offered throughout Europe every day and include them in their offer.
In order for their customers to be able to find the best offer for the car they are looking for at any time, the database has to be constantly updated with newly offered cars on all portals in Europe. At the same time, their dealers often give insufficient data on the car being offered or place the ad on several portals at the same time.
Carvago had to not only obtain new ads, but also eliminate duplicates, correct erroneous information and classify all offers on the basis of an exhaustive catalogue of car models, including key parameters such as engine, transmission type, drivetrain, etc.
The main requirements for the solution were:
We carried out a detailed analysis of the existing sources of information about cars and advertisements and identified:
Interesting fact: 10 car models cover 37% of the market.
Revolt BI’s solution for Carvago includes several components:
As a data warehouse and DevOps platform, we chose Keboola, with data storage on Snowflake. The main reasons for this decisions were excellent computing power, integration of all necessary services, diagnostics of all processes and the many other benefits of Keboola solution.
For automatic image recognition, we use deep learning – a convolutional neural network (CNN) that, thanks to a set of algorithms and technologies, is able to identify objects and many other types of elements in an image and draw conclusions by analysing them at low cost. Our solution is also able to correct incorrect information – e.g. it recognises from a photo of a car that it is a combi, even if the advertisement states that it is a VAN or MPV. We are even able to automatically recognise the type of air conditioning from the interior photo!
Interesting fact: 2,000 photos are needed for quality training of the neural network for a single model.
We perform business analytics using Tableau, as no other visualization tool would be able to easily handle such widely differing views of many aspects of Carvago’s operation, not only for the company itself, but also for its business partners.
Thanks to its cooperation with Revol BI, Carvago has obtained unique and always up-to-date data on European used cars, including the relevant parameters and price of the car, as well as analytical tools for their commercial use.
The business analytics from Revolt BI allow the Carvago sales department and its customers to make data-based decisions, such as targeting the offer to the vender according to their strong segments or a detailed comparison of the offered cars across advertising servers.
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