The Client Story
The client, established in 2015, is a major player in the international vehicle rental industry, known for their extensive fleet and customer-focused services. They operate thousands of vehicles across multiple countries, constantly updating their fleet to maintain market relevance and customer satisfaction.
| Industry: | Logistics |
|---|---|
| Cooperation: | Since 2023 |
| Location: | Europe |
The client increased the average truck selling price by 6%
Reduced expenses on new trucks purchases by 14%
How to automatically determine the optimal market price for a truck?
The price depends on numerous factors, including the year, make, model, the presence and model of a cooling system, and the vehicle’s condition and any damage.
The client requires daily market price data for their several thousand vehicles to determine when and at what price they can sell an existing truck. Similarly, when they need to buy a new truck, they need to find the best option with the right cost and condition.
AI-assisted vehicle pricing
We developed a platform collecting data daily from 18 major ad aggregators like via-mobilis.com, autoline.info, and mobile.de. Additionally, we created an AI-based analytical system using truck photos to identify unlisted ad parameters.
Analysing different damage types we can determine how they affect the pricing. Similar we study price divitations based on any add-ons to trucks or trailers, such as coolers, refregirators, trailers for animals etc.
In the UI that has been developed for data management, the client can study ads for the same truck from different countries, find the best option. They can analyze historical price changes, as well as add or remove trucks that need to be monitored.
We built a platform analyzing truck ads from 18 major marketplaces, allowing our client to compare options, study historical prices, and make more profitable deals.
Increased visibility over the fleet price
The client maintains a fleet of over 1000 trucks and trailers, and the main focus of the software was on data quality. We have built a robust data quality management system to react to any data deviations, gaps, or abnormal spikes. Each correctly made decision could save thousands of euros per item sold or purchased, and vice versa.
As a result, using the data collection and analysis software, the client was able to increase their selling prices by 6% and reduce the price of newly purchased trucks by 14%.
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