Auto Trader unlocks AI powered retailing with launch of Co-Driver

Auto Trader has launched Co-Driver, a suite of solutions powered by advanced artificial intelligence (AI) and machine learning, which is set to revolutionise automotive retailing. Harnessing Auto Trader’s vehicle data and consumer insights, as well as over a decade of investment, all of Co-Driver’s solutions will be focused on alleviating retailer pain points and driving retailing performance. 

The first release of a multi-year pipeline of AI powered tools will give retailers direct access to Auto Trader’s wealth of data and insights. It will also significantly reduce the time and effort required to create detailed, highly compelling, and high performing used car and van listings, shortening the average time taken from circa 28 mins to just a click of a button. 

As of this month, all retailers will have access to the first AI powered feature of Co-Driver, Smart Image Management. It utilises Auto Trader’s in-depth consumer data to instantly arrange vehicle images into the optimum sequence according to car buyer preferences. What’s more, AI image recognition will automatically categorise them, as well as flag missing imagery, to ensure every advert is as eye-catching as possible to discerning buyers. Auto Trader research shows that this is key, as buyers spend almost twice as much time engaging with vehicles that have the greatest variety of images, and the more time a buyer spends engaging with an advert, the more likely they are to buy.

It will be followed in the early new year with AI Generated Descriptions, which enables retailers to showcase their vehicles quicker with highly engaging, and instantly generated descriptions. Co-Driver is powered by Auto Trader Intelligence, which is underpinned by over 80 million cross platform visits and circa 619 million combined search minutes every month, as well as around 1.6 million daily vehicle observations. It also includes comprehensive VIN specification details sourced directly from leading manufacturers, ensuring the vehicle is described and positioned in the most accurate and appealing way for potential car buyers, with all the details they really care about, all with the click of a button.

 It will be released alongside the third feature in the initial wave of Co-Driver releases, Key Selling Points, which uses the same powerful combination of AI driven Auto Trader Intelligence to automatically highlight the most distinctive characteristics and specifications of the car. This will include those features unique to that specific model, derivative, and even individual car, that would make it more attractive to potential buyers.

To ensure all retailers can benefit from this revolutionary technology, the full range of Co-Driver’s features will be available as part of all used car and van advertising packages. They’ll be accessible through Auto Trader Portal accounts, and for those retailers utilising Auto Trader’s powerful suite of API solutions, Auto Trader Connect, they can also be seamlessly integrated into their chosen systems through their third-party technology provider.

“As one of the UK’s largest technology companies, we’ve long recognised the huge potential AI has in making retailers’ operations more profitable and more efficient, and have been investing heavily in it for over a decade. It already sits at the heart of many of our most powerful tools and solutions, but Co-Driver marks a massive leap forward in how AI can enhance retailing performance. These initial solutions, as well as all future Co-Driver releases, will not only alleviate many of the challenges facing our partners today, but will help them deliver retailing excellence.”

Developed by Auto Trader’s in-house team of over 400 data scientists and engineers, Co-Driver represents the scale of its data and technology capabilities and marks the pinnacle of more than a decade of investment in AI. Retailers are already benefitting from this investment, using AI and machine learning tools to make more profitable sourcing and stocking decisions, utilising Market Health and Retail Rating metrics to determine potential returns for stock at different prices.