Motorway

Motorway: Transforming how we buy and sell used cars with AI

Google Cloud Results
  • From several months to several days to productionize ML models from concept to customer

  • Using VertexAI, >80% of Motorway’s ML models make it to production

  • 94.7% accurate document validation using Gemini 1.5 Pro under-the-hood

Used car marketplace Motorway is harnessing the power of AI to build pricing, computer vision and personalisation capabilities that seamlessly brings buyers and sellers closer together online. Since pivoting to an AI-first strategy with Google Cloud at its core, Motorway has been productionizing use cases quicker than ever and launching industry-first features to enhance customer experience and disrupt the used car marketplace.

While buying and selling used cars remains largely an offline, bureaucratic, and lengthy endeavor, Motorway proves that there’s another way. With a network of more than 5,000 professional car dealers bidding directly on its platform to acquire the best used car stock, Motorway enables car owners to sell their vehicles from the comfort of their homes for great prices in as little as 24 hours. To make this innovative customer experience possible and bring its industry-first ideas to life, the company selected Google Cloud in 2021. 

The company now uses Google Cloud AI capabilities to provide instant, accurate car valuations for potential sellers and show registered car dealers which vehicles on Motorway’s platform are most relevant to their businesses. Internally, it uses AI to streamline complex, tedious, and time-consuming document validation processes, enabling agents to dedicate more time to valuable customer-facing interactions.

We wanted to use AI and ML to make our workloads and user journey as effortless as possible, and that led us to Google Cloud since its data science stack is cutting-edge. Our priority was to improve our pricing estimations and Google Cloud provided various tools to test our ideas.

Will McCoull

Director of Engineering - Data, AI and Platform Enablement, Motorway

A new way to value used cars in just a few clicks

Within six months of being on Google Cloud, Motorway entered the Google for Startups Cloud Program. This unlocked access to training, consultancies, and support in the development of its pricing tool, named Real-Time Price Machine (RPM). 

Now the company develops its own ML models on Vertex AI to fine-tune pricing estimations that take into account all the nuances that might affect a vehicle’s valuation. This includes analyzing information provided by the car seller—such as the vehicle’s make, mileage, service history, and defects—coupled with market research on the supply and demand for each vehicle at the moment of valuation. Additionally, Motorway uses Vertex AI endpoints to incorporate real-time data from the previous day’s auction to understand the current interest of the car dealers on its platform and how much that vehicle is likely to achieve in auction.

“Each used car has a unique story and circumstances, making it traditionally difficult to estimate their value with accuracy. But for dealers on our platform, who are working to make a margin on each sale, estimating the price by even just 1% too high or too low can have a huge impact. To tackle this, we use advanced machine learning techniques that consider the broader market, individual vehicle details, and our own marketplace dynamics, allowing us to provide accurate valuations and ensuring the best possible outcome for both our sellers and buyers,” explains Ben Jones, Head of AI & ML at Motorway.

The ML model powered by Vertex AI made us 2% in additional revenue in 2023, and is on track to deliver 15%-17% in 2024. We think there is still more gain to be had as we make it even more accurate.

Ben Jones

Head of AI & ML, Motorway

Since launch in 2021, the RPM vehicle-pricing tool has served approximately 8 million valuations to UK customers, giving car sellers an instant picture of their vehicle’s value on Motorway’s landing page. All they have to do is input their car registration plate and mileage to see—in one click—what their used vehicle would earn in auction at that moment. Based on this price, the user can decide to start a profile and go ahead with the online sale or not. Because the results are specific to current market conditions, the user can also choose to try again another day.

“Our RPM tool is designed to give customers an indicative and transparent view of how much their vehicles are worth at each given moment,” says Will McCoull, Director of Engineering for Data, AI and Platform Enablement at Motorway. “We’re using AI to foster trust by shining a light on what cars are really worth based on current, realistic market values.” 

Motorway acts as a neutral intermediary between car sellers and car dealers, while de-risking the process for car dealers by providing as much information about each vehicle as possible. Aside from supporting this convenient and fast process for platform users, the RPM tool has increased pricing accuracy, aligning expectations and fostering trust between car sellers and car dealers and improving business outcomes for Motorway.

Automating document validation for end-to-end car sale support

Anyone who owns a car knows the importance of keeping it in check, but did you know that a full service history can influence a vehicle’s worth by up to 20%? However, sorting through the service history documentation of used cars can be a daunting task and automating this process is equally difficult. That’s because vehicle service history data is unstructured, comprising invoices, log books, and digital records, with minimal to no standardization. Further complicating matters, much of it’s handwritten, in a haphazard fashion, with stamps that frequently overlay text. For Motorway, this presented the perfect opportunity to apply AI to the tangled mess of data that car sellers upload to its platform. 

“We use Gemini 1.5 on Vertex AI to make sense of the chaos,” says Jones. “It extracts text from digitized service history papers, classifies various types of documents, extracts service events, and presents it all in an organized table.” Having this organized, accurate information on display makes it easier for car dealers to trust that a vehicle is in good condition.

Vehicle documentation is the most complicated document-processing workflow to automate that I’ve seen (doctor’s handwritten notes aside). With Google Cloud, we’ve significantly streamlined a tedious, difficult task for our agents, delivered a more streamlined customer experience for our sellers and a more trusted platform for our dealers. It’s a win-win.

Ben Jones

Head of AI & ML, Motorway

When that’s not the case, Gemini flags to Motorway when the company needs to follow up with a car seller for more information, or if something doesn’t add up. “Before Gemini— which uses human-like reasoning to differentiate between handwriting, text, images, and other relevant information—this would have been impossible to automate,” Jones adds.

When selecting the right solution to support this process, Motorway benchmarked Gemini against other options by testing them with examples of documents that car sellers might upload to Motorway’s platform. For example, a receipt for an annual vehicle roadworthiness test required in the UK doesn’t qualify as service history evidence, but an invoice might qualify if it specifies that it charged the vehicle’s owner for a service event. “In the same way a human might, Gemini was able to pick on those nuances and produce results that are 94.7% accurate, compared to 78-88% from other leading generative AI providers,” says Jones.

Additionally, because this AI-powered solution is completely scalable, Motorway can continue to expand the business to accommodate more car sellers on its platform without overloading its team. Motorway’s human agents are then able to focus on value-added tasks, such as reaching out to platform users who might need support in selling their car, proactively elevating the company’s services to its five-star standards.

Deploying more ML models from scratch, 4x faster

As an AI/ML expert, Jones notes that pushing ML models to production is traditionally challenging. In fact, it’s common for companies to spend multiple months working on something that often struggles to see the light of day. “It’s commonly known in the industry that typically fewer than 20% of machine learning models make it to production,” he says. However, that’s not the case at Motorway. Since establishing its current technology and processes, more than 80% of Motorway’s ML projects make it to production, which means Jones’ team can launch new customer-facing features faster, and keep current ones up to date and fully optimized. 

And speaking of new customer features, Motorway is currently developing the next iteration of its Intelligent Vehicle Discovery tools for car dealers using its platform. This solves a challenge that’s particular to Motorway, compared to other online marketplaces: “Unlike ecommerce websites that list recurring products, our auction platform has entirely new stock every day. Since we never see the same vehicle twice, it’s difficult to use traditional recommendation techniques to learn what is useful and relevant to a user based on their interactions with vehicles listed on our page,” Jones explains. 

To solve this, his team is developing a bespoke personalisation engine to help car dealers find vehicles that match their interests by using criteria such as mileage, condition, age, and price, as well as make-model, on the Motorway platform. Additionally, more recommendation features are on the horizon for Motorway users, such as the ability to browse through similar, related vehicles to the ones they’re interested in, across similar makes or manufacturers.

To provide this experience for its platform users, Motorway is exploring Cloud Functions and Batch for training Motorway’s ML models, looking across millions of user interactions to identify which users are likely to click on which vehicles. The team runs the results with Cloud Scheduler and uses Pub/Sub to identify when these matches are complete.

Artifact Registry and BigQuery store all that data. Meanwhile, another vector-specific database provisioned by Google Cloud stores vehicle vectors used to identify which vehicles are similar to one another according to relevant criteria for car dealers. “With generative AI, we augment those vectors using embeddings from LLMs to really capture dealers’ interests and how they’re interacting with different kinds of vehicles. Finally, we then use Gemini to quantify the performance of our model for each of our dealers at scale,” Jones explains.

With well-established internal MLOps capabilities, or as Jones puts it, “the ability to do things better and faster,” Motorway is looking forward to launching even more exciting technologies, transforming the way we all buy and sell used cars.

It feels like we’ve already accomplished a lot and at the same time we haven’t yet scratched the surface of what we want to do for people buying and selling used cars online. From rearchitecting our user profiling journey to upskilling our team on new-wave AI with support from Google Cloud, we still have a long and exciting road ahead.

Will McCoull

Director of Engineering - Data, AI and Platform Enablement, Motorway

Motorway started in 2017 with a vision to build a better car market for everyone, harnessing the power of technology to deliver an amazing experience. They help everyone to quickly and easily sell their car for the best price from the comfort of home, using only a phone.

Industry: Technology

Location: UK

Products: Gemini 1.5, Vertex AI, Artifact Registry, Batch, BigQuery, Cloud Functions, Cloud Scheduler, Pub/Sub

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