Auto Trader builds a Composable CDP and increases engagement for new car buyers by 20%

The Results

• 20% increase in engagement for new car buyers
• Engineers have automated data syncs to Braze
• Lifecycle marketing campaigns are personalized based on individual session activity
• Better alignment between marketing and engineering teams
• Marketers can build custom audiences without requesting engineering resources
• Composable CDP architecture that eradicates vendor lock-in

The Challenge

Buying a car is an important purchase but also an infrequent one. On average, consumers are only in the market to buy a car every three years. Engaging with individuals with high buying intent is extremely valuable, and access to rich behavioral data is essential for Auto Trader to offer the best buying experience possible.

We wanted to make sure that we could offer the best platform experience to as many of our consumers as possible.

Darren Haken

Head of Engineering

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Auto Trader

Typically an option for this solution would be to go for a traditional customer data platform (CDP), but Auto Trader didn’t want the vendor lock-in that it would cause. So, they went down a different route, going for a Composable CDP architecture.

The Solution

From the start, Auto Trader wanted to build a composable ecosystem where it could easily interchange parts to keep up with the rapidly changing data ecosystem.

Using a composable technology stack lets us easily make changes and democratize our data to address our business needs.

Darren Haken

Head of Engineering

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Auto Trader

With an advanced data stack in place and all of its data already transformed in BigQuery, Auto Trader didn’t want to adopt an off-the-shelf CDP solution and move data out of its own cloud environment.

We evaluated CDPs, but they are expensive black boxes that are extremely technical, and they don’t always play nicely with other tools. Your entire organization needs to be really good with data to get value out of them

Darren Haken

Head of Engineering

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Auto Trader

Snowplow

Auto Trader chose Snowplow as the enabling technology to build trust and credibility by capturing, validating and delivering AI-ready data in real-time to its data warehouse BigQuery. The engineering team then stitches this behavioral data together with new columns around predictions, observations, and relevant business attributes like propensity to buy.

Behavioral data is the best indicator of intent. We don’t want to track stuff just for the sake of it. We’re more interested in summarizing behavior and using that to draw conclusions about customer intent.

Paul Nunnerley

Technical Lead

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Auto Trader

With Snowplow powering all of these new insights in BigQuery, the next logical step was to adopt a CDP (customer data platform) so that the marketing team could activate this data and personalize the experiences of each user.

People only buy a car every few years, and we might only see them for a single session, so we need to be able to personalize at the session level. Using Snowplow gives us access to the first-party data we need and helps us format our data and decouple ourselves from a locked-in solution.

Darren Haken

Head of Engineering

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Auto Trader

Hightouch

In search of a technology that would facilitate these needs, Auto Trader discovered Reverse ETL and turned to Hightouch. Auto Trader uses Hightouch to sync custom data models and audience segments created in BigQuery to Braze for lifecycle marketing.

Having Hightouch in place helps the data team optimize their time more effectively because they’re not having to spend it building and maintaining pipelines.

We didn’t want to write our own integration code for every tool, we needed to send data. Hightouch eliminates this problem, and we don’t have to worry about constant API changes. Hightouch Audiences lets our marketing team take ownership.

Darren Haken

Head of Engineering

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Auto Trader

Using Hightouch, Auto Trader can sync custom data models and audience segments created in BigQuery directly to Braze in near real-time. The marketing team can then personalize additional lifecycle marketing campaigns across previously inaccessible touchpoints like push notifications, email, and SMS. The marketing team can build custom audiences without ever requesting additional engineering resources.

Braze

With Hightouch syncing Snowplow data to Braze in near real-time, the marketing team can personalize additional lifecycle marketing campaigns across previously inaccessible touchpoints like push notifications and SMS based on individual session activity. For example, personalizing to new car buyers led to a 20% increase in engagement.

The exciting part is that we now personalize everything we do. With Braze, our marketing team is able to ask deeper questions and have deeper conversations.

Darren Haken

Head of Engineering

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Auto Trader

What’s Next

Implementing a Composable CDP through Snowplow, Hightouch, and Braze has given Auto Trader’s engineering and marketing teams better alignment, and there’s never been more productivity between the two teams.

I’ve never seen engineers and marketing people talk to each other as much as they are right now. All of our objectives are goal-oriented and outcome-oriented now. Access to first-party data has made our data engineers have more empathy for our marketers, and our marketers are now more willing to provide insight into the campaigns they are running.

Darren Haken

Head of Engineering

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Auto Trader

As the feedback loop continues to develop between Snowplow, and these tools, the experiences that Auto Trader can offer its users will only continue to expand and improve. With the “best in breed” technologies in place, the company can solve more and more use cases around Data Activation.

We’ve just touched the surface with Hightouch, Snowplow, and Braze, so I am super excited to see what’s possible.

Darren Haken

Head of Engineering

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Auto Trader