IBM Watson® Advertising Accelerator delivers personalized, high-performing creative at scale by harnessing AI to predict the optimal combination of creative elements based on key signals like consumer reaction, weather and time of day.

An industry disrupted struggles to connect with new buyers

The recent and rapid increase in consumer demand for electric vehicles (EVs) could go down as one the biggest milestones in the history of the automobile industry.

The International Energy Agency reported that EV sales doubled from 2020 to 2021 (link resides outside of ibm.com). Sales continued to rise in the first quarter of 2022, with two million EVs sold—up 75% from the same period in 2021. As a result, manufacturers are racing to capture this emerging market.

And with good reason. An IBM survey found that 48% of consumers are loyal to vehicle brands and tend to stick with them. That means winning EV consumers now will pay dividends for years to come.

But increasing data regulations and privacy concerns make it more challenging than ever to effectively reach consumers with ads that are tailored for their tastes and preferences.

That’s why many brands are looking for technologies that can customize ad experiences to different audience segments without needing cookies or personal identifiers.

Increases conversion rates by

118%
versus non-Accelerator impressions

Improves cost per model landing page visit by

271%
versus benchmark

Driving performance with dynamic creative experiences

Luxury car manufacturer Audi AG wanted to increase awareness and consideration for its new electric e-tron vehicle by understanding which creative elements in ads would resonate best with potential electric vehicle buyers.

Audi implemented IBM Watson Advertising Accelerator, a dynamic creative optimization technology solution that uses AI to rapidly and continuously learn which messages, images, videos and even colors will best resonate with each audience based on not only how consumers react, but also on other key signals like designated market area (DMA), device type and time of day.

The solution uses rapid in-market data processing, model creation and training to identify hidden engagement patterns across audiences and automatically cluster similar users together in ways that brands may not have previously anticipated.

Once clusters have been identified, unique ad experiences are served to each group based on how likely they are to increase engagement and action among each audience, ultimately increasing conversions. Performance is measured in real time to improve predictions throughout the campaign.

Since implementation, this campaign has helped Audi:

  • Increase conversion rates by 118% versus non-Accelerator impressions
  • Improve cost per model landing page visit by 271% versus benchmark and costs per inventory search by 320% versus benchmark
  • Serve 116 creative variations across 36.7 million impressions

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Produced in the United States of America, November 2022.

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