All Press Releases for May 13, 2024

Ocurate shares insights into its advanced ML framework for Real-Time LTV

Ocurate increases ROAS by 15%+



    SAN FRANCISCO, CA, May 13, 2024 /24-7PressRelease/ -- Ocurate is excited to publish a new White Paper on its machine learning technology. Ocurate's ML for real-time LTV enables applying per-customer revenue predictions for ad bidding, transforming digital advertising by increasing ROAS by 15% and more.

This sophisticated framework utilizes a combination of the most granular, real-time event stream data capturing all minute customer interactions with the brands' websites, and advanced neural networks to dynamically predict customer value. The result is unprecedented precision and Machine Learning accuracy.

"Our team of skilled data scientists has been continuously advancing machine learning for individual-level LTV predictions, delivering value to our clients. By employing neural networks structured in innovative ways and processing the most predictive, granular type of high-dimensional event stream data, we've significantly enhanced model performance and set new industry standards.," said Giovanna Fernandes, Head of Ocurate ML.

The achieved precision is a necessary step in leveraging the predictions for ad bidding. And the end-to-end solution is proven to significantly enhance advertising ROAS by allowing campaigns across platforms like Google and Meta to set bids most efficiently and acquire customers at the ideal price point. The end result is a ROAS increase of at least 15% for some of the biggest D2C ecommerce companies.

"This solution means that D2C brands will add an additional $1.5M in revenues for every $10M generated from online ads. This is the largest revenue initiative for the majority of our customers, and a significant step toward profitability," says Ocurate's CEO and Co-Founder Tobias Konitzer.

For a deeper understanding of how our technology works, please visit: Ocurate Machine Learning Framework.

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Anand Sharma
Ocurate, Inc
San Francisco, CA
USA
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