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Fanplayr, a leader in online behavioral personalization for the past 10 years, announced it has added Product Recommendations to its menu of offerings. Fanplayr is a global leader in e-commerce behavioral data, using machine learning and AI.

Product Recommendation algorithms from Fanplayr

The addition of Product Recommendations is a benchmark in Fanplayr’s bid to offer fully integrated, comprehensive, real-time behavioral personalization for e-commerce

Fanplayr, a leader in online behavioral personalization for the past 10 years, announced it has added Product Recommendations to its menu of offerings. The addition of Product Recommendations is an intuitive next step in the development of Fanplayr’s fully integrated approach to behavior personalization and real-time responsiveness.

Fanplayr is an early adopter utilizing Recommendations AI through the Google(R) Cloud Platform.

Fanplayr has made Product Recommendations fast and easy to set up and launch. Recommendations are delivered in real time using their state-of-the-art AI and ranking models. In addition, the service is fully managed and scalable using their patented “Segmentation-as-a-Service.”

Fanplayr’s Product Recommendations service can be delivered in multiple locations – on a customer’s website, via email, web push notifications, and SMS – allowing for seamless integration into the customer stream. Algorithms offered currently for Recommendations include: “Others You May Like,” “Frequently Bought Together,” “Recommended for You” and “Recently Viewed.” These Recommendations can be combined with Fanplayr Smart Product Rankings based on views, carts, purchases and revenue.

“We are pleased to offer Product Recommendations to our customers,” says Simon Yencken, Founder and CEO of Fanplayr. “Only when you look at the behavior of an individual can you understand what they truly want and use that to transform e-commerce. Product Recommendations deliver a better experience for the individual by using AI to recommend other relevant products and services, and therefore provides significantly positive results for our customers.”

Early results have exceeded expectations. Branshes, a leading clothing e-retailer in Japan (a division of Aeon Group, the largest retailer in Asia), was among the first to try the new product. Their results showed CVR (purchase probability) increased by +153% and AOV (average order value) increased by +130% after utilizing Product Recommendations by Fanplayr.

“Our preliminary results exceeded all expectations,” says Rajiv Sunkara, co-founder and Chief Technology Officer at Fanplayr. “In a digital-first economy, behavioral personalization must replace the proverbial salesperson. Analyzing customer streams and adding product recommendations is an important step in reflecting what the consumers want and helping them find it.”

About Fanplayr

Fanplayr is a global leader in e-commerce behavioral data, using machine learning and AI to enable businesses to increase conversion rates and revenue, collect more leads, and retarget visitors with personalized recommendations during and after the shopping experience. Fanplayr is headquartered in Palo Alto, California with offices in New York, Buenos Aires, Mexico, Milan, London, Amsterdam, Melbourne and Tokyo, see: https://www.fanplayr.com/.

Media contact:
Kathie Gonzalez
kathie@percepture.com

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Image Caption: Product Recommendation algorithms from Fanplayr such as ‘Frequently Bought Together’ are easy to set up and launch.

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Related link: https://www.fanplayr.com/

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