San Francisco, United States – Blueshift, the smart hub platform for intelligent customer engagement, announced at the company’s Engage 2022 conference the launch of the industry’s collection of 100+ pre-built AI recommendations recipes for marketers. The new recipes, together with Blueshift’s recommendations studio, provide unparalleled ease of use for marketers for hyper-personalised customer engagement, enabling them to recommend content, products, and offers that are based on each customer’s individual behavior, as well as the behavior of similar customers.
Today’s consumers demand personalisation across all engagement channels and interaction touch points, and the use of AI has become key for marketers to scale their efforts. In fact, studies show that marketing campaigns featuring AI recommendations are 116% more effective, driven by 22% higher click rates and 209% higher conversion rates. Over the last 12 months, marketers have hyper-personalised more than 10 billion messages using Blueshift’s recommendation studio, which is built using patented technology. Furthermore, Blueshift customers have reported significant business results from using recommendations, including 131% higher sales and 384% higher lead volumes.
“With today’s release of AI recommendations recipes, we are excited to bring accessible AI directly in the hands of marketers,” says Manyam Mallela, co-founder and chief AI officer at Blueshift. “We are empowering a new generation of marketers who are data artists, combining the art of marketing with the power of AI and data science.”
The new capabilities for AI recommendations recipes unveiled today empower marketers to:
- Get started quickly with 100+ pre-built AI marketing recipes: Marketers now have a great starting canvas, pre-loaded with configurations for common use cases like abandoned carts, newsletter feeds based on affinities, cross-merchandising based on the wisdom of the crowds, trending content or changes to catalogs, and more. These recipes can be easily edited to get the recommendations just right for each use case.
- Personalise each message using drag-and-drop simplicity: Once the recommendation scheme using out-of-the-box recommendation recipes have been built, marketers can use a newly released drag-and-drop interface to insert them into emails, SMS, push notifications, in-app messages, or any creatives for their campaigns. Additionally, it’s easy to suppress repetitive recommendations and to include seasonal and business promotions alongside predictive content.
- Analyse and optimise with advanced reporting: New in-depth reporting on advanced recommendation analytics enables marketers to optimise campaigns by using the best-performing recommendations, while also gaining visibility into which items are being recommended to each user and which ones users are engaging with.
Retailers, ecommerce providers, and digital media and over-the-top (OTT) companies are especially poised to benefit from these new capabilities provided by AI recommendations recipes. For instance, retailers can design customer journeys with highly relevant content and recommendations in real time based on the shopper’s affinities, search and browse activity and purchase history. Streaming service providers can use advanced AI to precisely match millions of viewers with hundreds of thousands of media content catalog items and engage them with daily content feeds that are auto optimised based on prior activity.
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