Algonomy, the leader in Algorithmic Customer Engagement (ACE) solutions, announced an array of new and enhanced capabilities in their latest Spring ’21 Release. The new release is specifically designed for Retailers and Brands who are in a post-pandemic recovery cycle, with a unified platform for digital customer engagement that integrates data from supply to demand across the value chain with algorithmic decisioning and omnichannel orchestration.

The release features numerous powerful capabilities like composite AI frameworks, no-code ML frameworks, Visual AI algorithms, greater control and governance over customer data, and better orchestration abilities across marketing, commerce and merchandising.

“The digital-first era is all about staging relevant experiences across the entire customer journey, and extend personalized interactions to all customer touchpoints, both inbound and outbound”, says Sarath Jarugula, Chief Product Officer at Algonomy, “In this release, Algonomy customers can continue to better leverage their technology investments across the enterprise, to improve on their metrics for customer engagement, conversion and loyalty.”

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Key capabilities in Algonomy’s Spring ’21 Release:

Algonomy Personalization Suite now features the following:

• New OOTB Connectors: Algonomy Connect (now in GA) can help Brands leverage their commerce investments with Shopify Plus, VTEX, Adobe Magento, SAP Hybris, SFDC Demandware and more to sync product catalogs, inventory, pricing to keep them always updated, with our unique real-time streaming catalog integration.
• DeepRecs Visual AI enhancements offer deep learning to replicate store-like personal experience on digital commerce properties, helping shoppers can find visually similar products and get complete-the-look recommendations based on product images and without the need for any behavioral data.
• Configurable Strategies features additional controls to apply category diversity to strategies such as Top Sellers, New Arrivals, Attribute Top Sellers, Best Offers and Category and Brand Affinity. A shopper’s affinity to categories or brands can be used as the seed, so the resulting recommendations match their affinities.
• Contact Center Personalization (EA only) provides online shopper behavior, intent signals, search data, affinities, cart contents as well as past purchases to sales associates and agents for personalized interaction and assistance.
• Social Proofing (EA only) engages shoppers using real-time view and purchase data, provides urgency messaging on digital commerce properties, resulting in immediate lift in conversion rates and reduced abandonments.

Customer Analytics now features an all new Data Studio that offers data scientists and analysts security-controlled access to full enterprise customer data to build models, perform exploratory analyses, and build dashboards in an easy to use interface.

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Customer Journey Orchestration (CJO) enhancements in online and offline journey automation, and an extended set of Journey Analytics capabilities.

• Universal Control Group allows creation of a program level control group to measure effectiveness of multiple campaigns and multiple journeys across longer-term marketing objectives.
• The platform features a new Criteo Integration enabling marketers to push automated dynamic and personalized ads to known customers across channels.

Merchandise Planning and Analytics features:

• New Size-pack Assortment Planning for multiple size strategies – single and multiple size packs, eaches, fill-in packs, and hybrid size planning. The enhancements feature granular store recommendations, greater user control and autoscaling, modeling for new stores and new plan classes without history, and enhanced analytics.
• Style Intelligence uses Visual AI to rank and recommend fashion products/trends and integrates with the attributes creating the assortment plan.
• Product Lifecycle Pricing offers UI enhancement and features a wider set of pricing and markdown strategies. New updates on cross-price elasticity and offer recommendations add to the depth of fashion merchandising analytics and algorithmic decisioning abilities.