Algonomy's solution empowers businesses to craft tailored digital experiences that delight customers and foster repeat visits. It leverages Xen AI, a patented decisioning engine, to monitor shopper behavior in real-time and apply over 150 pre-built recommendation strategies. This enables precise cross-sell, upsell, and complete-the-bundle recommendations without manual intervention or concern for stock compatibility. The platform also allows non-technical users to build and test personalization strategies through a no-code interface. Additionally, it facilitates the creation, management, and delivery of personalized content and offers across various channels, utilizing pre-built templates and machine learning for automated optimization. Audience segments can be built, optimized, and streamed in real-time based on customer behavior, preferences, and journey stage, supporting personalized marketing campaigns and targeted advertising. Social proof messages are generated from real-time customer activity and catalog data to build shopper trust and confidence. Guided shopping experiences are created through interactive quizzes that combine explicit customer input with implicit behavioral data to generate relevant recommendations. The system also offers AI-powered stylists to present curated product ensembles based on shopper preferences and trends, aiming to increase average order value and repeat purchase rates. Product catalogs can be enriched using LLM algorithms to improve product discovery and customer insights. Algonomy emphasizes AI transparency, allowing visibility into decision-making rationale, and combines human and artificial intelligence for balanced optimization. It can personalize experiences even without historical behavioral data using DeepRecs™ technology and unifies online and offline data for a holistic user profile and hyper-personalization across channels.

Features & Benefits

• Real-time Behavioral Monitoring: Xen AI monitors shopper behavior to select optimal recommendation strategies for tailored interactions.
• No-Code Strategy Builder: Empowers non-technical users to easily build and test personalization strategies without data science team involvement.
• Automated Recommendations: Provides precise cross-sell, upsell, and complete-the-bundle recommendations, managing compatibility and stock.
• Omnichannel Content Delivery: Centralized dashboard for creating, managing, and delivering personalized content and offers across desktop, mobile, email, and call centers.
• AI-driven Optimization: Leverages machine learning for auto-optimization of performance and reduces manual A/B testing efforts.
• Audience Segmentation: Builds and optimizes audience segments automatically based on customer behavior, preferences, and journey stage for targeted campaigns.
• Social Proof Generation: Converts customer activity and catalog data into compelling social proof messages to build trust and improve conversions.
• Guided Shopping Experiences: Interactive quizzes combine explicit and implicit data to generate personalized recommendations and accelerate discovery.
• AI-Powered Stylist & Ensembles: Delivers curated product ensembles based on preferences and trends to increase average order value and repeat purchases.
• Catalog Enrichment with LLMs: Uses ChatGPT and LLM algorithms to enrich product catalogs with specific attributes, improving discovery and customer insights.
• AI Transparency and Auditability: Provides visibility into personalization performance and the rationale behind AI decisions.
• Hybrid Intelligence Approach: Balances machine learning optimization with business objectives through configurable weights and rules.
• Personalization Without Behavioral Data: DeepRecs™ technology uses image recognition and NLP for recommendations even without historical data.
• Unified User Profiles: Combines online and offline data for a unified, real-time user profile for hyper-personalization across channels.