Personalised Product Recommendations
Real-time 1:1 recommendations across web, app and email driven by unified customer behaviour.
Connect every AI use case to the outcomes the business cares about.
Real-time 1:1 recommendations across web, app and email driven by unified customer behaviour.
Predict at-risk customers and trigger retention journeys with next-best offers.
Decision agent picks the best offer, channel and moment for each customer in real time.
Predict members likely to move tiers and trigger personalised nudges and challenges.
Learning-to-rank model improves relevance, synonyms and zero-result rescue.
Scan social, runway and competitor signals to surface emerging trends and gaps.
Generate per-customer subject lines, hero products and send-time at scale.
Generative video host runs always-on live shopping streams with personalised offers and Q&A.
Compose dynamic bundles by basket affinity, margin and stock to lift AOV without eroding margin.
Decision agent re-engages lapsed customers with optimal cadence, channel and incentive depth.
Conversational analytics over sales, space and cluster data to accelerate range reviews.
Generates on-brand copy, subject lines and creative variants across channels with guardrails.
Conversational stylist that builds baskets, suggests outfits and upsells across the catalog with live stock awareness.
Whispers next-best products, recent purchases and personalised talking points to associates serving high-value customers.
WhatsApp, SMS and social messaging assistant that takes orders, books appointments and recovers carts.
Autonomous merchandising agent that uses Xfuze's ML models to proactively alert and reorder stock based on recent and forecasted demand, independently evaluating and proposing replenishment and allocation strategies aligned with actual sales velocity and trends.
Launches hyper-personalised campaigns by identifying micro-segments from de-duplicated Single Customer Views and pushing tailored offers directly into marketing tools — shifting from passive analysis to proactive, revenue-driving engagement.
Detects lapsing customers and runs personalised, multi-step win-back journeys autonomously.
Bayesian MMM combined with multi-touch attribution to reallocate spend across channels with confidence intervals.
Real-time contextual bandit choosing the next offer, message or content for each customer across web, app and CRM.
Lets shoppers find products by photo, with attribute extraction feeding search, PDP and recommendations.
Autonomously triggers personalised recovery flows across email, SMS and onsite based on intent and inventory.
On-shelf availability and planogram compliance from in-store cameras and associate phone photos.