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AI Product Recommendations

AI Product Recommendations

Adobe Sensei-powered recommendation blocks that show each shopper the products they're most likely to buy — not the same bestseller list everyone else sees.
Increase Your Average Order Value
26%
Of revenue at top retailers driven by recommendation engines
10–30%
Typical AOV increase after AI recommendation implementation
6
Recommendation placement types across homepage, PDP, cart, and email
0
Manual rule maintenance once the model is trained on your data
Recommendation Types We Implement
Every placement serves a different intent — we choose the right algorithm for each position.
Customers Also Bought
Collaborative filtering based on real purchase co-occurrence. Shows products that buyers of this item consistently add to the same order.
Viewed This, Bought That
Bridges the browse-to-buy gap — shows the products shoppers actually convert on after viewing the current PDP.
More Like This
Content-based similarity using product attributes, category, price band, and visual features for catalogue browsing pages.
Homepage Personalisation
First-visit and returning-visitor recommendation blocks personalised to session behaviour and purchase history.
Cart Cross-Sell
High-margin complements surfaced in the cart drawer, tuned to avoid recommending what the shopper already has.
Email & Push Triggers
Post-browse and post-purchase recommendation sequences delivered via your ESP — personalised per recipient, not per campaign.
How We Implement
01
Data Audit
Review your order history volume, catalogue size, and existing analytics setup. Adobe Sensei requires sufficient behavioural data — we assess readiness before committing to an approach.
02
Configuration
Sensei Product Recommendations module installed and connected to your catalogue and behaviour data. Placement strategy agreed for each page template.
03
A/B Testing
Each recommendation block launched as an A/B test against the existing experience (manual rule set or empty slot) so the revenue impact is measured, not assumed.
04
Optimisation
Monthly review of click-through and conversion data per placement. Algorithm type adjusted where data suggests a different recommendation strategy would perform better.
Related AI Services
AI Search & Discovery
Connect search intent signals to power smarter recommendation ranking.
Personalisation
Extend recommendations into dynamic pricing, promotions, and segmented campaigns.
Adobe SaaS Services
Recommendations is one of four SaaS modules — see the full Adobe Commerce SaaS stack.
Let's build something extraordinary
Let's Build Something Extraordinary
Whether you're launching your first online store or scaling a global brand, we're here to help you succeed in the digital marketplace.
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