15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform
15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform
15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform
15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform
15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform
15+Years Trading
£3bnRevenue Processed
75Team Size
B2C & B2BExperience
Strategy-ledRetainer
1 WeekDiscovery
< 6 MonthsReplatform

Magento 2.3.5 Released with Adobe Sensei Product Recommendations

Major update introduces AI-powered product recommendations to Adobe Commerce merchants.

4 min
Magento 2.3.5 Released with Adobe Sensei Product Recommendations

Magento 2.3.5 Released with Adobe Sensei Product Recommendations

Adobe has released Magento 2.3.5, a major version update that brings AI-powered product recommendations directly into Adobe Commerce. The inclusion of Adobe Sensei-powered intelligence represents a watershed moment for the platform, democratising access to sophisticated personalisation capabilities that can meaningfully impact revenue and customer experience.

Adobe Sensei Product Recommendations

The headline feature is undoubtedly the integration of Adobe Sensei product recommendations. Rather than relying on simple rules-based logic, merchants now benefit from machine learning models that understand complex customer behaviour patterns. The system analyses purchasing history, browsing behaviour, seasonal trends, and demographic signals to deliver recommendations that genuinely resonate with individual customers.

How It Works

The system operates with minimal configuration. Merchants enable the feature, and Sensei immediately begins learning from storefront data. Within days, recommendation quality improves noticeably as the system accumulates behavioural signals. The engine constantly adapts, ensuring that recommendations remain relevant as shopping patterns evolve throughout the year.

Business Impact

Early adoption data suggests meaningful improvements in key metrics. Average order values increase as customers discover complementary products they genuinely want. Conversion rates improve when recommended products match customer intent. Customer satisfaction rises when recommendations feel personal and relevant rather than generic or misaligned.

Additional Enhancements

Performance Improvements

Version 2.3.5 includes optimisations to database query performance, particularly for large catalogues. Merchants running hundreds of thousands of SKUs should experience noticeably faster page load times, faster search response times, and improved overall platform responsiveness.

Security Refinements

Continuous security improvements ensure the platform remains protected against evolving threats. Regular security patching has always been essential in e-commerce; version 2.3.5 maintains this commitment with multiple vulnerability fixes and hardened authentication mechanisms.

Developer Experience

GraphQL API enhancements provide developers greater flexibility when building custom experiences. Improved extension points and cleaner integration paths make it easier for agencies to build sophisticated customisations without forking core platform code.

Strategic Significance

Magento 2.3.5 represents a clear statement: Adobe is embedding intelligence into the core platform. Merchants no longer need to choose between complexity and sophistication. Modern, intelligent commerce capabilities are becoming standard rather than premium features.

For merchants at any scale, the release presents an opportunity to enhance customer experience and drive incremental revenue with minimal effort. Early adopters of Sensei recommendations gain competitive advantages in an increasingly personalisation-driven marketplace where customers expect experiences tailored to their individual preferences and behaviours.

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