Recommai case study - Neural Lab

EMPOWERING PREMIER NEWS PORTAL IN SINGAPORE

Automated content personalisation

Recommai improved the reading experience with seamless, personalised content. Every reader benefits, even those browsing anonymously.

REAL-TIME INSIGHTS

ENHANCED ENGAGEMENT

CONTENT VERSATILITY

THE STRUGGLE TO MATCH USERS WITH WHAT MATTERS

Too much manual work, too little relevance

Content and product platforms had to give users relevant choices at scale but relied too much on manual work. Without automation and data-driven insights, the experience felt generic.

Readers kept seeing repeated articles. App users saw the same products. This caused high exit and bounce rates, low engagement, and lost revenue.

The challenge was to match the right item to the right user at the right time without manual effort.

CONTENT PERSONALISATION

Data-driven personalisation with auto A/B testing

Recommai tracks reader behaviour data in real time. It analyses actions continuously and places web content based on those patterns. This delivers personalised recommendations without manual curation.

A/B testing shows which title works best. Recommai continuously learns from results and refines the experience for every reader.

Lower bounce, higher engagement

With our solution, a leading news portal in Singapore dropped bounce rate from 68% to 37% on pages served through the recommendation engine.

Reader retention and click-through rates increased. Ad revenue also grew, supported by stronger insights into reader behaviour.

68% to 37%

reduced bounce rate

35% to 18%

reduced exit rate

1.5% to 13%

increased CTR

+5 mln

views per month

PRODUCT PERSONALISATION

Turning referrals into results with personalised products

Recommai supports an Australian referral app with automated product recommendations. Our engine analyses user behaviour, creates strategies, and selects the most effective ones.

This delivered precise, tailored suggestions without manual effort.