thanks for your advice
Topic summary
A store owner seeks to improve their 2.5% click-through rate on product recommendations by replacing generic “Bestsellers” displays with personalized suggestions based on customer browsing and purchase history. They specifically want an app with advanced algorithms, seamless theme integration, and A/B testing capabilities.
Recommended apps include:
- LimeSpot Personalizer – AI-driven with A/B testing support
- Rebuy Smart Personalization – Strong for upselling/cross-selling and cart-page recommendations
- Wiser – Multiple recommendation types with detailed analytics
- Glood.ai – AI-powered with A/B testing
- Recom.ai – Real-time adaptive suggestions
- ConvertWise – Claims up to 30% better cart conversions
Key advice for improving CTR:
- Test multiple recommendation types (“Frequently Bought Together,” “Inspired by Browsing”)
- Add in-cart recommendations
- Optimize placement and use high-quality product images
- One contributor challenges the need for A/B testing, noting most stores lack sufficient traffic for meaningful results and suggesting manual evaluation instead
- Most engines match products through attributes combined with purchase history rather than individual browsing data
The discussion remains open with the original poster thanking contributors for their suggestions.