How E-Commerce Retailers Use AI to Increase Average Order Value and Conversion Rates with Personalized Recommendations

By: GoBeyond Team
July 3, 2025
3 min read
E-commerce AI recommendation engine interface

Quick Overview

General e-commerce retailers use AI to recommend products at checkout based on browsing history, purchase behavior, and preferences. AI-driven personalized suggestions increase average order value (AOV), conversion rates, and repeat purchase intent.

Various global e-commerce retailers
Various global e-commerce retailers
Company Size
Varies widely
Revenue Range
Varies widely
Primary Challenge
Increasing AOV and conversion through personalized upselling and cross-selling
Key Metrics
\- 15–20% increase in average order value\- 15% higher conversion rates\- 80%+ repeat purchase intent

The Problem

Generic product recommendations lacked personalization and relevance, limiting sales potential

The Solution

AI-powered recommendation engines analyze user behavior and preferences to deliver tailored product suggestions during checkout

Results

\- Increased sales and customer loyalty\- Improved shopping experience\- Higher repeat purchase rates

Details

Industry
Retail & E-commerce
Departments
Sales & Lead Generation
Marketing & Content
Use Cases
Upsell & Cross-sell
Tags
Recommendation Engine
GenAI
NLP
Time-Saving
Cost Reduction
Client Satisfaction
SaaS
AI Tools Used
No items found.
Sources
https://dialzara.com/blog/ai-powered-upselling-and-cross-selling-2024-guide/https://www.creatio.com/glossary/ai-for-cross-selling-and-upselling

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