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
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
More Case Studies
See All
How Rigplay Uses Generative AI and ML to Automate Human Motion Animation and Slash Production Costs
Media & Entertainment
How Nordic Insurance Company Partnered with EY to Automate Claims Management Using AI
Finance & Banking
How Central England Co-operative Automated Employee Record Retention Compliance
Real Estate
How Macquarie Uses Predictive AI to Clean and Unify Data for Better Insights and Outcomes
Finance & Banking
How Holcim EMEA Digital Center Used GitHub Copilot to Accelerate Large-Scale Salesforce Code Refactoring and Improve Performance
Technology & SaaS
How DHL Uses AI to Optimize Logistics, Warehouse Management, and Delivery Accuracy
Retail & E-commerce