AI Applications for Ecommerce: A Technical Comparison
Virtual Assistants
- Technologies: Natural Language Processing (NLP), Machine Learning (ML)
- Purpose: Engage customers in conversation and complete tasks
- Integration: Separate to website, available via SMS messaging, voice, webchat etc
- Analytics: Can collect data from customer actions including intent, sentiment and task completion
- Benefits: Reduced customer enquiries, tailored conversations
Product Recommendations
- Technologies: Predictive Analytics, Machine Learning (ML)
- Purpose: Increase conversions and average order value
- Integration: Site-wide or specific products on certain pages
- Analytics: Can be tailored to weekly, monthly, and annual sales patterns
- Benefits: Increase sales, reduce returns, support discovery of products
Pricing Algorithms
- Technologies: Predictive Analytics, Machine Learning (ML)
- Purpose: Maximize revenue per customer by personalizing prices
- Integration: Various levels of personalization, e.g. non-personalized pricing, personalized product pricing, real-time price optimization
- Analytics: Measurement of customer response to various pricing models
- Benefits: Increased average order value, more efficient customer segmentation
Image Recognition
- Technologies: Computer Vision, Deep Learning, Machine Learning (ML)
- Purpose: Automate tagging images on product pages for faster search and sorting
- Integration: Every product page via APIs
- Analytics: Automatically detect and categorize image tags for product pages
- Benefits: Increases discoverability of products, personalize the customer experience
