AI guided selling turns complex product configuration into a conversation. Learn how conversational AI validates technical specs, checks BOM compatibility, retrieves documentation, and catches invalid combinations before the quote stage.
Sequential A/B tests on your AI shopping assistant take months and miss interaction effects. Multivariate testing reveals which variable combos actually drive revenue. Covers factorial design, Taguchi arrays, sample sizing, and reading results without false positives.
Google Lens processes 20B+ visual searches monthly, with one in five carrying shopping intent. Only 8% of brands have implemented visual search. Here's how it works and how AI chat turns a photo into a sale.
A technical breakdown of how AI chatbots fit into MACH architecture. Covers microservices, API-first, cloud-native, and headless principles for ecommerce engineering teams building composable stacks.
Most AI chatbots silently degrade after launch because nobody built a QA program. This guide covers the Audit-Test-Govern model: team structure, six test categories, quality scoring rubrics, and the governance policies every ecommerce brand needs to keep AI accurate in production.
Most ecommerce brands run one AI for product discovery and another for order support. The gap between these systems, where customer context disappears and contradictory messages erode trust, is where first-time buyers silently decide never to come back.