Different catalogs. Same playbook.
From western wear to ethnic décor to digital gaming: different catalogs, different shoppers, different commercial realities, and the same model architecture trained separately on each merchant’s own data. Every number below traces back to the merchant’s own Shopify orders.
AOV lift
Hat CountryROI
Hat Countryitems / order
LoveNspirerevenue
Exon GamesThree stores. Three verticals. One architecture.
Each report is a measured deployment with the metrics and attribution methodology included.
A set of AI models replaced four merchandising plugins.
Single-item carts turned into multi-item western-wear orders across the product page and cart, and the team stopped writing rules entirely.
Read the full report →Search that learned a festival catalog on its own.
Embeddings caught the cultural context and product pairings a generic search couldn't: no synonym list, Hinglish queries understood, items per order more than doubled.
Read the full report →Cart bundles that pay for themselves.
Platform-aware upsells and automatic bundle discounts now drive the majority of attached revenue across keys, DLC, and licenses, with no merchandising effort.
Read the full report →What merchants actually say.
“Shaswat went above and beyond, building custom recommendation models tailored to our catalog and customer behavior. The PersonalizerAI app has become one of our most valuable tools for increasing average order value and improving the shopping experience for our customers.”
“PersonalizerAI completely unblocked our discovery problem during peak festival season, effortlessly surfacing relevant bundles that generic apps missed.”
“The personalized cross-sells on game keys significantly improved our unit economics in a very competitive margins business. Dynamic bundle pricing changed everything.”
