YesPlz AI quickly adapted their AI model to our needs and delivered measurable improvements to our search experience. Their speed, technical precision, and collaborative approach made them an invaluable partner for Zilo.

Nishant Shetty

Deputy Director - Revenue, Zilo

Zilo is one of India's fastest-growing multi-brand fashion retailers. As their catalog expanded, so did their search problem.

They started with Shopify's native search. Results were too literal — shoppers searching "printed kurta" got everything except what they wanted. Then they upgraded to Algolia, hoping smarter indexing would fix it. It helped with speed, but Algolia doesn't understand fashion. It still couldn't connect "blouse" to "saree top," or rank results by what Indian shoppers actually buy.

So Zilo came to YesPlz. Search was driving 2x the sales attribution of their old Shopify setup — and 3.4x the add-to-cart rate of the industry benchmark.

Challenges

• Search that didn't understand fashion:
  Zilo upgraded from Shopify to Algolia hoping for smarter search. Algolia improved indexing speed, but it still had no concept of fashion context. Searching "ethnic formal" returned unrelated results. Shoppers who didn't find what they wanted in the first few results gave up and left.

• Manual tagging that couldn't keep up with a growing catalog:
  Every new product required the team to manually add tags. The workload never stopped — and the inconsistencies it produced made already-weak search results worse. Time spent tagging was time not spent on growth.

• Recommendations that ignored brand, style, and location:
  Zilo runs multiple storefronts serving different cities. The recommendation engine didn't account for regional preferences, brand affinities, or outfit context. "More like this" showed products that had nothing to do with what the shopper was looking at.

  Key Results:

  • 2x higher search sales attribution vs. their previous Shopify search

  • 3.4x higher search add-to-cart rate vs. the industry benchmark

  • 2.8x higher "More by Brand" recommendations ATC vs. the industry benchmark

  • Location-aware ranking active across all Zilo storefronts — regional inventory surfaced to the right shoppers

  • 8 AI tools deployed: Hybrid AI Search, AI Tagging, Recommendations, AI Stylist, Search Tune Agent, Smart Collection

  What really stands out about YesPlz site search is the flexibility and control it gives us. Our previous setup with Shopify felt constrained by the platform’s defaults, but with YesPlz we can tailor everything to how fashion shoppers actually browse — from prioritizing brands and sizes to fine-tuning fashion-specific keywords. Overall, YesPlz feels tech-driven and adaptable than Shopify’s built-in search.

  

  Pragyay Parashar

  Senior Product Manager, Zilo

  Solutions: 

• Custom Hybrid AI Search — trained on how Zilo's shoppers actually search:

  YesPlz built a search model specific to Zilo's catalog and shopper behavior. When someone searches "printed indo-western" or types "blouse" instead of "saree top," the results still match. The model learns from Zilo's actual click and purchase data — not generic fashion benchmarks.

• Automated AI Tagging — every new product tagged the moment it's uploaded:

  YesPlz's tagging model was trained on Zilo's multi-brand catalog, including India-specific fashion categories that Western tagging models miss. Tags now include vibe, occasion, regional terminology, and style attributes — applied automatically, consistently, at scale.

• Location-Aware Recommendations + AI Stylist — personalized at the storefront level:

  Each Zilo storefront now surfaces recommendations tuned to regional inventory and local preferences. The AI Stylist adds conversational discovery for shoppers who don't know exactly what they want — they describe an occasion, a vibe, or a style, and get a curated result.

AI Site Search: Before and After (e.g., "Formal Dresses")

Before

After

Automated Product Tagging: Before and After

Before

After

AI-Powered Curation: Before and After

Before

After

From Zero to AI Stylist: Tailored Success with Zilo

Before

After

Lesson Learned

• Generic search engines don't understand fashion terminology:
  "Blouse" and "saree top" mean the same product to your shopper — but not to Shopify or Algolia. Fine-tuning for your specific catalog language is the difference between search that converts and search that frustrates.

• Tagging is the foundation, not the afterthought:
  If your product attributes don't match how your shoppers search, no amount of search tuning will close the gap. Getting tagging right — with fashion-specific and market-specific labels — unlocks everything else.
  
  Want the full breakdown? Read the Zilo deep-dive:

• AI Solutions for Fashion Retailers: Zilo’s eCommerce Success Story

• Trying Zilo AI Stylist: My Honest Out-of-the-Box Experience as a Fashion Non-Expert