On-site search is the internal search engine of an eCommerce platform that enables users to instantly find products across multiple brands, categories, and storefronts.

In multistore environments, complexity increases significantly. Customers may search across:

• Multiple brands under one umbrella

• Thousands or millions of SKUs

• Different price segments

• Overlapping product categories

• Various store inventories

Because multistore eCommerce platforms manage large catalogs and diverse customer intents, search performance directly impacts:

• Cross-store product visibility

• Conversion rate

• Basket size

• Inventory exposure

• Overall revenue performance

If search fails to understand brand intent, category context, synonyms, or stock availability across stores, friction rises and customers abandon quickly.

Optimized on-site search in multistore environments:

• Unifies product discovery across brands

• Prioritizes in-stock and high-margin items

• Supports scalable catalog growth

• Drives measurable revenue contribution

For multistore eCommerce businesses, search is not just a feature.
It is infrastructure-level growth technology.

Findbar optimized the on-site search engine of Public focusing AI-powered relevance, typo tolerance, semantic understanding, and real-time product ranking. This resulted in better product discovery and higher engagement from search users.

AI search understands user intent (even with misspellings or Greeklish queries), prioritizes high-converting products, and reduces zero-result searches. When customers find what they are looking for faster, conversion rates increase significantly.

Search Revenue Contribution (SRC) measures the percentage of total online revenue generated from users who interact with the search bar. In many pharmacy eCommerce businesses, search users convert at a much higher rate than non-search users.

In multistore eCommerce environments, product catalogs are large, diverse, and often complex. Customers don’t want to manually navigate multiple brands or categories — they want immediate, accurate results.

Multistore customers often:

• Search for specific brands across the platform

• Look for the best price among multiple sellers

• Compare similar products from different brands

• Use exact product names or model numbers

• Filter by availability, location, or store inventory

Because multistore platforms aggregate thousands (or millions) of SKUs, search becomes the primary navigation tool.

If search fails to unify results across brands or misinterprets intent, users experience friction and abandon quickly.

That’s why optimized on-site search is a key revenue driver in multistore environments.

It:

• Connects users instantly with the right seller

• Improves cross-brand visibility

• Enhances product comparison

• Increases conversion rate and basket size

For multistore eCommerce, search is not just convenience.
It is operational efficiency and revenue acceleration combined.

Yes. Findbar is optimized for Greek language queries, Greeklish searches, and transliteration patterns — which are extremely common in Greek Multistore eCommerce.

Implementation is typically fast and lightweight, requiring minimal technical effort. Most online Multistores can activate Findbar quickly without disrupting their existing eCommerce platform.

Yes. When users immediately find relevant products, bounce rates decrease and session duration increases. This improves both user experience and revenue performance.

Unlike basic search tools, Findbar:

• Uses AI for intent understanding

• Optimizes product ranking based on performance

• Supports Greek & multilingual environments

• Provides measurable business KPIs (SRC, SMI, Search CVR)

Yes. Whether a Multistore has a few thousand SKUs or a large product catalog, AI-powered search scales efficiently and drives measurable growth.