Search in a Shopify store with hundreds or thousands of items is more than just a search box. Rather, it is a mechanism for retrieval and ranking that determines what items the customer sees after entering a query.
For example, consider a customer that searches for the phrase “stainless steel lunch box with three sections for less than ₹1,500.” The catalog might contain an item called “304 SS 1200ml Insulated Meal Container,” with no match in terms of keywords.
Here is where AI search, semantic retrieval, product attributes, ranking, and filters become useful.
Boost AI Search and Discovery is one of the solutions that are developed to deal with this issue. This solution combines AI search, filters, merchandising, and product discovery in Shopify stores. Nonetheless, retailers with complicated catalogs may want some solutions that better handle relevance, retrieval, ranking, and analytics.
What Does Boost AI Search & Discovery Do?
Boost is created to focus on Shopify’s search & discovery ecosystems. Offering a range of features like AI-supported search, comprehensibility, a tolerance for spelling errors, filtering, merchandising, and product search.
Its filtering functions rely on product specifications or different filtering systems in collections, while its AI search can understand the meaning of product specifications, like price, color, size, or brand name, within the requirements of the question.
This leads to Boost being of benefit to merchants who want to enhance their Shopify searches.
However, the more intriguing consideration is:
How much control do you have over the search engine behind the experience?
What to Look for in a Boost Alternative
The modern method of ecommerce search includes the following steps:
Query → Query Understanding → Retrieval → Ranking → Filtering → Product Results → Click → Purchase
If something goes wrong at any of these stages, the conversion rate will be affected.
For instance, if a Shopify website generates ₹30 lakh monthly, out of which ₹7 lakh comes from search queries, achieving a better conversion rate could help the site gain some extra money if the conversion increases from 3 to 3.4%.
Thus, it would be wise to keep track of the following metrics:
- Search conversion rate
- Search CTR
- Zero result rate
- Unclicked queries
- Add-to-cart rate
- Average click position
- Revenue generated from search
- Filter usage
Boost AI Search & Filter Alternatives Compared
| Platform | Search | Filtering | Relevance Control | Analytics | Best Fit |
|---|---|---|---|---|---|
| ExpertRec | AI and semantic search | Advanced filters and filter trees | Field weights, synonyms, ranking | Search, funnel and product analytics | Stores needing configurable search optimisation |
| Boost AI Search & Discovery | AI search and discovery | Advanced Shopify filtering | Relevance and merchandising controls | Search and product insights | Shopify stores wanting an integrated solution |
| Algolia | Lexical, semantic and neural search | Facets and filters | Extensive developer controls | Advanced search analytics | Engineering-led teams |
| Bloomreach | AI search and discovery | Advanced faceting | AI, merchandising and personalisation | Commerce analytics | Larger ecommerce organisations |
| Searchspring | Search and merchandising | Faceted navigation | Strong merchandising controls | Commerce reporting | Merchandising-focused teams |
ExpertRec: A Search-First Alternative
ExpertRec sees ecommerce search as a configurable retrieval and discovery system.
In the case of Shopify, ExpertRec offers semantic search, SKU search, metafield search, synonyms, typo correction, autocomplete, ranking controls, filtering, merchandising and analytics. (expertrec.com)
One key feature of ExpertRec is field-level relevance.
Think about, for example, a hardware store where the products data might include:
- Product title
- Manufacturer
- SKU
- Material
- Thread size
- Category
- Technical specifications
For the query “M10 stainless steel bolt,” the reference to SKU, material, size and type of product might play a more important role as a ranking signal rather than a long description of the product.
ExpertRec gives merchants the opportunity to create their own searchable fields and prioritise fields such as title, brand and SKU. (expertrec.com)
That means that merchants can influence the way catalogue data is used to provide relevant search results.
Semantic Search for Natural-Language Queries
ExpertRec semantic search documentation covering vector embeddings and search modes.A customer’s search based on exact keywords is effective only when they know what to look for by using the same terms given in the product’s catalogue.
This is not always the case.
For example, a customer may be looking for “an ideal chair for people who work eight hours for ₹12,000 maximum,” while the item in the catalogue may be called “Lumbar Support Ergonomic Mesh Office Chair.”
The two descriptions do not match, but the goal of both searches is very similar.
Semantic search is a way of knowing whether the query and the product are connected or not and relies on theories of semantic meaning rather than simple keyword matching.
The way ExpertRec implements semantic search is through vector embeddings and sentence transformers to give meaning to both queries and products.
This type of search may come in handy especially for those businesses where technical products are sold, and those selling big catalogues and long queries.
Filters That Work With Search
Filters can be helpful when the customers are aware of the features they seek but are unsure of the name of the product.
An example of this would be:
“Summer linen dress for vacation under ₹4,000.”
In such cases, the filters used could be:
- Size
- Colour
- Fabric
- Sleeve style
- Length
- Cost
- Availability
Expertrec facilitates filtering through product features, tags, and metafields as well as using filter trees and advanced numeric filters.
The use of filter trees thus creates various options for discovering products.
Search Analytics Reveal Relevance Problems
Search analytics will answer more than just “How many times have the search been conducted?”
| Query | Searches | Clicks | Purchases |
|---|---|---|---|
| office backpack | 1,950 | 1,210 | 105 |
| laptop backpack 15 inch | 1,480 | 970 | 96 |
| waterproof travel backpack | 1,120 | 530 | 41 |
| anti theft backpack | 980 | 215 | 17 |
| backpack for college | 760 | 490 | 52 |
The fourth question indicates that the search volume is high, while, engagement is low.
Possible reasons for this are bad synonyms, bad ranking, incomplete product features, or irrelevant results on the first page of search.
ExpertRec analytics can show zero-result searches, unclicked searches, search CTR, filter usage, spellings correction, and the funnel of conversions. Integration with GA4 will connect the search behaviors with the broader revenue analysis.
AI-Powered Shopify Search & Product Discovery
Looking for a Boost AI Search Alternative?
Move beyond basic product search with ExpertRec. Improve Shopify product discovery with semantic search, SKU and metafield search, intelligent autocomplete, configurable ranking, advanced filters and actionable search analytics.
Semantic Search
Advanced Filters
Relevance Control
Search Analytics
Explore AI-powered search for your Shopify store
Ranking Control Matters
Let’s take the case of 10 products for the term:
“gaming monitor 27 inch below ₹25,000.”
Even the least priced product may not have the first position.
Ranking involves:
Text relevance + availability + popularity + product quality + business rules.
This is where the role of search weight, ranking rules, synonyms and merchandising comes in.
ExpertRec provides controls for search weight and product ranking to the merchants such that they may control the retrieval or display of the products.
Boost vs ExpertRec: Which Should You Choose?
Shopify merchants who want a single solution for search, filtering and merchandising can consider Boost.
If, on the other hand, your search solution is supposed to be a measurable marketing channel, make sure you turn to ExpertRec. You should consider ExpertRec in case you need:
- semantic product search
- SKU search and metafields search
- weighted search at the field level
- custom filter trees
- if advanced numeric filters are needed
- synonyms management
- typo tolerance
- search redirects
- search analytics
- search to purchase analysis
- GA4 integration
- custom search interfaces
This is due to the fact that ExpertRec’s solution for Shopify search delivers the above-mentioned abilities combined with the support for customizable search templates and APIs.
How to Evaluate a Boost Alternative
Don’t select a search tool solely because it markets itself as “AI search.” Conduct the same tests as you would with a standard catalogue:
- Nonsense/normal requests
- Long-term searches
- Item number searches
- Incorrect queries
- Synonyms
- Combinations of characteristics
- Price criteria
- Queries with no result
- Multiple filters
- The process of starting a purchase
It is also necessary to compare results.
It is essential to understand that what matters is not the number of AI features of the tool but whether customers can get the needed product faster and purchase it more easily.
Final Verdict
Boost AI Search & Discovery is an efficient search and filtering solution for Shopify users. Its combination of filtering, merchandising and searching makes it a good choice for most of Shopify stores.
However, as the catalogue gets complicated, merchants need to look for alternatives assessing the quality of retrieval, ranking control, semantic comprehension, and analytics instead of merely counting the features of the solution.
For Shopify-based stores that want to have a customizable solution, ExpertRec is a good candidate as long as the requirements are related to semantic search, SKU and metafield search, complex filters, relevance management, and search-oriented analytics.
