eCommerce Search is a high potential product discovery channel with a 2X higher conversion percentage than other channels like Product Listing Pages and Product Recommendations. However, the success of this channel depends upon the data assigned to the products and its configuration in the search index.
The products that match the query in the search index are sorted using the T-Score and not relevance, as we are optimized for higher conversion. The T-Score is a score assigned to each product based on engagement metrics and more can be read here. Improving the quality of data in the search index improves the quality of search results displayed for all queries.
The Tagalys search index contains product information like attributes, fields, category/collection names, etc, This data is assigned to products on the eCommerce platform (Magento, Shopify, BigCommerce, etc.,) and is sent to Tagalys as part of the dynamic product feed. From today, merchants can define which tags should be included in the Tagalys search index to avoid product catalog rework.
When the search query contains the words that are available in the search index, the products associated with them will be included in the search results.
Example: Consider Product A has the tags ‘Product Type: Shirts’ and ‘Color: Blue’ and these tags are included in the search index. Now, when a visitor searches using the query “Blue Shirts”, Product A will show up.
If these tags are not included in the search index, the search query “Blue Shirts’ will not show Product A in its results unless the query is covered in other details which are a part of the search index.
The eCommerce search engine is unlike a context-based search engine like Google. The eCommerce search results depend upon the data assigned in the product catalog. The better and accurate the data, the more accurate is the search results.
The accuracy of the search index is more critical for eCommerce retailers with high site search volume (greater than 200K searches per month) as inaccuracy in some individual search queries can dramatically affect the store conversion.
(Search Query for ‘Shirt’ showing ‘Blouse’ in results)
Here are some of the factors that affect the search accuracy
Retailers could choose to improve search accuracy by configuring the search index according to their requirements. Tagalys provides the ability to modify the search index at the granular level to omit selective tags that return false positives.
Example: When two or more product types are grouped under a single Category/Collection and if it causing false-positive results, the particular Category/Collection can be removed from the search index.
Here is a sneak preview into the search accuracy add-on dashboard! Contact us for immediate access.
Feel like trying this? Get a complimentary pack of the first 20 tags!
Also, Check out our Magento Search, Shopify search, BigCommerce Search plugins which offer various other features like Synonyms, Stemming, Suggestions, Spell-Check, etc
Interested in a complete demo of Tagalys Search? Schedule a discussion with us today!
Vanja S
Sheike
"Tagalys makes merchandising effortless. Their data driven sequencing and sorting drastically improves our effectiveness. Tagalys takes the guesswork out of merchandising and product recommendations."
Ryan R.
Camilla
"I love that Tagalys listens to customer needs and has an innovative + agile team around them which can support addressing those needs and adding improvements to the roadmap."
Rafaelle C.
Blue Bungalow
"Tagalys is the powerful and reliable data-driven solution that we were looking for when it came to search & merchandising for our Shopify Plus store. There is no limit as to how custom you can get with your merchandising, which is exactly what we were after!"
Tiarne Warren
Meshki
"The dedication of Tagalys team is evident from the feature developments. I appreciate their effort in understanding our business needs and feedback. We have saved numerous working hours and achieved great performances."