A customer visits your Shopify store looking for a specific product. Rather than just searching for “black sneakers”, the customer might enter the exact SKU in your search box, which could be something as specific as NK-AIR-42-BLK.

The SKU could be the number from the previous invoice, estimate, catalog, WhatsApp conversation, distributor document, or a previous order.

So, when entering the SKU in Shopify search, the customer may not be able to find the product and think that it is out of stock, whilst it is actually in stock.

This means that for those e-commerce stores that have large inventories of products, technical products, spare parts, B2B goods, wholesale products, electronics products, industrial equipment, or products that have several variants, the Shopify SKU search can be extremely essential for enhancing the search experience for the customers.

What Is SKU Search in Shopify?

SKU means Stock Keeping Unit.

It is a unique internal identification number that helps a company identify its product or product variation.

An example will be an online store selling office furniture:

• CHR-ERG-BLK-01
• CHR-ERG-GRY-02
• TBL-WD-120-OAK

A client may search using a full SKU:

CHR-ERG-BLK-01

Or just part of it:

ERG BLK

A good e-commerce search engine should be flexible enough to understand:

SKU search is the ability of a site search engine to:

1. Index SKU data
2. Compare customer queries with SKU
3. Retrieve the necessary product/
4. Rank the searched product accordingly
5. Show the product information and availability

SKU search is remarkably different from standard keyword search.

“Wireless headphones under ₹5,000” is the expected outcome of such search.

In the second case, using the product code number, say WH-SONY-BL-230, allows making the search precise.

Every little character counts.

Why Is Shopify SKU Search Important?

SKU search is essential for retailers whose customers already know the product code.

Such businesses can be:

• B2B ecommerce platforms
• Electronics market
• Automotive parts retailers
• Industrial equipment companies
• Hardware stores
• Medical devices catalogues
• Wholesale retailers
• Fashion dealers with significant product collections
• Spare parts ecommerce companies

As an example, think about an industrial supplier selling as many as 25,000 different pieces.

A buying manager has bought:

BRG-6205-2RS

At the price of ₹1,850 per unit before.

They log into the website later to find the part they need.

However, the search results include:

• Similar bearings
• Related components
• Products with “6205” in their title
• Irrelevant items

This means customers will have to search for the part manually.

How Shopify Product and Variant SKUs Work

The Methodology Behind Shopify’s Product and Variant SKUs

When it comes to SKU searching, one major issue is that a SKU can refer to a variant instead of referring to the main product.

Take this example, for instance:

Product Name: Men’s Running Shoes

Variants:

So when a customer uses the search term RUN-BLK-09, the best search experience will not provide results that only show the main product.

Instead, it should assist customers in going to the exact variant they are looking for.

Thus, the ability to do searches is based on data indexing for the individual variants.

And from a technical perspective, it is necessary for the search engine to have the ability to categorize searchable features.

Exact Match vs Partial SKU Matching

One of the essential aspects of SKU search is figuring out how a search engine interprets different search queries.

Exact SKU Match

User Search:

LAP-HP-15-512

This means that the user expects an exact match.

The search engine should enhance the ranking of the exact SKU.

Partial SKU Match

User Search:

HP 15 512

The user might only know a part of the SKU.

The search engine should check whether this search matches the SKU in the database.

Differences in Formatting

SKUs can consist of:

• Hyphens
• Underscores
• Numbers
• Letters
• Spaces

For example:

MOB-CASE-IPH-15

The user can search for:

MOB CASE IPH 15

or:

mobcaseiph15

At that point, query normalization becomes important.

A search engine might normalize the formatting, punctuation, and capitalization prior to the search.

Otherwise, minor differences in formatting might prevent a user from finding a certain product.

Common Problems With Shopify Search by SKU

Many Shopify shops face problems while searching for SKUs because search relevancy is interrelated to various other parameters or columns.

One such issue is the field weight.

For example, let’s say that the product description shows the SKU:

HD-100-PRO

while the product title mentions:

Professional Home Blender

When someone searches for the SKU, the search software must recognize that the SKU field is more relevant than the not-so-clear product title

For this purpose, the search column must be ordered by relevance.

Problems that arise are numerous, including:

SKU Not Indexed

SKU may not be indexed properly in the search engine.

Variations Search Limitations

The search engine might show the main product but might be unable to present the right specific product.

Bad Partial Matching

For example, when you try searching with:

6205 2RS

the SKU can be:

BRG-6205-2RS

Incorrect Ranking

Some products with nearly the same number can receive a higher ranking than an exact SKU.

Issues With Special Characters

Hyphens and underscores can lead to incorrect tokenization of any search request.

Out-of-Stock Products

A customer can find a suitable SKU, but it is shown with products unable to be purchased.

An advanced search implementation should allow businesses to configure how inventory status and search ranking interact.

Technical Requirements for Effective SKU Search

An effective implementation of SKU search should take into account certain search technologies.

1. Field-Level Indexing

In the SKU search, it is necessary to index the SKU as a special searchable field instead of just considering it as part of the product description.

• Product Title: Wireless Headphones
• SKU: WH-BLU-ANC-01
• Category: Electronics
• Price: ₹4,999

The search engine must recognize that the SKU is a separate field.

2. Exact Match Boosting

Exact match boosting means that products that are the same as the keyword would rank higher than products that only have partial matches.

In terms of impact:

Exact SKU Match > Partial SKU Match > Product Title Match > Description Match

The reasoning here is to keep unrelated items from ranking higher than a precisely matching product.

3. Query Normalization

Query normalization refers to the processing of search requests in order to eliminate formatting discrepancies.

For instance, the following items:

• WH-BLU-ANC-01;
• wh blu anc 01;
• WH_BLU_ANC_01,

Should be processed to capture the essential similarities of the input queries.

4. Tokenization

The search engine is required to make a decision regarding how to break down an SKU into tokens that can be searched.

For instance:

BRG-6205-2RS

can be considered as:

• BRG
• 6205
• 2RS
• 6205-2RS

Choosing the right configuration leads to the location of products by the search engine regardless of the presence of an incomplete SKU code.

5. Synonym and Alias Support

At times, a customer can use the internal part number or the manufacturer part number.

For instance:

• Internal SKU: MOTOR-AC-220
• Manufacturer part number: MX220-A

Both part numbers can be necessary for determining the same product.

AI-powered Shopify search & SKU discovery

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Enhancing SKU Search in Shopify Using Expertrec

As a Shopify store grows its product catalogue, the limitation of using basic keyword matching for SKU search becomes evident.

This is when using Expertrec as an advanced ecommerce search solution becomes relevant in defining the search actions undertaken in the Shopify ecosystem.

An eCommerce search application like Expertrec provides eCommerce vendors with better ways of product discovery, with the capability of searching through multiple product attributes and relevance signals.

In SKU-focused searches, it is insufficient to just look for matching text.

The main aim is to set a search approach where vital identifiers are taken into account. They need to create a search mechanism that gives the proper weight to important identifiers. For instance, an electronic store should make its search process focus on the following fields:

• Product name
• SKU
• Manufacturer part number
• Brand name
• Product category name
• Tags
• Personalized attributes of a product

If a user searches for:

CAM-SNY-A7-III

the search engine may prioritize that item, instead of performing the basic keyword search.

This is becoming much more relevant because when there are a couple of products in the database, their search performance is still satisfactory.

However, as the range expands to thousands and tens of thousands of products, the situation changes drastically.

Expertrec can help to enhance searching with many facilities such as:

• Spell correction
• Search recommendations
• Auto-completion
• Product filtering
• Synonyms
• Search statistics
• Relevance improvement

Thus, SKU search is no longer viewed as something separate from ecommerce search.

SKU Search Analytics: An Often Overlooked Opportunity

Search analytics can help in examining whether customers are able to find products using the processed SKUs. The shop managers must watch for several KPIs:

• Searches without results
• Search phrases associated with the SKU
• Search exit rate
• Conversion rate by search
• Popular SKUs searched for
• Search requests followed by purchases.In case a customer repeatedly finds:

BRG6205

and it results in “No results found” while the shop actually has:

BRG-6205-2RS

it represents the search relevance gap, which can be used to optimize:

• SKU format
• Search normalization
• Synonyms
• Partial matching
• Articles’ metadata

If the number of searches is equal to 500 monthly and conversion from SKU search increased from 4% to 7%, then even a small improvement can make a huge difference if considered through the lens of the average check of ₹8,000.

Final Thoughts

The Shopify SKU search feature is of paramount significance when buyers are already aware of the specific items they wish to purchase.

In this case, the process of searching is explained as being a retrieval of the item rather than an exploration.

The key element of the Shopify SKU search functionality is that it should learn how to exactly match, partially match, normalize queries, index product variations, and prioritize SKU and part number fields.

Advanced ecommerce solutions require the power to control how such serial keys as SKU and manufacturer parts can affect the results of searches since the Shopify databases are constantly getting bigger.

Expertrec can become an effective addition to the ecommerce search process in case the online retailer is interested in increasing product discoverability using advanced AI-based search tools. By combining two features of searching, ecommerce companies will be able to create a seamless search experience for their customers.