Perfect Onsite Search: Understanding Main Types of Customers

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A lot has been said about the importance of internal website search and the ways to optimize it. Autocomplete and autocorrect options, segmenting search results, advanced search mechanisms — all proved to be of a huge help to searchers.


However, all these tools come totally useless you figure out: what your site visitors are actually entering in the search box?

Are they searching for a particular product feature, a certain product type or a product model? Is the search term a product itself, or just its feature, accessory or spare part?

The thing is, to deliver the best matching results, you need to understand what types of search queries are most popular with your site visitors.

From this post you will learn about:

  • 7 most common types of eCommerce search queries
  • the search methods (and their combinations) that will perfectly handle each search query type

Let’s dive into it!

1. Exact Search Queries

Most often, store visitors use the internal search to find a certain product. Hence, they enter either an exact product title or its ID.

Example: ‘Samsung Galaxy S6’, ‘’iPhone 6S’.


This type of search queries is the easiest one to handle technically. All you need is a search engine that supports this type of queries (Sphinx, Solr).

However, there are some important aspects one should take into account:

  • grammatical/ phonetic misspellings  — users may have misheard the name of the product or brand or don’t know how to spell it the right way. E.g. ‘Sumsung C6’.
  • alternative product names— the same product or service may have different names, or the names, localized for different markets. E.g. ‘Nestlé Quik’ vs ‘Nesquik’
  • copy/pasted product names — these may be copy-pasted from other websites, industry databases, or user-generated Web content.
  • searching for product models — sometimes users may search not for the product itself, but for its certain model. E.g. ‘Samsung – Galaxy S6 edge 4G LTE 32GB Gold Platinum Verizon’.

To gracefully handle these variations of exact search queries, you need to:

  • add autocorrect tools to your site search toolkit
  • find an opportunity to partner with database sites and get all possible variations of  product title variations (that can be Goodreads if you are selling books, DPReview if you are in cameras & video equipment niche, etc.)
  • add/enable the ability to search within secondary product data attribute.

2. Product Type Search Queries


Searching by product type is a second popular type of search queries. By entering a generic product type into a search box (e.g. ‘jeans’) visitors get straight  to the category product list. That is often done to avoid browsing through numerous store categories.

The main challenge with supporting these queries is that search results may return a bunch of not relevant products. For example, when looking for ‘jeans’ you may get:

To avoid this, you should properly categorize and label all products in your store catalogue.  Accessories, product spare parts, and related products — all should be moved to separate subcategories and labeled accordingly.

Another important aspect to consider in this case is synonyms. Customers may search your store using the words different from the ones you used for naming your products and categories. Adding search synonyms for each product and category will help your visitors get what they need.

For example, items from the category ‘sweaters’ should get included into search results when a visitor enters ‘jumpers’ or ‘pullovers’.

Also, it can be helpful to add relevant filtering and sorting options so users could narrow down the search results to a specific category or attribute (model, brand, etc.).

This is a great example by Walmart:


3. Feature Search Queries

Often, site visitors may search for a certain product feature, a set of features or  particular product qualities. For example, when searching for an iPhone case they may want a green, waterproof, silicon model.

To handle this type of queries, your website search engine should be able to parse product attributes (color, material, format, quality, form, etc.) and correlate them with the entered search queries.

Additionally, you can dynamically add a set of attribute filters right on the results page. That will let site visitors analyze the found items on a more granular level and find the exact product they need.

Here is a great example by Forever21.


4. Compatibility Search Queries

A lot of products can be compatibility dependent. Although they are sold as separate items, they can be used only with products that customers already own or want to buy in your store. It can be accessories, spare parts (e.g. an iPhone charger), products used in conjunction with other products (a Surface tablet keyboard), consumables (ink for an HP printer), etc.

Therefore, the search relevance of these products is determined by their compatibility with other product(-s) in your store catalogue.

The easiest way to handle this type of search queries is to let site visitors filter out products based on their compatibility and add links to compatibility dependent product categories.


But when it comes to compatibility search, it’s important to remember that site visitors may frequently search for accessories or spare parts not knowing their exact names. Hence, you should:

  • Include a brand name into the title of each compatibility dependent product
  • Add the product model details into the title and description of any compatibility dependent item

To avoid any confusion by mixing up results for products with their accessories, you’d better display the found compatibility dependent products in a separate section.

5. Relational Search Queries

Sometimes people may search not for a product itself but for any notion, entity or name associated with it.

That is mostly typical of entertainment search queries.

For instance, Harry Potter fans may be searching for any books written by J.K Rowling, and Brad Pitt fans may want to find DVDs with his early movies.

Also, this way people can search for designer things (clothes or jewelry) and items associated with certain events (e.g. halloween costume).

The biggest challenge with this type of queries is that the associated thing (a person or event) may not be included into a product title or its attributes list. Hence, it will require contextual search tools.

Additionally, your store search engine should be capable of identifying this type of search queries as independent search terms (and autocorrecting them whenever needed).

6. Slang, symbols and abbreviation queries

Cyberspace is the place, where people don’t always follow the linguistic standards and norms. They tend to use a lot of jive talk, various symbols, and may literally shorten every second word.

All these aspects should be taken into account when optimizing your site search mechanisms. Also, understanding a wide range of linguistic shortcuts can be extremely important, especially if you target young folks or geeks.


Technically, the support of slang search queries is very easy to implement. All you need to do is mapping between the standard and slang terms. E.g. “tee” should be mapped to “T-short”, “shoes” to “kicks”.


First, find out which symbols you site visitors usually enter (this info can be found in your search logs). Next, you may either map terms that contain symbols to your popular search terms (iPhone 6 +) or introduce new ones (t-shirts $50-$70).


Supporting abbreviation queries also doesn’t require knowledge of programming know-how. All you need to do is to map a shortened form of the search term with its full version. E.g. ’JS’ to ‘Java Script’, “HP” to “Hewlett-Packard”.  


7. Long-tail natural language search queries

You must have heard a lot of funny stories about weird search queries like “a perfect holiday tour, somewhere in a warm country with a 5-star hotel on the beach of a picturesque torques sea”.

It may seem funny, but quite often your site visitors may enter something similar to what they use in their regular spoken language. And in order not to let them leave your store dissatisfied, you should be able to handle these long-tail natural language queries.

This is the case, when your website search engine should understand context, semantics and relationships of the query. The query should be broken down to separate constitutes and each one should be correlated with a certain product attribute.

E.g. for the query “trainers that are of a green color and are available in size 43”, your site visitors should see a list of green trainers in size 43.

Abt almost managed to do it right:


Tools to Improve Onsite Search:

Below is the list of search engines, tools and services you may use for your eCommerce store to perfectly handle any type of the above mentioned queries:


An onsite search box is an effect tool of communicating with site visitors and turning them into buyers. In addition to its main purpose – delivering results, the internal store search can help you learn more about your customers interests, shopping habits, which, in turn, will help you shape better pricing policy and customize offerings.


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Vishal Gaikar

Article by Vishal

I am Vishal Gaikar, Software Engineer, Web Addicted, Living in Maharashtra, India. If you like This post, you can follow Tricks Machine on Twitter, also you can add me on Google+.

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