For retailers and brands that have massive product catalogs — DIY, consumer electronics, auto parts, etc. — effectively selling ALL categories of your products in ALL their variations on your retail website is challenging to say the least. Consider how many different product variations there are for retailers serving specific consumers where product variability is necessarily broad and deep.

Take original motorcycle parts, for example. How many motorcycle models, sizes, and specifications for original parts does Harley-Davidson have for sale on its website? There are three options alone on a set of original mirrors for a 1984 Touring Electra Glide FLH.

Aftermarket motorcycle part provider Revzilla.com has 12,466 motorcycle parts for sale. If each of these products has several options, this equals a massive amount of SKUs. This ridiculously large number of products doesn’t include the numerous variations of helmets, riding gear, accessories, or tires.

How about sites like Home Depot or Lowes Home Improvement where the variability of options across and within product categories is broad and deep? How many specific product variations must be properly indexed, managed, and analyzed on these eCommerce websites?

Perhaps a better question is: Can online shoppers actually find what they are looking for on your large catalog retail site?

If your answer is “no” or “I don’t know,” it is likely you are losing potential sales conversions due to inadequate search engine capabilities.

How retail website search affects sales conversions

As you know, Amazon’s powerful search engine knows what you’re looking for often before you are finished typing. This equates to many multiples of upselling and cross-selling opportunities that you are missing out on.

The following eye-opening statistics indicate just how important an eCommerce website search engine is to your bottom line.

• 43% of shoppers on retail websites go directly to the search bar (Forrester: “Must Have E-Commerce Features – Roadmap: The Retail E-Commerce Playbook”)
• Conversion rates increased by 100% for shoppers that successfully used the site search toolbar (Moz.com: “SEO Has a Younger Sibling: It’s On-Site Search, and It Deserves Attention”)
• 76% of consumers report an unsuccessful search resulted in a lost sale (Google: “Search Abandonment Impacts Retail Sales Brand Loyalty“)
• 48% purchased the item elsewhere due to unsuccessful search (Google report above)
• 52% of shoppers abandoned shopping carts when there was at least one item they couldn’t find (Google report above)

It is quite evident that upgrading your e-commerce site’s product search capabilities will lead to big benefits over time. It is also quite evident that if your current search engine isn’t up to par, your sales conversions aren’t as good as they could be.

The basics on website search functionality

Below is a brief overview of the basic functionality your search tool/engine requires to properly serve and engage online shoppers.

Recent search – This basic search function gives shoppers lists of all the search queries they performed previously on the site. As the shopper types in the search bar, the results become more specific.

Auto spacing – When this search functionality is enabled, the search engine automatically corrects shoppers that don’t include spaces in search queries and provides results for the corrected queries. For example, when a user quickly types “samsungsmarttv”, the search engine automatically interprets it as “samsung smart tv” and gives the correct results.

Spelling correction – Many times when typing a search query, shoppers make spelling mistakes. When this occurs, the search engine automatically corrects typos and uses the correct spelling.

Synonyms – Sometimes shoppers perform searches using keywords that are not used in the product names and descriptions. When this occurs, shoppers aren’t given sufficient search results and are forced to try further variations. At such times, the search engine should recognize synonyms of the search keywords and give shoppers more meaningful and wider ranges of products from which to choose.

Alternate suggestions – When entering a search query, if shoppers make mistakes in semantics, spelling, spacing, etc., the search engine automatically makes the necessary corrections and uses corrected search queries to process and deliver results.

Stemming – When shoppers use natural language including singular, plural, tense, case, suffix, prefix, etc., in search keywords, the search engine should ignore them and instead use root words so search results are complete and consistent. Thus, a search query like “Boy’s playing vehicles” gets converted to “boy play vehicle” for further processing.

Search Across Dimensions – When a shopper searches for specific attributes, the search engine should query keywords across all product dimensions and fields and return a complete set of results.

How fast are your retail website’s search queries?

Page load time directly impacts customer bounce rates. It is important for the search engine to process the query, compute the product rank, and render results as quickly as possible to maintain shopper engagement.

For reference, Amazon.com takes 145 ms to generate a response for the search query “scarf with leopard spots and crinkled texture” on a desktop.

In conclusion, getting your large category retail website better equipped as far as search capabilities will go along way in improving sales conversions and average order value.

To learn more about improving your eCommerce search engine, visit our Intelligent Search engine page.

Read this blog post if you are relying on a homegrown or legacy system for your eCommerce website: Why Legacy eCommerce Websites Cause Black Friday Nightmares.