As an online store’s product catalog grows it becomes increasingly important to provide site visitors with a robust and feature-rich search solution to help them find just the right product as quickly as possible while also providing an enjoyable shopping experience. The larger and more complex your product offerings become, the more you need to provide a high quality search solution.
Effective Ecommerce Search
Algolia’s Instant Search demonstration is part of a tutorial written to help web and application developers learn to use the San Francisco-based company’s hosted search application programming interface (API).
Although it is something of an academic example, the demo is delightful to use. As you type, it provides search suggestions not as a dropdown, but by swapping out page content. The words you type are highlighted on the various product entries shown, so that it is easy to understand why the search engine chose each result. Finally, it is lightning fast, returning a new, more refined set of products with each keystroke.
In short, it is a good example of an effective ecommerce search solution, because it delivers, if you will, in three ways.
- It provides a shortcut to content.
- It shows you what it is thinking.
- It works quickly.
A Shortcut to Content
If you think about it, your site’s search is a shortcut to content. Rather than making a shopper click on the main product navigation to uncover several product category options, which lead to even more sub-category options, which direct us — we hope — to a set of products, the shopper can bypass the site hierarchy and go directly to the set of products she wanted to see.
When this happens as expected, you have a happy customer who just saved time and effort.
This successful search shortcut depends on several component parts or features, including the way in which the search function finds matches and how the search is built to manage synonyms or related words.
Consider, first, how matches are found. Is the search querying a database? Is it conducting a full text search on some form of product data feed? Or is it crawling the site and indexing the content that it finds on each page?
How the search actually works will have a significant impact the results it presents and how quickly it presents them.
Next, how well does the search manage related terms? In a blog post about search synonyms, Algolia’s Julien Limoine used the example of the term “tablet.”
When a shopper starts to type “tablet” into a search box, should the search also match the term “iPad?” And does that relationship work the other way around? If a shopper types in the term “iPad,” should other tablet computers be shown in the results? Google seems to have answered this. On August 2, 2015 a search for “tablet” in Google Shopping returned iPads in the result set, but a search for “ipad” did not include results for other tablet computers. This makes sense because “iPad” is more specific than “tablet.”
For a search shortcut to be truly great, it needs to understand some of these relationships, so it can provide the proper and expected results.
Show Why Terms Are Selected
If you search for the term “tablet” on the Newegg website, one of the suggestions is for Tabletop Unlimited, a kitchen supply brand, which offers, among other things, a square griddle and a jumbo cooker.
Newegg’s search returned this result because the term “tablet” is inside the term “tabletop.”
The search is trying to anticipate what the shopper wants, so this result makes perfect sense, but imagine what the shopper might have thought if the Newegg search had loaded a new page with a picture of an Asus tablet computer and a skillet.
If Newegg did not have Tabletop Unlimited products listed on its site, this would not be a problem, but because the site has many, diverse products — remember with a great number of products comes the need for great search — it must show shoppers why a particular suggestion is being offered.
Search Should be Fast
On the JadoPado site, search moves fast. As the user types, the search feature displays not just suggestions but actual products, updating the list of products displayed with each successive letter.
This means that the search function must reach out to the server, compare the term with the indexed content, and return a full result set in the time it take the shopper to press a key.
This flashy example of search speed is important because it gives the shopper instant feedback. A significant number of shoppers will refine their search one or more times to get the best results. Quickly showing the shopper the sorts of results a term will return, makes the process of refining search almost automatic. In fact, the shopper might not even realize that he is refining as he adds “computer” to the term “table” to eliminate a skillet or two.
This is especially important for Internet retailers with large product categories that may share key terms.