In hopes of helping ease conversations with your development team, we decided to dedicate this blog post to explaining eCommerce search terminology to bring you up to speed on the basics.
1. Autocomplete or Autosuggest
Autocomplete or autosuggest is present in most search functions. It automatically provides keyword and product suggestions to users as they type their search keyword/phrase. It was popularized by Google, which only suggests terms. Bing, a search engine made by Microsoft, takes a slightly different approach to autocomplete, and recommends “entities”, which are suggestions structured with images. In an eCommerce scenario, it’s common to offer product suggestions in Autocomplete, which provides direct navigation to the product page.
Autocomplete serves as a way to predict the user’s intent and help them formulate their search phrase quickly and efficiently. Some autocomplete tools provide suggestions as soon as a user clicks inside the search box, while others require the user to type 2-3 characters before providing suggestions. Autocomplete ranks suggestions by an algorithm based on product popularity scores and relevance – so its recommendations are likely to convert. Most Autocomplete solutions provide typo corrections, which is an important search feature, especially on mobile devices.
2. Query or search term
A query is one of the most fundamental phrases in eCommerce search terminology. A term entered into the search box in a user’s everyday language is called a query. The average search term length is 2.4 words and half of the users enter a single query during their search session. The other half of search users refine, or reformulate, queries. Since reformulation is so common, search engines allow users to easily enter their next query through the use of Autocomplete and related search suggestions on the Search Results Page. The role of the eCommerce Search Engine is to provide the best result based on the user’s query. It has to take into consideration the users’ previous queries and other user actions on the webshop. Google Analytics offers detailed tracking of web visitors searches on its Site Search Report. This report isn’t available automatically, but can be generated after enabling a few settings in GA to collect this data.
3. Phrase matching
Phrase matching refers to a tool employed by advanced search engines that identifies sets of words that are a single phrase. For example, the phrase “tennis shoe” applies to sport shoes, not tennis and shoes. Phrase matching groups these words and displays relevant results to search users.
Most eCommerce search engines only do basic keyword matching and thus only display products when all the search terms entered by the user are present in the product’s name or description. This is incredibly limiting because users enter search terms in their everyday vocabulary, which doesn’t always match the store’s webshop naming convention.
As you can imagine, advanced phrase matching can make a huge difference in user experience while interacting with search engines. If you use AdWords, you’re already familiar with Phrase Matching as this is the same concept used by eCommerce Search Engines.
4. SERP (Search Engine Results Page)
SERP is an acronym for Search Engine Results Page, which is where product results are displayed. The SERP is the most important “real estate” on your webshop and should be optimized. Most users first interaction with your online store comes from the use of the search function.
Search result ranking and matching logic optimization is key to boosting sales and conversion rates, so be sure to keep an eye on your search analytics.
Analyzing the user interaction on your SERP is a time intensive activity, but worth the effort. If you don’t have the time or resources to devote fully to this task, make sure you’re at least monitoring the most popular search terms on your site. If you a high percentage of search exits for a particular search term, that’s usually an opportunity for conversion optimization.
Web shoppers expect to find products quickly, so be sure your webstore makes the product search process as quick and easy as possible. eCommerce managers typically invest a lot of time and money in SEO for Google and Bing. Optimizing your SERP is “internal SEO”, a process over which you have full control. Internal optimization makes it much easier for you to get conversion gains.
5. Product popularity score
Products in a webshop are automatically assigned a Product Popularity Score based on the number cart actions and purchases they receive. Products on the SERP are ranked partially according to this score. It ensures popular products are ranked higher than other less popular products. When trying to determine the product popularity of a given product, consider:
- Product purchases
- Cart actions
- Clicks on the product on the SERP or category pages
- Product page views
- Conversion rate
- Ratings and reviews
Product popularity changes over time, the season, and the availability of the product; so it’s best to re-calculate this daily.
Find a more in-depth description of product popularity here.
6. SERP click-through rate
The frequency users click the products listed on the SERP to get to the product page determines the click-through rate (CTR), which is an essential word to know when you’re talking eCommerce search terminology. If a user executes a query and clicks on a product on the SERP, this will boost the product’s relevancy in relation to that keyword.
This information is free feedback from your users. It shows that the product returned by the search engine is relevant to their search term. If people don’t click on products, especially those at the top of the SERP, this indicates these products are less relevant and thus will have a CTR of 0 or another low number.
Over time, these CTR values can help you root out products that don’t meet user intent for certain keywords. Similarly to the percentage of Search Exits, the CTR for a search term provides insight into the quality of the SERP and can help you optimize your site.
Positional Bias, another important word in the eCommerce terminology sphere, means users are more likely to click on a higher result than those listed later. This is not so common for eCommerce sites because results typically include an image, which makes it easy for users to skip irrelevant results.
7. Cart actions (add to cart)
To add to our list of eCommerce search terminology, cart actions refers to users adding certain product items to their cart. If a product has a high cart action rate, it means users frequently add it to their baskets – this also means that product will rank higher on your SERP (arguably one of the most important words in the eCommerce search terminology realm) as this indicates a high popularity and relevance to the executes query.
Cart actions are a much stronger signal of a product’s popularity than page views or SERP clicks are, because cart actions signify a user is ready to buy a certain product. You’re probably thinking there’s a flaw in this calculation – cart abandonment.
As you know, online shoppers don’t always purchase whatever is in their cart, which means that cart abandonment is high, so those cart actions happen much more frequently than purchases. And you’re right. That’s why it’s not enough to rely solely on cart actions (or on any other single metric) when calculating product popularity.
While cart abandonment is generally high, there are certain steps you can take to help reduce your site’s abandonment rate.
8. Attribute filters, faceted navigation
Attribute filters are parameters shoppers can use to refine search results. Some examples of frequently used filters are colour, price, category, and size. Attribute filters can be used on both the Search Results Page and on the category pages. Filters should be optimized so they are easy to use.
Using multiple attribute filters to refine the result list is also called Faceted Navigation or Faceted Search.
In the eCommerce search terminology world, there are “static” filters, such as price, which is a common property of every product in the web store. “Dynamic” filters are specific to products in certain categories and will only appear on the UX if the product result list of the search contains specific properties. For example, when you search for “notebook”, you will have “screen size” as a filter, which would not be applicable for when you search for hard drives. In that case, things like memory size would be more useful.
9. Related searches
As you can guess, related searches displays suggestions related to the initial query. These usually appear as keyword suggestions above or below results on the SERP or on 0-result pages. For example, if someone search for shoes, shoe cleaner might be a relevant related search suggestion. The most popular use of Related Searches is on 0-results pages or at the top and bottom of the SERP.
Related searches can also recommend products in place of a given keyword, or it can suggest complimentary products. In an eCommerce search scenario, the search engine often fails to return results for long tail keywords. This is an opportunity to show related products to the user even when their original intent is slightly different.
10. Cart abandonment
As far as eCommerce search terminology goes, cart abandonment happens when someone adds a product to their cart and doesn’t complete the purchase. Carts are abandoned much more frequently than users purchase everything they place in the cart.
So, as you can imagine, there are many techniques and technologies that can be used to re-target and convert users who have abandoned their carts. One great solution is ReCart, which has a blog that offers tips about creative re-targeting.
Web shoppers often use the cart as a shopping list before they go to the physical store – they use it as a place to compare prices and keep their spending in check. Since the cart is often used as storage, instead of actually for shopping, you can see why abandonment rates are so high.
11. Product ranking rules
There are many different ways to rank products on the SERP. Some people place the highest importance on the relevance between the title and the search query, or the relevance of the product description first, etc. In our experience, we have seen that product descriptions are often noisy, which leads to irrelevant results. If you’re determined to use product descriptions as a criteria for search, we recommend summarizing descriptions with just a few highly relevant key terms to boost the accuracy of the search.
If you have information about the items your web visitors are clicking on, what they add to their cart, what they actually buy, this is valuable and can be used when determining the ranking on your SERP. While these are useful, we don’t recommend sorting solely by popularity metrics because that will lead to inaccurate results.
A matching score (eCommerce search terminology for how accurately a product’s assets match with the search query) also needs to be taken into consideration. When considering how to rank products, it can also be a good idea to boost discounted or new products on the SERP.
If you’re thinking about personalizing your SERP, you can rank products based on historical user behaviour. For example, if someone has purchased Nike shoes from your shop in the past and they return and search for “shoes”, it would be a good idea to rank Nike shoes first as you already know he/she is interested in Nike.
This improves the user experience and increases conversion rates.
Talk about a win-win.
eCommerce search terminology is a complex language and these are just a few of the more common terms. If you’re looking to learn more, we’re happy to help. If you’re simply looking for more eCommerce (not search specific) terms, check out more here.