Why enhancing your site search matters
Search is a critical feature of ecommerce websites that enables customers to find products quickly and easily. However, just having a search box isn’t enough to gain the benefits of a fully optimized search. Current search capabilities in many ecommerce websites have limitations that can negatively impact the user experience, resulting in increased bounce rates and decreased sales.
What exactly is the impact? According to recently released data from Google Cloud, the costs of search abandonment are significant, with $2 trillion lost each year by businesses. Adding to that is the impact of the search functionality towards brand loyalty and shopper sentiment. For online businesses that fail to optimize their site search, the negative effects are often long-lasting (and sometimes permanent).
Therefore it is essential for businesses not only to resolve issues with their search, but also to seek new ways to enhance their ecommerce search to improve user experience and revenue. In this article, we’ll explore five ways to enhance search capabilities and provide examples of ecommerce sites that effectively implement these best practices.
Enhancing text search capabilities
Text search is the most common way users search for products on ecommerce websites. However, the text search capabilities for a majority of ecommerce sites have limitations that can frustrate users and thus negatively impact conversion rates.
Here are some interesting findings from Baymard regarding search terms:
- 61% of sites require users to search by the exact product type jargon the site uses, e.g. failing to return relevant products for a search such as “blow dryer” if “hair dryer” is used on the site.
- 46% don’t support thematic search queries such as “spring jacket” or “office chair”.
- 27% of sites won’t yield useful results if users misspell just a single character in a product title.
- 25% of sites don’t support non-product search queries, like “returns” or “order tracking”.
How can you resolve the above limitations?
Users, being humans, can be both predictable and unpredictable in their shopping behaviour. There is always the possibility of unique and unexpected search inputs. Therefore, site search engines should have the flexibility to interpret user search terms in different ways. Tried and true advanced features such as intelligent autocomplete, spelling corrections, fuzzy search, and synonym matching can significantly help users find what they want.
“23% of users use Google’s autocomplete suggestions.”
Online shoppers that use the search box know exactly what they want and have high intent to purchase that product. Conversion rates are higher for products offered by text searches compared to products offered by other recommender systems.
Implementing UI/UX best practices for the search bar
In addition to enhancing text search capabilities, implementing UI/UX best practices for search also play an important role. The size, design and placement of the search bar are main factors to consider. According to a study by UX Planet, the optimal location for the search bar is in the website header, and the minimum size of the search bar should be at least 27 characters wide.
Is bigger better? Yes, up to a certain extent. There are many variables at play in the overall UI/UX design of an ecommerce site. The most important point to this is that the search bar should be easy to spot. This is especially important for content-heavy websites.
Here are some best practices to consider for search bar placement and design:
- Use prominent and consistent design across all pages
- Avoid clutter in the search bar area, and give it breathing space.
- Some users prefer pressing ‘Enter’ while others prefer clicking on the search icon to submit their query. Provide several options so everyone can search the way they please.
- Use placeholder text in the search box to encourage users to search.
In addition to implementing the right search design, it is also essential to regularly monitor and test the search functionality so that it behaves as expected for the user. Search filter issues are one of the most critical errors that impact ecommerce sales.
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Faceted search
Facets in ecommerce is one of the most flexible and powerful features you can implement for your online business.
Faceted search, also known as faceted navigation, is a way of organizing and presenting search results. It is a way for users to easily drill down and refine search results based on specific attributes or facets, such as price, size, and colour. These facets can be selected or deselected at anytime by the user.
While the term “facets” is commonly used interchangeably with filters, they have important differences. Faceted navigation provides multiple filters to include one or more different attributes, whereas regular filtering analyzes a set of results and eliminates any content that does not meet the specific criteria. This makes faceted search a more flexible tool for users.
Zappos and Amazon are two great examples of ecommerce companies that effectively use facets to enhance user experience. As you can see above, Zappos does a great job of providing additional facet filter suggestions as you narrow your search and apply more filters.
Best practices for faceted search: Use clear and concise labels and avoid clutter in the search results area.
Natural language processing for better results
Natural language processing (NLP) is an advanced search capability that is already used by the biggest companies – Apple, Facebook, Amazon, etc. What is NLP?
Search engines like Google and Bing are no longer looking at keywords or phrases individually like a basic search engine would. They are now looking at phrases as a whole, assessing the intent and sentiment of the searchers. With NLP, users would type a search query in the same way they would say it aloud to a friend, and get a relevant answer. The benefit? This saves a lot of time and effort for the visitor and speeds up the buying process.
Baymard Institute has found that 61% of ecommerce sites require users to search using the exact product type jargon used on the site. NLP features can easily navigate this problem.
Leveraging machine learning and AI-powered search
There is plenty of hype surrounding the adoption of artificial intelligence, helped by the wave of generative AI technologies led by ChatGPT. For some companies, AI is an opportunistic endeavor, a term thrown out to entice customers for a promise unlikely to be fulfilled. However in the ecommerce industry, there is no doubt that AI and machine learning will play a significant role in the future of online businesses, with search being one of the most important usecase applications.
Tech’s next big thing is not exactly new. Machine learning has already been embedded in business processes of large ecommerce companies for many years now. With the increasing adoption of AI-powered search, we will find more and more businesses that can provide a more personalized and intuitive search experience for their customers.
Here are two ways to implement AI for better ecommerce search:
Personalization: Can you actually integrate ChatGPT to analyze user data and provide personalized search results based on browsing and purchase history? As of right now, no. Nevertheless, ecommerce platform providers have already started to offer machine learning capabilities so that online stores can continually improve their search functionality, and deliver personalized search experiences to their customers.
Search assistant and chatbots: Sephora uses AI-powered chatbots to help customers navigate the search process and provide recommendations based on their search queries. The potential here is huge, especially in terms of pushing customers to the next step in the customer journey, automating sales, and offering post-sales support.
Search: Shortcut to the destination
We looked at several ways to optimize ecommerce search capabilities, along with best practices that businesses can implement to provide a more personalized and intuitive search experience for their customers.
As technology advances, the potential for ecommerce search continues to expand. The possibilities of natural language processing and other AI-driven search solutions offer even greater room for improving the user experience.
While a great web navigation goes a long way for an ecommerce site, the focus should be on the search functionality. Why? Search is the shortcut to the destination. By enhancing ecommerce search capabilities, users can have greater success in finding the products they want to purchase. And in the case of online businesses it is about facilitating the best possible user experience for better conversions.
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Digital UX, writing about the latest ecommerce trends.