Onsite search is long known as a significant contributor to online sales. According to Econsultancy, visitors who perform a search convert at 4.63% - 1.8 times more effectively than the website's average. In one of our case studies, visits with search account for 7% of the website traffic, but have a 6-times better conversion rate than those without search.
People visit an eCommerce store with various intentions. To make them close the deal, online merchants need to meet the distinct intent of different shoppers’ personas. Today, we'll introduce you to some common types of eCommerce customers and focus on how to optimize your website for an eCommerce customer journey with site search.
Every eCommerce buyer is different. Some people come with a specific item in mind. Others are making purchasing decisions. Some come to pass the time. From product photos to descriptions to registration and checkout, every aspect of an eCommerce site is critical to its success. Distinct categories of shoppers, on the other hand, rely on different aspects of the site.
Identifying various user types may assist you in conversion rate optimization by creating usable and beneficial experiences for all sorts of customers. The E-Commerce User Experience report series done by Nielsen Norman Group uncovered numerous different categories of shoppers, each with their own set of requirements. Still, we can see that all types of eCommerce shoppers are likely to use the site search in their shopping journey.
Buying intent
A product in mind
What they want
What you should provide
Product focused
High
Yes
Browsers
Low - Medium
No
Researchers
Medium - High
Yes but unclear
Bargain hunters
Medium
Yes but highly flexible
One-time shoppers
High
Yes, usually gifts, cards
Searchers begin their online shopping session with a well-defined product or an idea of the product in mind. As a result, speed plays an important role in sealing a deal. Most shoppers aren't patient enough to look at page 2 of the search results as they expect to get the right product from the first five positions.
They may start searching on external search engines like Google and continue with the internal search if the search engine result pages don't surface what they want. To be honest, it may not be the search systems' fault. A rough estimate from available data on NNG proved that searchers are actually not good at searching. They can misspell the keywords, use wrong grammar, add special characters to the queries, and so on. This makes simple search engines stir up ineffective and irrelevant results, then irritating the online shoppers. However, it is understandable because we can’t expect the shoppers to know the logic and algorithms behind our search engines. Therefore, it's the merchants' responsibility to make the site search smarter so it can process natural language.
Ecommerce shoppers alternate between searching and browsing on occasion. They begin by exploring a website and clicking on menus, categories, and other pages. If the experience is up to their expectations, they will move on to looking for specific things. That's why it's beneficial to have “browsers” look at your website.
These are individuals who choose to spend time on your website, with your business, and with your brand. Your store serves as a source of pleasure and inspiration for them. There's a big chance you can convert these browsers into buyers. They'll be more likely to think of your site – or your business – when they're ready to buy if they have a continuous positive experience with your online store.
On the other hand, people can switch from searching to browsing too. This usually happens when customers search for a broad term, “party dress” for example. They may then be taken to a collection or category page for this kind of product and explore the most well-matched results using filters and sorting options.
With these distinct shopping behaviors, how can you design your internal search to serve your customers to the utmost? Keep scrolling down to discover.
Autocomplete/ Autosuggestion/ Predictive search
This is a feature in which the application predicts the rest of a word a user is typing and thus completes it automatically. The autocomplete results are shown on a dropdown called the Instant search widget.
Site-wide search/ Content Search/ Federated Search/ Universal Search
This allows shoppers to search many data sources, including product data (SKUs, metafields, tags, etc) and non-product data in various forms (how-to guides, pages, blog posts), at the same time.
Spell check and Fallback Search (“Did you mean” Suggestions)
Spell check helps to return the correct search results for misspelled keywords with a minimal number of mistyped letters.
Fallback search is the act of offering alternative query suggestions that show up at the top of a search results page. Most often found on zero-result pages.
Search stemming and Case sensitivity
Search stemming takes into account the common stem of different words to yield results for keywords with the same stem.
Case sensitivity allows the search engine to treat uppercase and lowercase as equivalent.
Redirects
Redirect is to direct shoppers to a certain page on specific keywords instead of showing results.
Synonyms and Stop words
Synonyms are words that have search results tied together. It makes search results come back for products that might not have one of the words in its searchable data,
Stop words are words that are filtered out, “ignored”, or “muted” from the search data.
Natural Language Processing (Semantic Search)
Natural language processing is to determine customer search intent and context, with features like measurement detection, character recognition, product typing, and more.
Facets (Faceted Search or Facet Filters)
Faceted search lets users manually refine their searches by multiple dimensions at the same time (e.g. size, color, material, etc.).
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Merchandising (Product Promotion or Boosting Rules)
This feature is to select and prioritize the products you want in the search results. As mentioned above, searchers pay the most attention to the first five positions. Hence, using merchandising is a great way to showcase your best-selling items and get more sales.
Personalization (Personalized Search)
This allows for the promotion of products that a customer has already interacted with. Trending and recently viewed products are promoted to the customer when they click on the search box and activate the search function.
Self-learning Search
It makes use of machine learning capabilities that learn from the search behavior of previous site visitors. The results and experience can then be automatically improved for everyone.
Voice search, Visual/ Image search, Geo search
Spoken voice by humans and real-world images can be used to create search commands instead of typing with voice search and visual search.
Geo search is to filter and sort results by location-based queries, by distance, or around specific geographical locations.
| Explore:Useful and practical tips for site search UI/UX
Due to their proportion and the conversion rate, online merchants should improve the whole shopping experience of site searchers. Understanding site searchers and following our suggestions will make sure you are providing the best search service on the eCommerce customer journey.
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