While the value of external search optimization (SEO) is widely known, many ecommerce websites overlook the value of the hidden gem that is internal search engines. Only 15% of businesses dedicate resources into perfecting the site search. This is worrying as 68% of customers do not return to an ecommerce website that provided a bad search experience.
When building an internal search engine, businesses should provide a search experience that matches their products and audience. This requires configuring your search engine’s ranking rules, synonyms, faceted search, and more.
When we designed our Search APIs at Medusa, we abstracted the search functionalities to allow developers and businesses to either implement custom logic, or, more commonly, use search services like MeiliSearch or Algolia. These services continuously optimize their search functionalities to ensure that your ecommerce website provides a good search experience.
This article explains some tips for configuring and optimizing your search engine to provide a better search experience for your customers.
What is Medusa? Medusa provides bespoke, modular and open commerce infrastructure for developers. Medusa’s different components and APIs are built in abstract layers, making it easier for developers to customize the core functionalities for different business use cases.
Some Search Statistics
If you’re unsure of the importance of internal search engines, here are some statistics that emphasize their effect on ecommerce sales:
- 43% of customers on retail ecommerce websites go straight to the internal search engine.
- Internal search engines are widely used by the most valuable customers; customers that use the internal search engine are 2.4 times more likely to make a purchase.
- Customers that use the internal search engine spend 2.6 more times than those who don’t search.
- 39% of customers are influenced to make purchase by relevant search results.
Tips to Optimize Internal Search Engines
Ranking rules are used to decide which search result shows first. A basic approach would show the results having the same exact words in the name of the product first. Although this is fine, but in a lot of cases you must take into account other attributes such as the category of the product or its stock amount.
You might also want to boost the ranking of some products over others due to a marketing strategy. For example, you might want to show products having a discount higher than those without a discount.
Defining your ranking rules can help customers find exactly what they need and influence them to make a purchase.
Customers often make typos while searching. If a search engine shows them results based on their exact query, they’ll typically land on no results pages, which leads them to making no purchase.
An internal search engine must be optimized to detect and resolve typos, providing the customer with the results they’re looking for. Most search engine services utilize machine learning to ensure typo tolerance and provide a better search experience.
Search analytics can be a minefield of valuable information about your customers. It can help you understand what are the most searched for items. Coupled with other analytics you have related to purchases, you can figure out which of these items result from search results and, in turn, boost their ranking.
Search analytics can also help you figure out which queries lead to no search results. This can be useful to understand what type of products your customers are looking for in your ecommerce website. You can also utilize this to define related results for these search queries.
Often, multiple words have a similar meaning. For example, some customers might use “shirt” and “t-shirt” interchangeably. This can also be affected by different customer cultures or locations.
A good search engine should provide synonyms that would allow the customers to land on the same search results, despite which synonym they use. Obviously, it would be difficult to cater to every possible synonym. You can utilize here the search analytics mentioned earlier to figure out what synonyms are necessary to define.
Parsing Search Queries
According to Google’s 2022 Year in Review, there’s a +75% year-on-year (YOY) increase in search queries related to saving money, such as “cheap electric cars”. Some customers might use other search queries, such as “shirts under $20”.
Although it might not be highly necessary to account for these search queries, parsing them and showing the customer exactly what they need can show customers that you understand them. Consequently, it can lead to a better search experience.
Faceted search enables users to narrow down their search queries by providing filters that allow them to be more specific.
For instance, by using this search feature, someone looking for a Batman shirt can filter out books and videos about the superhero and focus the search on the desired product.
Filters can be as basic as showing different available categories, and can extend to adding more advanced choices such as material, brand, colors, sizes, and more.
A/B testing is the process of comparing the outcome or analytics two different versions of a feature or interfaces. In the context of internal search engines, A/B testing can be used to figure out which configurations drive more sales.
For example, if you have two ranking rules, and you’re unsure which one would be better for your customers, you can use A/B testing to figure that out.
There are many ways to run A/B testing. Algolia provides steps to run an A/B test for search relevance. Search services may provide this functionality differently.
Optimized No-Results Page
Despite all the configurations and optimizations you may put in place to improve your internal search engine, it’s still inevitable that the customer might land on a no-results page. Instead of trying to avoid the reality of a no-results page, you can embrace and utilize it for other opportunities.
A no-results page can be optimized to include the following:
- Recommended results: You can show results for a collection of products that drive sales. For example, discounted products or best-selling products.
- Suggested queries: You can show queries that are similar to the customer’s query, or queries you’re sure will provide many results.
- Personalized suggestions: You can use analytics related to the customer to provide suggestions. For example, you can show results based on the customer’s previous search results. You can also show results that are popular in the customer’s region or location.
Search Metrics to Measure
Search metrics and analytics can be key in optimizing your internal search engine. They can help you better understand your customer and decide on new configurations if necessary.
Some search metrics that you should measure are:
- Most Searched Products: this metric can help you understand what your customers look for the most in your website. It can be an opportunity to find new products for your store.
- Searched Products Leading to Highest Conversions: just because a product is searched for the most does not mean it’s the product that leads to conversion and revenue. Combining the Most Searched Products metric with the Conversion metric can be useful to decide on ranking rules.
- New Searches: new searches wouldn’t rank high in the Most Searched Products metric, but they can provide useful insights to the new and upcoming trends in your industry.
- No Result Searches: this metric shows which search queries lead to no-result pages. This can be used to define synonyms or search suggestions.
Optimizing your internal search engine can be a powerful tool to improve your ecommerce sales. By carefully configuring your ranking rules, typo tolerance, synonyms, faceted search, and parsing search queries, you can provide a better search experience for your customers.
Additionally, by measuring search metrics such as Most Searched Products, Searched Products Leading to Highest Conversions, New Searches, and No Result Searches, you can better understand your customer’s needs and optimize your search engine accordingly.
By implementing these tips, you can be sure of providing an improved internal search engine experience for your customers.
Medusa is a composable commerce engine that allows you to integrate whichever search engine you find most suitable for you. If you’re interested in Medusa, check out the quickstart guide.
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