With more and more customers are going online for their regular shopping, the products on the ecommerce stores are also increasing. If the website structure is not proper, the customers may need to wander through many pages to find their desired product. This raises the need for a search mechanism in your store. The customers prefer to directly search their products in the store rather than finding through filtering or navigating the products.
A good search should be quick, making a better shopping experience and less frustrating to the customers. The search functionality allows the user to find what they require without any fuss. It is limited to improving the user experience and helps in a better conversion rate, and reduces abandoned cart rates. When a user searches for a product, he is more likely to purchase than that user who navigates for a product.
Consumers who use search are 200% more likely to get convert.
With an exemplary search service, businesses can learn more about what customers want by searching, information that can inform future business decisions.
The latest Magento 2.4 version series comes with a prevalent catalog search engine, Elasticsearch 7.6.x. It has become the default search of a Magento store. There were different catalog search engines in the previous versions, such as Elasticsearch 2.x, 5.x, 6.x; MySQL, Solr, Sphinx, and others. In today’s article, we will come to know the working of Magento search and the benefits of Elasticsearch for your Magento store.
How Magento Search Works?
After the installation of a search engine, it immediately starts working by indexing content on the site. In ecommerce stores, it implies creating a “list” of products along with their attributes. This is a continuous process. Whenever a new product is added to the site or removed, the “list” needs to be refreshed.
E.g., if you have an electronic gadgets store, and you add a new pair of “headphones” to your website. The catalog search engine will index things like its title, description, and price. It will also index some particularly associated attributes with the product, such as noise cancellation, microphone availability, etc.
When a user searches the store, the search engine will check the entered query, sort it with the list of products and their attributes, and bring back the most relevant result. Different search engines do this differently and have different features for interpreting and filtering more complex data.
Since JSON is a compelling and fast programming language, Elasticsearch lets the merchants deliver search results outside of just text-based strings. In the previous search engines, the functionality was minimal.
Also Read: Magento 2 Review for eCommerce Websites
What To Look In Search In Your Magento Store?
Regardless of whether you are using Elasticsearch, any other catalog search engine, or any third-party search, there are certain features on which you must focus. These are:
- How much time does the indexing and results compiling processes take? If it takes a lot of time, the search will be prolonged.
- Which languages can the search engine handle? First decide, which will be the best language for your store, and then make sure the chosen search engine provides support for it
- What natural language processing features are there? It is important for voice search and other features
- How the faceted search will work, and how detailed can the filters be?
- The accuracy of the search engine makes it worth trying the search engine to see if it provides accurate results.
Elasticsearch fulfills all these requirements, and that’s why Magento has made its default search engine.
Elasticsearch is currently the most popular search engine used by thousands of websites and ecommerce stores. It was originally developed in 2010 and become one of the biggest players in the search space, replacing popular rivals Solr and Sphinx.
It is a java-based document store that can store large numbers of JSON documents and speak to them natively. Thus, it can’t just handle text-based queries but can also understand advanced analytical queries, including interpreting numeric and geodata. Where Elasticsearch really shines is in its full support for Apache Lucene’s real-time search. From the user’s perspective, it implies ES can provide faster and more relevant search experiences. For ecommerce store owners, it will result in faster conversions.
Elasticsearch takes what was great about MySQL and makes it even better.
Suppose a user wants to buy a pair of headphones but only remembers the keyword “Master class” In the earlier MySQL search engines, the query “Master class” would return a huge chunk of irrelevant products. It will result in increased bounce rates as customers will go to the competitors for ease of use.
Elasticsearch optimizes this issue by allowing you to specify different criteria for which the customers may be searching beyond just the product name. It includes description, manufacturer detail, release date, etc.
With Elasticsearch, you can define what search results look like in detail. This makes Elasticsearch an ideal product search back-end for your ecommerce store due to its flexibility and performance.
Benefits Of Elasticsearch
After knowing the origin and working on Elasticsearch, let’s know about its benefits as well:
1. Extremely Fast Search
Speed plays a vital role in ecommerce. The users don’t just need a fast website that gets a load in less than a second and wants the results for their search query quickest. This requirement meets by Elasticsearch efficiently. Elasticsearch is a speedy catalog search engine, especially when searching through large product catalogs. It can run a search over millions of products in a matter of seconds, and it is rare to have this number of products in an ecommerce store.
A Fast search means fast shopping journeys which increases the chances of a purchase.
The speed at which Elasticsearch delivers results is usable for continuously updating results. The search begins as soon as users start typing their query; in fact, Elasticsearch searches faster than the users can type.
2. Accurate Search Results
For nearly 75% of the customers, the quality and relevancy of the search results can define whether or not they will purchase on an ecommerce store. Elasticsearch gives highly relevant search results even when the users aren’t sure about their fuzzy searching queries.
Fuzzy searching allows ecommerce stores to interpret customer queries by taking textual queries and interpreting them based on more than just 1-1 word comparisons. It uses the technique called the Damerau-Levenshtein distance formula. Fuzzy searching helps you to provide users with the right products from your catalog even when they mistype or search for a product that is not present in the catalog.
3. Easy To Use
Poor search results are more detrimental to your ecommerce store than no search results at all. However, considering the complex working of Elasticsearch, you may expect that it will be difficult to use, but it couldn’t be easier.
Indexing means importing information from a huge data source and storing it in an easy format. The indexing techniques of MySQL used to become a bottleneck. This increased the search time, and customers might leave the site.
Elasticsearch ships with sensible indexing defaults and return better results instantly. Thus, in Magento 2.4 or better version, search is almost immediately improved without any complicated configuration.
4. Improves User Experience
In today’s modern digital world, you have very little time to grab the attention of your customers. As per the research of Microsoft, the average user spends just 10 seconds on a webpage. Thus, you have only 10 seconds to deliver them what they want and, in this case, “Products”. If you miss this time frame and you are at risk of losing them to your competitors.
Elasticsearch is overlooked in regards to the UX, but search plays an important role in the user’s shopping journey. Searchers are twice as likely to purchase non-searchers. Key to the success of your store is driving this part of their journey to motivate your customers for purchase.
Elasticsearch improves UX by combining all the above-mentioned factors. Faster speed, accurate search results, ease of use improves the customers’ user experience.
5. Complex Search Query Support
While both Elasticsearch and Solr are based on Lucene query parsing, Elasticsearch comes with support for structured query DSL. It helps give results for more complex search queries, which can’t be managed by just Lucene query.
Elasticsearch also supports scoring scripts which are implemented through JS.
Pros & Cons of Elasticsearch
- Default search engine for Magento 2.4 and higher versions
- Faster search than Solr, MySQL, and Sphinx
- Developed while focusing on the ecommerce stores need
- Occupies more space due to indexing
- Can cost extra for hosting space
- Requires lengthy indexing
In today’s article, we have gone through all the aspects of Elasticsearch and how it can benefit your ecommerce. Although it has become the default search for Magento 2.4 and higher versions, many Magento store owners still use older versions. Thus, we recommend upgrading their Magento version and start using Elasticsearch. At Emizentech, the best Magento development company, we have expertise in upgrading Magento versions, developing Magento stores from scratch, implementing new features and functionalities, and much more. Let us know your requirements.