Elasticsearch is an open-source analytics engine that offers full-text search and is incredibly scalable. It has a swift and dispersed nature. The best search results are delivered to your customers by integrating Elasticsearch features into your Magento 2 store. You can add the function to your Magento 2 store with the help of the Magento 2 Elasticsearch extension.
Online store owners can use this feature to quickly and easily store, search, and analyze a large amount of data. You can also track the behaviour of the customers coming onto your website by integrating the feature of Magento 2 Google Tag Manager.The results are delivered in milliseconds, making it the fastest search engine.
Note: Elasticsearch Engine v7.6 must already be installed on the system of the store owner before installing the Magento 2 Elastics search extension. Also, it must be running.
Highlighted Features of Magento 2 ElasticSearch
Auto Correct Search Suggestions
If customers accidentally type the wrong product name, they can search for the products using this feature.
Spell Correction in Search
For customer searches, the administrator can also specify different levels of spell-checking.
The admin can add numerous synonyms for the products and categories using Magento 2 Elasticsearch.
A customer can search for products, categories, or even pages with the help of the Magento 2 Elasticsearch extension.
According to the language of the Magento 2 store, the administrator can choose the appropriate language stemmer.
Multi-Match Query Search
A multi-match query can be as the search type by the admin. Customers can now look for products using the admin-created attributes for each product.
Simple Match Query Search
The customer can search for a product using its name and SKU if the admin chooses to use a simple match query as the search type.
Bulk Update Of Data On Elastic Server
The system administrator can reindex sizable amounts of data using the command-line tools.
Hyva Theme Compatible
The extension seamlessly integrates with the Hyva Theme, providing enhanced functionality and a cohesive user experience.
GraphQL has been strategically implemented to enhance the extension's functionality and improve its data querying capabilities.
Why do we need Magento 2 Elasticsearch Extension?
The ability to search for products on an e-commerce website is a very significant and demanding feature that customers frequently look for. The best search system should be made available to customers by the store owner. A slow result and an unsatisfactory search suggestion should not be provided by the e-commerce website's search engine.
As a result, your customers might have a negative experience, and you might even lose them. If you're trying to find the best way to give website visitors quick access to precise search results. Elasticsearch is then the best option for your store. Full-text searching is offered by the open-source and highly scalable Elasticsearch search engine.
It spreads quickly and naturally. You can give your customers a thorough and streamlined search experience by using the Magento 2 Elasticsearch extension. The search results will be more focused as a result, and the accuracy rate will rise. Additionally, it will make it possible for you to quickly search for and analyze a large amount of data.
Integrate Magento 2 Elasticsearch to Online Store
With the help of the Magento 2 Elastic search extension, integrating Elasticsearch into your store could be a simple process. As a front-end search type, you can choose between "multi-match query" and "simple match query."
The multi-match type is available in a drop-down list for the admin to choose. The most popular multi-match types are phrase and phrase prefixes, along with best fields, most fields, cross fields, and fields.
The multi-search query's admin can choose between "And" and "Or" operators. Additionally, to change the search term supplied by the customer, the store owner can choose from a variety of token filters.
- The Elasticsearch engine is simple to enable.
- Choose a language stemmer based on the language of your Magento 2 store.
- A minimum match percentage is set to decrease the number of poor matches in the search result.
- There are four different token filter types. They are the stop word filter, lowercase filter, elision filter, and synonym filter.
Modifying Indexes with the Magento 2 Elasticsearch Extension
After adding products to the store, it is necessary to index (i.e. store) the product data on the elastic server.
- According to the available index types, the data is stored on the elastic server.
- The admin can choose the pages, categories, and product index types here.
- By choosing the index type first, the admin can then choose the mode for that index type. Afterward, the admin needs to click on the Actions dropdown.
- Between "Update on Save" and "Update on Schedule," you have a choice.
- The administrator can now choose the index type and click the reindex link under the Action button.
- The admin can use the command-line function to perform a bulk update.
Features for search suggestions are already included in the Magento 2 Elastic search extension. The user can view related searches using a few search terms. Customers can find a fitness watch, fitness accessories, fitness equipment, etc. by typing "fit" into the search bar.
- The customer's product search is made simple by this feature. If you are looking for a product search via image you can check our Product Search Via Image for Magento 2. (Need to purchase separately).
- The customer can use this feature to view the related searches in addition to the item they were looking for.
- Customers can search categories, pages, or products with the help of this feature.
- They simply need to type the search term.
You can also look at Magento 2 Search Suggestion. While you are still typing, results are already displayed. It provides product recommendations that include the product's appearance and cost. Additionally, the search box displays popular items.
Auto Correct Search Results
The admin can set the spell checking at level 1 or level 2 using the Magento 2 Elasticsearch extension. This allows the Elasticsearch engine to analyze incorrectly entered search terms made by the user. The most relevant results to the search term are then displayed.
For instance, if a user accidentally typed "bakpak" when searching for a backpack. The search engine will then analyze the search term and display the Backpack results.
- The levels for spell-checking can be chosen by the admin.
- The customer can use this feature to search for the right product even if they typed the wrong spelling.
Search Filters in Magento 2 Elasticsearch Extension
The token filter is one of the search filter types that is used to change the customer-provided search term. Elasticsearch for Magento 2 supports four different categories of search filters.
- Synonym filter: A customer can search for products appropriately by using a group of synonyms that the admin can create.
- Elision filter: The following filter removes vowels, consonants, and syllables from the search term.
- Stop word filter: Stop words are eliminated from the search term using this filter.
- Lowercase filter: This filter normalizes token text to lowercase.
Character search filters are available in addition to token filters. Unwanted characters are eliminated from the search term. There are three of these:
- The HTML Strip Char Filter eliminates the HTML elements that the admin has chosen.
- The mapping Filter swaps out mapping keys for values. Therefore, it will eliminate any character from the mapping.
- Instead of mapping, the Pattern Replace Filter replaces patterns.
Filter(s)/Layered Navigation Support
For quicker search results, the Elasticsearch extension supports advanced layered navigation in Magento 2. The Elasticsearch engine will now handle all of the search requests generated by the category pages.
- Filter products quickly.
- Utilize various sliders, options, and filters.
- Works on category-specific pages.
- Takes advantage of Elasticsearch engine.
- It is simple to switch from the MySQL search engine to Elasticsearch.