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Decoding Magento 2's search_query Table: Powering Personalized Experiences and Influencing Product Popularity

Decoding Magento 2’s search_query Table: Powering Personalized Experiences and Influencing Product Popularity

Magento 2's search_query table significantly benefits the eCommerce industry by improving user experiences and tracking product demand. This database stores customer search queries which is then used to personalize customer suggestions and measure product popularity. The table comprises important entities such as query_text (exact search terms), num_results (count of same terms), and popularity (popular search words). This data, essentially reflecting customer intent and product demand, is used to enhance future customer interactions. Also, by using past search data, the search_query table helps in suggesting products to new customers, boosting personalization and navigation. However, clearing or altering this table can result in data loss that impacts user experiences. Pioneering eCommerce solution companies, like Meetanshi, assist in handling this table's complexities to further optimize the eCommerce experience.

Full article here: https://ipllfirm.com/all-insights/news-and-articles/decoding-magento-2s-search_query-table-powering-personalized-experiences-and-influencing-product-popularity/