What is Sobooster Search & Filter?

Sobooster Search & Filter is a powerful tool that helps eCommerce sites improve customer experience and boost sales. Our advanced search feature is designed to deliver fast and accurate results, just like customers expect from industry giants like Amazon and eBay. With Sobooster, you can reduce bounce rates, increase conversions, and provide a smooth and seamless search experience that keeps customers coming back. Don't let the competition get ahead – give your site the edge it needs to succeed with Sobooster Search & Filter.

How does Sobooster Search & Filter work?

Our search system utilizes state-of-the-art AI technologies, including natural language processing, text analytics, and machine learning. This enables us to deliver highly accurate search results and efficiently guide customers to the products they are looking for, resulting in faster search experiences. By optimizing the search process, we contribute to driving conversions and boosting sales for eCommerce sites.

Natural Language Processing (NLP)

Natural Language Processing encompasses both Natural Language Understanding and Natural Language Generation, enabling computers to interpret and comprehend human communication.

Sobooster Search & Filter utilizes NLP algorithms to extract information from user queries. Its processing systems can analyze vast amounts of text-based data in an unbiased and consistent manner. In the online world, shoppers expect to enter a search query and receive relevant suggestions instantly based on their purchase intent. This type of interaction requires data analysis at a speed and scale that is unsustainable for humans alone. NLP lightens the workload by continuously learning and developing insights into customer intent and preferences. Today, NLP is essential for online businesses to deliver exceptional search experiences to their customers.

Machine learning

Machine learning utilizes intricate data analysis to enhance performance and predictions without relying on explicit programming. This technique is inspired by the human brain's ability to recognize patterns in various layers of data, known as neural networks. When integrated with Sobooster Search & Filter, machine learning can significantly improve the understanding of user queries and identification of search rankings. By connecting keywords with customer search behavior and product data, such as click rates, conversion rates, inventory, and margins, the system is empowered with predictive analytics to better understand the customer journey and factors that motivate them to make purchases.

Text analytics

Text analytics is the process of analyzing the content and extracting meaningful metadata from unstructured text data for business purposes. It lets your users search and filter results based on the phrases returned from the analysis phase.

What can Sobooster Search & Filter do?

Smart search and auto-suggestion

Improve customer satisfaction by providing instant search results with keyword highlighting, auto-complete, typo tolerance, and relevant suggestions.

Sobooster Search & Filter enhances user experience by predicting search intent and offering a drop-down list of suggestions and product matches that update as users input more characters. Auto-complete suggestions not only expedite the typing process but also streamline the buying journey, enabling customers to directly access product pages and checkout with just one click.

Powered by AI and machine learning technology, the engine continuously improves its intelligence and emulates human thinking. It delivers precise and meaningful search results by not only identifying keywords but also understanding query intent and contextual meaning. For instance, if a query for "brown jacket" is expected to match a product with two color variants, black and brown, the system will display the relevant product image corresponding to the color "brown".

Key Features:

• Typo tolerance: Accounts for users' misspellings or typographical errors by matching words with similar spellings to provide relevant search results.
• Synonym search: Allows for user input variations by setting up synonyms, enabling the search tool to identify related terms. For example, if a user searches for "settee", the system can be configured to also recognize "sofa", "couch", and "fawn".

Dynamic Product Filtering for the collections & search result pages

Help customers navigate through thousands of products and find the most relevant ones that match their needs.

• Customize filter options: Filter products by Collections, Vendor, Product Type, Product Variants, Tag, Rating, Price, Availability, and Metafield. Optimize the user experience (UX) design for your website by choosing how to display the attribute filters on the front-end, such as Checkbox, List, Color Swatches, Sliders, and more.
• Dynamic Product Filtering: Easily set up different filter groups and offer the appropriate options for various collections. When users interact with search results, available filters dynamically update to reflect the attributes of the remaining results.
• Values Merging: Group similar instances under a standardized value. For example, you can combine 'Electric blue', 'Dark blue', 'Light blue', and 'Navy' into a standard global color like 'Blue'.
• Attribute-based Breadcrumbs: Show customers the refinement attributes they have chosen to narrow down the search results. They can remove the selection by clicking on the icon.

Search Merchandising for business metrics

Optimize your business goals by strategically displaying items within search queries or categories. Take advantage of functionalities such as 'pin,' 'boost,' 'bury,' 'include,' and 'exclude' to promote higher-margin products and maximize revenue, or to hide irrelevant items and low-stock products. This efficient approach engages shoppers and guides them towards making a purchase.

Site Search Analytics

Leverage the power of data-driven insights. Through detailed analytics on 'Top search queries', 'No results found', and 'Top click', you gain a deeper understanding of your customers' search behavior. This allows you to make informed decisions on inventory management, product naming, and synonym optimization for relevant key terms.