According to a Forrester research report,
So it is essential to carefully setup search to offer better user experience to customers and thus increasing their sales.
SearchSpring helps online stores grow by making it easier for shoppers to find the products they want through search and navigation. It provides relevant and personalized search results.
The experience from start to finish is powered by the relevancy engine which analyses and understands aggregate user behavior and even picks out individual behaviors to deliver a unique and relevant experience for every shopper.
This creates an unbelievable experience that increases sales and keeps customers coming back.
On average, just after 3 months of integration, retailers see a boost of 15% conversion rate and 10% reduction in call center volumes giving CSR more time with each customer to develop a relationship and trust.
Our capability to identify customer search intent and context with features like measurement detection, character recognition, product typing, and more.
A module that appears when a user starts typing in the search box and helps the user to locate what they’re looking for in real time with product and search suggestions along with faceting options.
Sequence the display of products based on how the data matches compared to our predefined rules, e.g. displaying new products first and sort those by the highest margin.
The merchandising tool which provides merchants with the ability to customize how specific search pages look and behave completely.
Search Insights leverage SearchSpring’s search tracking data, while also examining some supplemental Google Analytics data to present crucial metrics breakdowns for searches performed on our site.
A high-level overview of our site’s connectivity status, and reports that provide visualizations & breakdowns of our site’s search performance.
AI is primarily being used today to make search and merchandising algorithms smarter. A search bar that’s truly taking advantage of the next-generation AI technology will better understand search queries and will return far superior results.
Conventional keyword-based search systems will take a basic search for something like “blue Levis jeans” and return outcomes for any products that contain the words “blue”, “Levis” and “jeans”. In this search example, rather than seeing products that match the query, results will usually contain a seemingly arbitrary collection of jeans, Levis branded items and other items that contain these words in their searchable fields.
While some custom work can refine the relevancy of the search results, it can never completely fix the inherent issue that the algorithm does not understand what the shopper wants.
AI search engines deal with this issue with tailored algorithms that read the product data in a retailer’s database and make an understanding of what each item is. In this scenario, the engine figures out the association between each of the words in the query. This empowers the AI search engine to return only the products that the shopper wants, rather than a mixture of products that are relevant or irrelevant to the shopper’s search.
When analyzing search performance before and after integrating AI into the search bars, the average retailer sees a 22% boost in search-driven revenue.
Royal Cyber has certified Ecommerce consultants to guide you to deliver a successful online store and provide a revolutionary Ecommerce site search.
For more details, visit the below URL:https://www.royalcyber.com/technologies/ibm-websphere-commerce