“Our semantic search engine incorporates Natural Language Processing to allocate results based on the overall meaning of the query. Our expert linguists have built a proprietary lexicon that enables our technology to understand complex queries that include idioms, slang, synonyms, misspellings, abbreviations, jargon or symbols,” says Jordi Torras, CEO and Co-Founder of Inbenta. This unique search methodology enables the customers of Inbenta’s clients to find the information they need quickly, easily, and in an unprecedented way.
“For example, on a standard search engine, the phrases ‘run a test’ and ‘run a race’ differ in context and the difference is obvious to a person who is familiar with English, but not to the search engine,” explains Torras. However, Inbenta’s semantic search takes the analysis further by assessing the contextual meaning of words, allowing it to choose the best definition of the word “run” even when the syntax and the word itself are the same.
Through natural language and semantic search technologies, Inbenta's e-commerce search achieves a 40 percent higher than the industry standard search-to-cart rate, while its self-service technology prevents more than 65 percent of incoming tickets from reaching customer support agents. And as a preferred partner app of Zendesk, organizations using the cloud-based customer service platform providing support-ticket software, can be running Inbenta’s solutions in less than three weeks.
Our semantic search engine incorporates Natural Language Processing to allocate results based on the overall meaning of the query
One of Inbenta’s key differentiating factors is how the firm implements the software based on the Meaning-Text Theory, which conceives natural language from lexicon to semantics. This contributes immensely in the creation of detailed and specific descriptions of the lexical unit in several different languages by Inbenta’s specialized linguistics teams.
There are many instances where Inbenta has proved to be exceptionally beneficial to its clients, largely in directing its ticket deflection rate. One such illustration is through optimization of resources by increasing customer self-service in the midst of rapid growth, a problem faced by Coupa Software, one of the leading providers of cloud-based financial software. After implementing Inbenta’s solutions, the client witnessed positive outcomes. “During our trial period, without any additional configuration, we saw a 14 percent deflection rate. After additional configuration, we anticipated deflection to be 35 percent of incoming ticket volume,” Julian T. Pebbles, Senior Director of Global Customer Care, Coupa Software.
Inbenta is rapidly growing into one of the most prominent Natural Language Processing companies focused on improving the customer experience for online businesses. With positive growth reporting a 117 percent year-over-year increase in revenue for its U.S. segment, the company plans to continue supporting a vast array of customers.
“We set out with the goal for U.S. expansion only a few short years ago and thanks to a dedicated and capable team, we’ve exceeded client expectations,” says Torras. “Internationalization has always been a priority, particularly because customer support and search are universal challenges for every online business.”