It’s a story as old as the Internet itself: how do you find the one piece of knowledge or content you’re seeking among all the world’s information? For nearly two decades, search engines and crawlers have filled the void, retrieving information and data scattered throughout the Internet.
On a smaller scale, companies face the same challenge on a daily basis. In their own universes, organizations need to make information about their products and services easier to find for customers, partners, and employees alike. Such was the challenge for Snowflake Computing.
New solution, new challenges
Snowflake Computing burst onto the scene with a next generation data warehouse built for the cloud. Snowflake’s service helps companies eliminate data silos that restrict analytics, create complexity, and increase the total cost of ownership of data. Companies in a variety of industries and geographies have adopted the solution as an alternative to conventional data warehouses.
Since its launch, Snowflake has created hundreds of pages and many pieces of content, from documentation to videos, including basic product overviews, support articles, manuals, training materials, and specific reference libraries. However, those documents were stored in different repositories based on the intended audience and purpose.
Users often had difficulty finding exactly the information they wanted because the search functions that came with the various tools or systems used were limited to straight text searches and only within a specific repository. The result: increasing volumes of unsuccessful searches that triggered more questions from their users, often in the form of support tickets.
Cross-platform Natural Language Search for greater accuracy, fewer support questions
Snowflake turned to Inbenta’s AI-powered Natural Language Processing (NLP) Search to simplify and unify its search and to reduce the number of user questions. Inbenta was chosen in part because it provided integrations with Snowflake’s various systems as well as a service-based model tailored to the needs of a growing business.
Inbenta supports complex phrase searches across all indexed content, such as the information stored in Snowflake’s Zendesk-based Help Center and Snowflake’s documentation site, regardless of where it’s stored. The NLP search technology understands a user’s intent and the meaning of their search instead of searching by keyword text, delivering fast and accurate responses that help Snowflake customers, partners, and employees find exactly what they’re looking for without intervention from the support team.
The move to an NLP search solution simplified searches across Snowflake’s various repositories, resulting in more successful user searches and fewer questions—even from internal users. With users relying much less on help from the support or documentation teams to find whichever document or article they want, both they and support staff can spend more time on higher value activities than resolving search issues. And, as the company adds self-service sales capabilities, Inbenta’s scalable technologies will help to ensure that Snowflake can reliably and comfortably meet increasing customer needs for product information and documentation with their current resources.