SearchUnify’s algorithms blend user data, machine learning and natural language understanding to learn on the go and present the most relevant results
Machine learning algorithms study search data across users, geo-locations and touchpoints, and the engine self-learns which results will lead to the most conversions for a given search query. The more you search, the smarter it gets!
Artificial Intelligence takes into account users’ access permissions, search history and journey on a platform, ensuring that the content they are served by our search engine is tailored to their needs. Users are more likely to click on results that are targeted to them.
SearchUnify uses NLU (Natural Language Understanding) to ascertain the context of each search query, rather than mapping results to search strings using only keywords. A robust library of synonyms, that is manually configurable as well as self-educating, drives cognitive processes that can identify precisely what you mean, just like a human being.
Our AI-driven chatbot, Sarah, can drive contextual conversations with customers and solve frequent queries effectively, making service operations cost-effective. Users can access search results in their chat windows too – benefitting from enhanced relevance in their interactions with Sarah.
Relevant suggestions and an enhanced auto-complete functionality ensure that users spend minimal effort to get to the answers they are looking for, enhancing their discovery experience.
A semantic knowledge graph is a segment of information, alongside search results, highlighting the most relevant search result at the top with other related queries and information at the bottom.
After implementing SearchUnify, the quality of support improved significantly as our support heroes could access relevant information from MadCap Flare inside Salesforce console. Similarly, customers could also access more relevant content within the Help Center. We got more than we asked for and for that a big shout out to the folks at SearchUnify.
For us, technology is just one piece of the puzzle while the vendor and its attitude makes up for the rest. If a vendor doesn’t have the responsiveness or desire to actually look beyond the product and think of a solution, the vendor-customer relationship may be short-lived. This is where the SearchUnify team delighted us with its agility and responsiveness.
As the Zuora Community Strategist, the level of metrics detail that SearchUnify provides for me in the administrator dashboard is impressive and useful. Not only does it give me a glimpse into the behavior of our community’s visitors so that we can create a better, more optimized experience for them, but it also highlights the content gaps so that my team can quickly add needed content in the Community. At the end of the day, we want all Zuora Community users to be able to get the answer they need, as quickly as possible.
The reason we chose SearchUnify over the other enterprise search products is its speed and ease of deployment. It’s an amazingly flexible search product that provides cross-channel content search functionality. I particularly love the fact that we are able to securely share relevant information from all of our portals, whether public or private. Above all, the ability to analyze users’ search behavior and our content’s effectiveness is something that keeps us one step ahead of user expectations.