Unlock powerful self-service and support outcomes for your business by tapping into user data with artificial intelligence
AI-powered search uses Natural Language Processing (NLP), semantic processing, and Machine Learning (ML) algorithms to surface extremely relevant search results. It turns your platform into a one-stop-shop for relevant information, irrespective of its use case. Tweak relevancy of search results for users by manually tuning content based on keywords, popularity, date created, etc.
Take personalization to the next level with search-powered recommendations that leverage ML to adapt to a users’ search behaviour to recommend content that resonates with their interest and the level of experience they have with the product.
Give your users another medium to harness the power of search with AI-powered chatbots built on the same intelligence as your search engine. The bot powered by NLU and search insights can understand the intent behind a message or a question, to personalize conversations based on a user’s behavior & search history.
Community helper, the new age ‘always on’ bot, is a godsend for community managers. Built on an AI-fueled search framework, it auto-tags content so that it’s easily discoverable. It constantly monitors and auto-responds to community discussions, keeping engagement in check. And in case it’s unable to find an apt response, it routes the queries to community experts.
Empower your support teams with case-resolving content and shorten mean-time to resolve a case. SearchUnify’s agent helper classifies existing cases in your support database intelligently and provides all the information like top articles, SMEs and similar cases. It also provides insights into the customer journey and predicts escalation chances, so that support agents can come up with better responses.
‘Hear’ warning signs from customers based on the keywords used by them in community discussions, support queries, or social media. AI-driven sentiment analysis gives an overview of customer opinions which puts you in a better position to curate positive brand experiences. It also helps you identify potential issues and deliver proactive support.
Every customer is unique, so treat them likewise. AI-driven search does the heavy lifting by analyzing user behavior such as searches, clicks, views, upvoted discussions, etc., and self-learning with every interaction. It then generates personalized recommendation widgets and displays dynamic UIs to heighten engagement.
Intelligent search maps the semantic relations of words so that when a user searches for something, the search engine also considers synonyms and other related words. It leverages NLP to–identify duplicate content, auto-suggest while a user still types, and understand actual intent behind the keywords typed–to elevate user experience manifolds.
Inform your archiving strategy with an in-built content duplicacy checker that leverages NLP to identify similar words including synonyms within your content pieces to help you discover duplicate content in your repositories.
Harness the power of AI to identify intent faster with a search engine that classifies queries as a question or information. For example, if the engine detects that the user has asked a question, the result that shows up can be a featured snippet with detailed points on how to resolve the query without the user having to click on the article.
Make sure the correct result is delivered every time with a built-in auto-synonym factory that takes into account historical searches and clicks to identify synonyms and possible errors in spellings when your users type in a query.
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