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Ways Machine Learning Helps Attain Smarter Results from Enterprise Search
According to the survey, customers demand personalized engagement based on previous encounters and a consistent brand experience.
Fremont, CA: Investing in AI technology is one of support leaders' top goals throughout the world. According to the report, AI use in customer service is expected to increase by 143 percent in the next 18 months.
According to the survey, customers demand personalized engagement based on previous encounters and a consistent brand experience. To achieve these expectations, businesses have realized that they must use consumer data to enhance products, provide better support, and simplify self-service.
It's where machine learning comes into play. ML is a technique of AI that allows systems to learn and develop independently without having to be explicitly programmed.
How Machine Learning Affects Enterprise Search
Knowledge Discovery is made easier with relevant results
As the name implies, machine learning algorithms are continually evolving and becoming wiser over time. Before deciding whether the search results are the most relevant, they consider several factors. Assessing the user's search history, articles that deflect cases, user feedback or page rating, query intent, page visits, and so on are some of these criteria. Smart search solutions adjust search results depending on these criteria, ensuring that the most relevant results are displayed first.
Personalization is taken to the next level
Users receive proactive recommendations from intelligent search engines. They can utilize machine learning to learn and tailor these recommendations by analyzing the user's search behavior and history. A smart search system can take all of this data from the search query and utilize it to pre-select the most relevant aspects for customers, improving personalization and user experience.
Chatbots with Strengths that Complement Search
Thanks to machine learning, humans are getting closer to humanizing replies to user inquiries. For example, the last time users likely spoke with someone on a support site, it was a chatbot rather than a real workforce.
Chatbots powered by AI is a useful addition to search. However, some community members may not want to utilize the search box to obtain answers and assist themselves.