AI Makes Search Relevance Critical
Delivering on search relevance will become more crucial — and more difficult — in the future, making artificial intelligence (AI) and machine learning (ML) more important, according to a survey conducted by Lucuidworks.
In fact, 52% of respondents to a study released this week said AI will become extremely important in the future to deliver relevant search results, 36% said very important, 8% think somewhat important, and 4% said not as important.
The data shows 88% of respondents believe that AI is very or extremely important in the future of search. AI has already revolutionized the field of search relevance by providing algorithms that can interpret the intent of a user’s query in a more human-like manner.
AI has become increasingly adept at analyzing large amounts of data to provide relevant results. Data shows AI has led to a significant improvement in the accuracy and effectiveness of search results, according to Lucidworks, which fielded the survey in January 2023 to more than fifty thousand search practitioners. Survey participants were in North America, Europe, and Asia Pacific.
In fact, 76% of respondents expect search relevance to become even more important in the future, and the majority believe delivering relevant search will become more difficult.
When asked to describe the biggest challenge to deliver highly-relevant search, participants pointed to too many stakeholders to make necessary changes, understanding how context and intent influence relevancy, and creating filters and data signals to narrow the search criteria to result in positive outcomes.
To deliver search relevance, 36% of participants cited collecting quality signal data; 34% said analyzing data using analytics reports; and 30% said taking corrective actions like tuning, recall, precision, ranking) from search relevance-related data
What’s required to deliver relevant search results? Some 37% said collecting quality signal data about search relevance, 36% said taking correct actions from search-related data, and 27% said analyzing search relevance-related data using analytics reports.
To improve search relevance, 39% said it requires different or better technology, 33% said different or better expert guidance and consulting, different or better professional development.
It will require improving signals, attaining accurate data, creating better analysis of user intent, increasing transparency of models, and helping AI and deep learning technology to accelerate relevance.
When it comes to the difficulty of delivering relevant searches in the future, 40% of respondents cited it will take more effort, 32% indicated it would take less effort, and 28% of respondents said it would take the same amount of effort.