Industry tag: DATABASE MANAGEMENT
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Query-Item Matching
Irrelevant search results frustrate e-commerce customers. According to Forrester Research, nearly 50% of potential purchases on eCommerce sites are lost because users can’t find what they are searching for.
Idea
Developers designed a classifier to increase the accuracy of results provided by the search engine to customer queries and thus improve search relevance while reducing friction points in the e-commerce customer journey.
Pain / Challenges
Customer queries and indexed product information are often mismatched. For instance, a customer may search “clog remover” when the retailer labels the product as “drain auger”. Besides, slight vocabulary differences also change the search intent.
Solution: Product Search Model Training
Our team focused on training the model to identify query-model mismatches. The annotator is presented with a customer query and related results provided by the search engine. The quality of the match between the query and its results is evaluated and judged if the query and results are an exact match or not. The annotator marks “Other” when there is doubt in the decision.
Results
26% F-Score
17% Area under PR curve
40% Increase in customer engagement
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