Tobias Mérinat Semantic Search Query Analysis
Bike or bicycle? Cookie or biscuit? Comprehensively analyzing search terms is a demanding task. Methods derived from machine learning and natural language processing enable variations in how search terms are written, synonyms and typing errors to be intercepted. Search requests can be meaningfully grouped together and analyzed, making the language of the customer visible.
Your added value in terms of trade
The bundling of synonymous or similar search terms allows a more exact analysis of needs, better content marketing, recognition of trends, ad word optimization, uncovering of gaps in the services offered, and enhanced cross- and upselling.
Details on the speaker
A Machine Learning Engineer at the Lucerne University of Applied Sciences and Arts, Tobias Mérinat passionately implements data-based industrial projects and works freelance as a consultant. He studied IT and mathematics and completed an MAS MTEC at the ETH Zurich. He has been gathering experience in various industries for 20 years as a software developer, project manager and data scientist.