Search engines such as Google, increasingly go for target group specific content. Google users should receive a result that is individually tailored to their search inquiry. Google is increasingly relying on the direct delivery of matching keywords and information that are directly displayed to the Google user in the search result.
Reliable test data is essential for modern, self-learning systems. Self-learning systems need them in order to be trained on human behavior patterns and the desired behavior of algorithms. A few examples of the applications are:
robots, autonomic driving systems, language recognition and search engines.
What decision would a human being make, how would they react, where would they expect what, and in what kind of categories do they think?
If you need valid information just ask the crowd. In this instance, crowdsourcing in connection with a full project realization service is an ideal tool to quickly obtain valid data.
Case study – Optimization of search engine results
We would like to present a few practical examples of how our “categorization” service can be used to make search engines within websites “smarter”, and thus improve the relevance of the search results.
To successfully operate an online shop you have to observe certain things. Among others, the shop and the content need to be updated at regulars intervals. This includes product descriptions as well as pictures of the products. However, many operators forget to categorize and tag their products.
Many shop operators make it easy on themselves or simply do not have the capacities – they describe their products with just a few short key points or use the product texts written by the manufacturer. However this approach does not boost sales or promote the Google ranking of the shop.