Understanding search behavior in different market segments helps SEOs adapt an SEO strategy to real user behavior and to seize opportunities when certain types of searches take off–or drop off.
In SEO, tracking search trends requires the collection and analysis of additional data, usually from keyword trackers, Google trends, or even social media. In some cases, historical data for crawls and site performance can also be useful. Because of the volumes of data involved, it’s usually best to look for an API rather than trying to collect and process the data manually.
Once collected, the data have to be analyzed to understand the trend. Machine learning and data visualization are two techniques used in market trend analysis. For example, Oncrawl Labs offers a project on long-tail keyword performance prediction, which uses machine learning to develop a sensitivity to patterns in long-tail searches. This is then used to project past patterns into the future and predict new trends.