Forecasting Website Attendance
Our most remarkable project related to data science involved forecasting website attendance to adjust and improve SEO-strategy.
This project relied on the analysis of multiple behavioral models and used several methods of Data Mining to classify and find out the most appropriate way of forecasting.
For example, we are using methods of analyzing Time Series Forecasting to determine incoming traffic according to its timestamps. This is useful to make predictions of the future attendance and reduce uncertainty, connected, for example, with launching a new site, products or changes to marketing strategy.
Another example is the Search For Dependencies method. It may be useful, for example, in finding some explicit and implicit relations between traffic intensity and the time of day.
It is obvious that each method gives only approximate results and some uncertainty is still here, due to a constant changes to search engines algorithms, however, data science makes forecasting rely more on comprehensive data analysis coupled with mathematical calculations rather than just on primitive statistics.
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