Understanding user behavior in the digital environment is paramount to refining and optimizing a marketing strategy or new implementation. Through smarter analytics, a business can make decisions based on a user’s true wants and needs – delivering a more controlled and authentic experience.
With the ability to gather data, equipped with these intelligent insights, the optimal technology can be implemented to achieve the ideal approach to a digital strategy – transforming big data into smart data.
Predictive Analytics
A traditional predictive analytics approach, also known as ‘forecasting’, is sufficient in giving key metrics, such as the number of active users, drop-off rates, and demographic breakdown. Predictive analytics uses historical data, allowing businesses to influence the future, by making customized predictions and using predictions to drive decisions.
Adaptive Analytics
The application of adaptive analytics is the next step in smarter analytics. Because nothing can truly predict the future, adaptive analytics comes in to continually adjust the predictive model, optimizing on an almost constant basis. The adaptive methodology of analytics is in it’s infancy, and thus, only implemented by a select group. Many current analytics programs use adaptive components, but not many are fully adaptive – yet.
For the the demanding user of today, a business will need more than just the numbers to keep up. A mixture of both predictive analytics and adaptive content must comprise a model based on previous data, combined with current data to better understand customers, products and competitors. It’s all about creating personal experiences, effectively targeting prospective users and maximizing marketing dollars.