In order to enter into a new market, businesses must have an effective product adaptation strategy. This strategy is essentially the knowledge of what part of a product or service must be changed in order to appeal to local customers.
Adaptation differs from localization in that the former changes only surface-level factors.
Sales forecasting is the system by which future sales volumes are estimated—at what price, during which time, and in which market. Product performance forecasting enables businesses to make informed decisions in both the short term and the long term. Machine learning software is continually improved, providing businesses with better analysis all the time—faster and more reliably than manual methods.
In the current era, consumers expect the firms they engage with to provide personalized service and offers. They believe that companies have the technological tools to analyze their specific needs and can perform this task with minimal effort, so businesses should develop such ability.
One may imagine that this kind of mass operation will need some resources and financial investment but by implementing artificial intelligence and automated processes, this capability can be readily available for any business.
Traditionally, personalization was focused on a set of rules based on existing data. The firms used to collect data in advance without any consideration for real time data but now better and much faster results can be obtained by using AI that allows businesses to conduct profiling and real-time analysis to optimize each conversion. This process is defined as Predictive Personalization and is driven by Machine Learning.