In the general sense, sales data analytics is a process of generating actionable insights out of sales-related data to find ways to boost sales performance.

At Digital Insights Africa, we usually define 2 types of sales analytics:

• Descriptive sales analysis aims at interpreting historical sales data collected from a variety of sources to draw conclusions. Its results help you answer such questions as ‘What were the company’s total sales last quarter?’ or ‘What products/services were best-selling last month?’
• Predictive analytics serves to mine historical data to produce forecasts for the future, and it can be conducted with such advanced technologies as machine learning and artificial intelligence. To get an example of this sales analytics type, explore one of ScienceSoft’s projects, in which our experts helped a dairy manufacturer receive an accurate forecast with data science.

Improve customer experience

You can use sales analytics results to conduct profound customer segmentation and deliver personalized customer service. By analyzing your sales, you can also identify what of the customers’ needs are unmet and apply this knowledge to improve customers’ journeys and leverage up-selling and cross-selling, thus laying the groundwork for building customer loyalty.