Business analytics certification is an advanced analytics course that enables professionals to make accurate predictions about future events based on historical data and predictive intelligence.``
In this article, I have specifically mentioned the key skills that would prove instrumental in your rise as a business analytics leader in a competitive job market.
Customer Data Management
A very important part of predictive intelligence arises from the need to segment customer profiles into identifiable segments. Also called as customer segmentation, customer data management offers the ability to stay focused on markets that cater to specific set or groups of customers. For example, female population above the age groups of 14 years and below 50 years, who are more likely to buy a sanitary periods pad.
Or, boy aged above 14 years who are more likely to buy or shop for beard and face cleaning products. The knowledge of customer data segmentation using Big Data, user profiling and social media interactions are unique external sources of data collection that appropriately help in business analytics for product centric businesses.
A very successful business leader once said, “Every penny you spend on acquiring a new customer is not worth the thousand you spend on retaining your old customers!” Churn prevention is about holding onto your existing customers and save the thousands you otherwise would have spent in dilly dallying without the use AI ML business analytics.
Churn Prevention -- This is a new age terminology used to manage customer attrition in toughened market conditions, such as transitioning from a brick and mortar shop to fully digitized website, or mobbing from website marketplace to an app. Churn prevention essentially involves the use of various churn data formulae and AI ML data to drive predictive intelligence.
There are new age tools to handle and reduce churn prevention, and a course in business analytics would assist your career goals when it comes to helping a startup lower customer acquisition costs and increase annual revenues with optimized profits.
Sales forecasting enables business analytics teams to accurately project sales goals, based on the various external and internal factors that could affect the sales pipeline in the present or in the future. Sales forecasting entails the use of highly advanced machine learning and automation tools that can spot potential risk and challenges in meeting sales goals on a monthly, quarterly and yearly basis. For example, a sales team would leverage business analytics teams to forecast sales goals imagining how the team would perform if there was a sudden change in market demands, change of marketing goals, and / or change of sales targets in case of recession or lockdown.