The Power of Data Analytics 2
This series of briefings looks at advanced Data Analytics applies to the past, the present, and the future.
Looking ahead to find out what could potentially happen in the future if trends continue.
– Forecast new sales revenue totals that are expected within the next reporting timeframe.
– Predict which opportunities the sales team is most likely to win this month, this quarter, and this year.
– Determine the propensity of selling a specific product together with a new product just introduced into the market.
Here are examples of foresight:
– Sales management generates a new sales forecast detailing each deal amount for each customer opportunity. This includes a “win rate confidence level” based on several factors, including deal complexity, customer business value, sales process steps completed, and salesperson profile.
– Predict the percentage of leads that will convert into sales for each customer buying segment. This is determined by several factors, including lead source, customer loyalty level, and age of the lead.
– Determine the propensity of a customer to sign up for premium product support based on the customer’s loyalty level, range of products used, and size of company.
– Determine the propensity of selling products together in a bundle. In other words, how likely will bundling increase the sales of each product?
I’m DJ Sebastian, and we will continue our discussion on Data Analytics in the next briefing.