Sales Forecasting is a critical factor in the growth of the business. It has usually been done in a combination of historical sales analysis, pipeline analysis and gut. It is fair to say that most sales forecasts tend to be ineffective or inaccurate.
Pharmaceutical companies can use AI in planning activities specifically for sales forecasting. Historical sales data are fed into the AI model (ARFIMA, Box Cox Regression, Exponential Smoothing, etc.) that generates sales forecasts. The sales forecast can be done monthly or quarterly and at varying levels of granularity.
By using AI Algorithms, Pharma companies can increase the accuracy of their sales forecasts. The predictions provided by AI on Sales Channel Effectivity, Customer Segment Performance, Product Performance and Customer Engagement enables them to set attainable targets/quota, proactively make decisions and identify opportunities to increase/decrease investments.
New Customers are the drivers for an organization’s growth. AI can analyze profiles of customers who buy the company’s product based on demography, interests and purchase behaviour. This allows an organization to identify their very best prospects by running lists on a Look Alike Model.
Lead Scoring Models can then further segment the prospects. AI identifies the customer profiles that have a high probability of conversion and applies them to select the best prospects from the whole population. This is useful for marketers because it helps them optimize campaigns in terms of target size, quantity, spend and messaging.