Sales Forecasting - predict future sales based on historical information about previous marketing and sales activities.
Input data: historical data about marketing budget, number of ads, special offers and other factors affecting sales.
Targeted Marketing - reduce costs by targeting a particular marketing campaign to the group of people which have the highest response rate. Avoid wasting money on unlikely targets.
Input data: information about customers and their response rate.
Service Usage Forecasting - forecast the number of service calls, customer transactions, customer arrivals, reservations or restaurant covers (patrons) in order to effectively schedule enough staff to handle the workload.
Input data: season, day-of-week, hour of the day, special events in the city/area, marketing budget, promotional events, weather, etc.
Retail Margins Forecasting - forecast the behavior of margins in the future to determine the effects of price changes at one level on returns at the other.
Input data: retail prices, expenditures at the retail level, marketing costs, past margin values, price variability and other market characteristics.
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