Solve business problems with AI Builder prediction models
AI Builder prediction provides organizations with the expected outcome for a business scenario based on historical trends. Multiple scenarios can be processed, and each will determine a different type of outcome.
First scenario: Sales opportunity success
The sales staff at a gardening services company is overwhelmed by the number of opportunities that they must manage. They want to prioritize those opportunities so that they can work on the ones that have the highest probability of success.
In the last few years, the sales staff has compiled information, such as the location of the customers, the size of the yards to cater for, the size of the buildings on the premises, previous year service providers, and many more. Additionally, they’ve recorded the outcome of the opportunity, whether it’s won or lost.
Based on that rich historical data, they can use prediction to process the new opportunities information and let the sales staff work on the opportunities that have a potential for being won.
Second scenario: Product selection
The gardening services company offers over 12 different fertilizers that can be applied to customer lawns. Based on satisfaction surveys, the company has become aware that customers are often overwhelmed by the number of options and would prefer to be presented with the fertilizer that the customer is most likely to select.
Based on the rich historical data that’s compiled, the company can use prediction to analyze the profile of the customers and determine which of its products the customers are most likely to select.
Third scenario: Number of visits required
The gardening services company offers different service plans with visits frequency adjusted based on the customer's preferences and types of maintenance selected. The customers require that sales agents determine the number of visits that the gardening and landscaping crew will need to schedule at the customer site during the contract period.
Based on the rich historical data that’s compiled, the company can use prediction to analyze the bookings for each customer and determine how many bookings will most likely be required for the new customers or contracts.
Now, you’ve learned how to solve different scenarios by using AI Builder prediction model. Next, you'll learn how to build a prediction model and then use it in a model-driven app.