Product Pipelining and Revenue Stream Selection for Sales
Businesses still and always will require a level of human insight into which revenue streams to place products. Indeed, automation and algorithms to perform tasks are currently only as good as the humans who design them.
Applying Data Science
Where human operators may normally need to search for products to buy and sell, The Data Analysis Bureau’s data scientists can build tools to help the operator to make decisions.
Based on past data, algorithms can be written to flag valuable products, match them to revenue streams for sale, and return a likelihood of selling in different streams.
Machine algorithms can be used to evaluate and update the successes and failures of the human user to further refine decisions and increase efficiency.
Using data driven insights and evidence to direct human decision making can improve the selection of valuable products and increase the likelihood of successful sales to the most valuable revenue streams, thus increasing profit.