Using Artificial Intelligence to Prioritize Customer Engagement

If only one salesman came to work today, what is the first opportunity he should act upon that is most likely to sell a car today?. If two salespeople show up, who show perform the task?

Using a combination of public service 911 to dispatch customer engagement one at a time and deep machine learning to select the highest Sales Result Probability (SRP) activity, customer engagement increases by 50% daily per salesman and it follows that sales increase immediately by the same amount. By knowing which customers have the intent to buy in the next 90 days, marketing is laser focused and marketing budgets slashed by half or more. Aligning the right customer with the right salesperson maximizes the result. It's Moneyball for the car business.

Check out Jim's interview:

About Jim Roach: 44 Years in Automotive from Salesman to Dealer Principal to Founder of 5 Auto related companies. I wrote the foundations of modern reporting systems such as StoneEagle and Ristken, have multiple patents filed in DMS data extraction. I was a pioneer in predictive artificial intelligence for use in auto retail in the 1990's and created the first reserve chargeback insurance policy. After 6 years of pioneering work in data mining with AutoAlert I created the industry first Human Capital Management System using deep machine learning to triage sales opportunities and prioritize execution of tasks. the system is based on modern 911 public service dispatch systems.