Set of machine learning models on Sales Pipeline


Every sales team wants to sell more. They want to know health of sales pipeline and determine whether they will meet quota at end of quarter or not. Below is comprehensive list of machine learning models you can use on sales pipeline. Good news is you need not have to spend years to built it. Microsoft team has built these models. You can use the template and modify it to your need.

  • Predict probability of lead getting qualified into opportunity.
  • Predict probability of wining an opportunity.
  • Predict probability of Sales opportunity to go to next stage
  • Predict estimated revenue of sale opportunity
  • Predict how many opportunity a sales team will win in next quarter.
  • Predict total estimated revenue for next quarter.

 

You can start with Opportunity Scoring for Dynamics CRM and Opportunity Scoring for Sales Force

To get additional models contact Microsoft Data Science team

Estimated Win Count

Estimated win count predict - # of deal sales team will win.  Below charts show actual win count vs predicted win count for a quarter.

Prediction is made every week for 13 weeks of quarter.

deal-count

 

Estimated Revenue

Estimated Revenue predict - Revenue sales team will win.  Below charts show actual revenue vs predicted revenue.

Prediction is made every week for 13 weeks of quarter.

revenue

Stage Transition Prediction

Below chart shows aggregate prediction - how opportunities will move from differenct sales stages.

Example Develop --> Solution -> Win

 

distribution-stages-opportunity

 

Comments (4)

  1. Florian says:

    Unfortunately there is nothing “below”.

  2. Blake says:

    Are the AML experiments public that you can share? I’m trying to use the installer on codeplex but I am receiving a script error during the step to authenticate to Azure.

    1. http://opportunity.codeplex.com/ , http://opportunityscoring.codeplex.com/, http://crosssell.codeplex.com/ are public
      Estimated revenue, Estimated win count are not public yet. If you have a customer and interested to use – we can help them set up.

      Feel free to contact our data science team alias mentioned above.

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