Subscribe to DSC Newsletter
If you’re a modeler, you might say, “who the heck is this guy telling me that my precious thing is useless?” Wait a minute. I will explain later. If you’re new to this, let me tell you what predictive modeling is: It is the power to predict the future. Like a prophecy, except its using data, lots of them. Sounds cool? Yes, but it’s useless. Sad? Me too. I’m also a modeler.

Let me tell you a story. Once upon a time, I was preaching in front of senior management on how we could get more money. Using predictive model, it was proven that business could get cleaner leads, the right customer with higher likelihood to take our product. On paper, we could increase the revenue. It turns out, the customer response went double and revenue went sky rocket. However, 3 months after the implementation, it went back to pre-model performance, even worse. What has happened, Is predictive modeling become useless?

We dig a little deeper to find out what went wrong. What really happened during the implementation? It turned out something we did not realize happened during the leads distribution. Somehow, the sales team leader were all gone.

The sales team has hundreds of sales troops which were led by team leaders/supervisors. These team leaders have the expertise and experience to distribute the leads to the right sales person.Should the “good” leads be given to a more senior sales person or junior/trainees?This methods were proven to provide good result most of the time. These team leaders have vast sales experience that gives them instinct on how to utilize the leads to the max. It worked beautifully until the perfect storm hit the sales room floor. These team leaders were suddenly away at the same time due to various reason for the whole month.

Suddenly, out of nowhere most of the team leaders were gone. The leads were distributed randomly to all the sales troops. Suddenly, the predictive model is useless.

This is what we call sales bias. If the model was implemented through different channel: direct mail, SMS or email campaign, there will be no bias and the predictive model will work perfectly. In our case, the model still has dependency on outside component: the sales person. The customer response will depend on how good the sales in pitching the product. What should we do? Can we replace “team leader experience” and distribute the leads “independently”?

Yes there is a way. We could actually provide logic to give “score” to each sales team member. The score will depend on sales’ past performance: how good they are in converting the sales. This score will then be matched to the leads’ score. The question now, should the high-score-leads matched to the high-score-salesperson? The best answer is to test it and make the mix and matched to give better result.

Views: 1533

Tags: Modeling, analytics, big, data, modeling, predictive


You need to be a member of Data Science Central to add comments!

Join Data Science Central

Comment by Laura Gardner on November 13, 2015 at 9:08am

The title of this article is what's known as "click-bait".

© 2021   TechTarget, Inc.   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service