This article was originally published on the Sales Hacker blog by Sean Zinsmeister, VP of Product Marketing at Infer.
Every CEO wants to squeeze more out of their investments in customer acquisition. And that’s particularly true in today’s market. Stock multiples have come down, especially for many business-to-business SaaS companies that are not yet profitable. In this environment it’s all about doing more with less, and hence we’re seeing the rise of the “moneyball” CEO. These smart leaders leverage predictive analytics to grow revenues with what’s already in their pipeline.
Before getting into how to identify this “whitespace” of untapped opportunities, let’s take a step back and think about what executives should be doing to drive revenue. If I were to encapsulate a go-to-market (GTM) manager’s key functions as an algorithm, it would look something like this (in pseudo-code):
Loop Until Fired():
There are fairly established tools for the forecasting step — like Birst, Cloud9, Domo and GoodData — and the reassigning and enabling step is generally covered by proven approaches to training, hiring / firing, territory management, reallocating spend based on customer acquisition costs (CAC), etc. However the step of identifying specific gaps in the pipeline is the toughest to nail (especially when it’s late in the quarter), and it’s the defining the step that separates mediocre from amazing strategic leaders.
It’s time for this second GTM step to have a framework that’s just as repeatable as the other two, and we finally have proven data science to make that possible. Predictive analytics is a great way for any B2B company to mine their business funnel for deals that can close quickly, and identify potential revenue they might be leaving on the table. In fact, I’ve benchmarked several companies and found that they’re consistently sitting on pipeline which could add 10% of overall revenue from leads and contacts they already paid to acquire.