Bayesian Thinking

In the fast-paced world of selling B2B software, especially in fintech, decision-making often feels like gambling with incomplete information.

Consider this common scenario:

A Fintech Sales Problem

Your team is working to close a deal for a claims digitization solution with a major insurer. The first demo receives lukewarm feedback: “The OCR accuracy isn’t impressive.” Post-meeting, the sales team debates whether the deal is at risk. Some argue it’s a lost cause, while others are optimistic. As new information trickles in—like a competitor’s weakness or positive feedback from a key stakeholder—the team’s assessment of the deal shifts, but often without structure or a clear process.

This is where Bayesian reasoning shines. Instead of viewing outcomes as black or white—win or lose—you think in probabilities. What’s the likelihood of closing the deal based on current information? What would new data (like a better OCR performance in the next demo) do to change that probability?

Enter Bayes’ Theorem

Bayes’ theorem encourages us to adjust our beliefs with each new piece of evidence. For example:

1. Initial probability: Based on historical trends, your fintech solution has a 30% chance of winning deals at this stage.
2. New data: After the demo, customer feedback indicates interest in your categorization feature despite OCR concerns. This raises the probability of success to 50%.
3. Further input: A competitor’s higher price point gives your solution a relative advantage, increasing the probability to 70%.

By methodically weighing evidence, your team avoids knee-jerk decisions like abandoning the opportunity too soon or becoming overconfident without reason.

Broader Implications

I used the idea of Bayesian thinking in the context of my own Fintech Sales domain. That said, the concept applies to almost all decision-making areas- product decisions, resource allocation, strategy, etc. Bayesian thinking is an essential skill that helps one to manage uncertainty, navigate complexity, and make decisions rooted in rationality rather than intuition.

To dive deeper into how Bayes’ theorem can sharpen your thinking and decision-making, I recommend this excellent article from Farnam Street:  Predicting the Future with Bayes’ Theorem.

Equip yourself and your team with this mental model, and you’ll find better ways to process information, update your beliefs, and predict outcomes—no matter the challenge.