Revenue Engine Analytics - Part V

This series has covered a lot of ground.

In Part I we set the table. We discussed how power, efficiency and reliability are the key performance indicators for revenue engine health.

Part II focused on breaking down the revenue engine into sub-components, each with a heartbeat that can be measured.

Part III featured our first working Py script which enabled us to visualize pipeline generation in useful ways.

Part IV we dove deep into data frames and leveraged them to explore pipeline velocity.

Now we’re getting into the advanced techniques. Today we’re using Python and SQL to visualize conversion performance of our new business revenue engine, accounting for all the complexities doing business in 2025!

It’s pandas ‘red pill’ time.

Measuring Conversion Efficiency

Measuring stage-to-stage conversion rates in Salesforce is a pain.

With the power of pandas… it’s very simple. With a little extra effort, this analysis can become very powerful, too.