Overview: Commercial analytics in Practice
This article from Revology Analytics explains commercial analytics in the context of modern pricing analytics and revenue growth management. It draws on real engagements with mid-market and enterprise clients to turn commercial analytics from a buzzword into a measurable commercial capability. Read on for the full perspective, and see our related reading for additional depth.
There’s quite a bit of hype surrounding “Generative AI” reminiscent of the Data Science hype 5-10 years ago. However, something different about the capabilities of so-called “Large Language Models” (LLMs) excites us.
We’re less excited about the transformative power of these algorithms – they will undoubtedly append any repetitive non-physical jobs (e.g., admins, customer service reps, etc.).
We’re more interested in LLM’s ability to enhance our analytical productivity.
GPT-4 is already starting to reshape the field of commercial analytics, and we at Revology Analytics are huge proponents of it.
In our recent webinar titled “GPT-Powered Speed: Supercharging your Revenue Analytics,” we delved deep into how GPT-4 is a game changer for analytics teams. More specifically, we explored GPT-4’s ability to accelerate productivity around diagnostic and predictive analytics for Revenue growth problems.
In addition to exploring how to create the perfect prompts for analytical workstreams, we provided hands-on examples in Python using simulated data sets for things like Price Elasticity modeling, Cohort Analyses, and Churn Modeling.
The full recording is available here for those who missed the live session or wished to revisit the insights.
If you have trouble viewing the below presentation, you can also access it here.
Please visit our free revenue analytics tools section to access our accompanying Python code.
Related Reading
- How to Build an Effective B2B Price Elasticity Model (in under 90 minutes)
- How To Build a B2B Margin Analytics & Optimization Platform (in under 90 days)
For broader industry perspective on pricing analytics and revenue growth management, see McKinsey’s Growth, Marketing & Sales insights.
