Harnessing AI for Real-Time Pipeline Analysis
A Game-Changer for Coaches and Entrepreneurs
In the latest of my “Cool as Heck” AI series, I’m diving into a practical use case that’s reshaping how I analyze client data during coaching sessions.
I recently found myself on a call with a client who had meticulously compiled a spreadsheet of pipeline metrics.
While crunching numbers live during sessions can feel tedious, a lightbulb moment sparked: what if AI could do the heavy lifting?
That’s when I thought, Why not just take a screenshot of the spreadsheet and let ChatGPT analyze it for us?
This experiment turned into a revolutionary moment. Using a simple screenshot from our Zoom session, ChatGPT began pulling insights, spotting trends, and even calculating ratios.
Here’s how it all unfolded and the powerful lessons it unveiled about using AI for pipeline analysis.
From Screenshot to Insight: The AI-Enhanced Pipeline Review
The idea was straightforward—use AI to examine ratios, conversion rates, and trend shifts in pipeline data, with a specific focus on a client’s sales metrics across different months. This AI-driven process allowed us to dig into:
Active Chat Ratios – By looking at the number of initial contacts (chat starts) and their conversion rates to triage calls, we saw that numbers had shifted significantly when the founder took over this stage. Analyzing the change from outsourced to in-house chat management helped us identify efficiency improvements and uncover where volume wasn’t the issue—it was who was managing it.
Conversion Trends – AI pulled out conversion rates for September and October, highlighting a shift from a 0.39% conversion rate to a 0.32%. These numbers indicated where adjustments might be necessary, especially around triage call quality.
Efficiency Ratios – The rule of thumb for chat-to-action rates is about one action per 30 chat starts. AI instantly pinpointed where September’s performance lagged at 71 chat starts per action and where October’s in-house management hit closer to the mark. Spotting this discrepancy without manual digging saved us substantial time and gave us a clear target for future improvements.
Why Real-Time AI Analysis is a Game-Changer
Imagine the power of not needing to mentally juggle numbers in a live coaching call or being bogged down by math that might trip you up.
Having ChatGPT analyze the data allowed us to stay fully engaged in the session, focusing on strategic decisions rather than calculations.
It’s like having a virtual analyst at your fingertips, ready to pull insights on the fly.
This is more than just automation; it’s a new dimension of analysis that turns data into immediate action.
The Bigger Picture: Building AI Tools for Your Niche
As we approach the launch of the AI 30 Day Challenge (AI30DC) on July 1, 2025, from Tokyo, I can’t help but see how AI tools like these can empower others to leverage technology uniquely suited to their industries.
For coaches, consultants, and business owners, the ability to quickly analyze and interpret data in real-time means more than efficiency—it’s a competitive edge.
Imagine building custom tools for your niche, solving specific pain points with just a screenshot and a few clicks.
Conclusion: AI Isn’t Just for Data Scientists Anymore
AI’s potential in fields like ours isn’t fully tapped yet. While tech trends go through cycles—hype, backlash, then stabilization—AI’s current phase offers us a golden opportunity to innovate. And this quiet phase is where we lay the groundwork.
So, the next time you’re on a coaching call, think about what AI might pull from a screenshot that you’d spend hours combing through manually.
With the AI30DC on the horizon, these kinds of innovations will be front and center.
I hope you’ll join us for this journey because, believe me, the possibilities are just getting started.
Stay tuned, and don’t forget to like, share, and spread the word!
What prompt did you give with the screenshot to get it to stay interpreting the data?