Category: AI

Does anybody remember ‘The Game’? If you do then, sorry. If not, then the purpose of The Game is...

Introduction There’s lots of excitement about AI, but have you ever noticed how it’s mainly coming...

AI is making sales worse. There’s a massive over-rotation to doing things ‘at scale’ that’s propped up by evidence that it works. But just because something works sometimes, doesn’t mean it’s the right path. Case and point: look at your inbox. 

We are all missing the point

I know there’s an argument for how important relationships are in sales, but let’s be real, relationships built on lies are going to end. So no, you did not “come across my profile” and even the well written ones that are less detectable, are disingenuous unless it’s made explicitly clear it came from an AI.  

Beyond my own opinions on AI SDRs, the buying experience is objectively worse than it has ever been and AI is to blame, it’s not just top-of-funnel. 

It just sounds so good on paper. “AI is going to make us faster, more efficient, more data-driven. It’s going to completely change how we sell.”

Everybody is missing the point.

How to Create Your Own Data Lake: A Practical Guide for Sales and Revenue Leaders (with Playbook and Workflow)

As a sales &/or revenue leader, you manage vast data across various accounts, sales pipeline stages, and buyer behaviors. The challenge is that this data often sits in silos—scattered across CRMs, spreadsheets, email threads, or worse, only in your head. To truly harness the value of this data, you need to create a data lake (puddle or pond): a centralized repository where all of this data is stored and structured, allowing for deep analysis and actionable insights.

A data lake is like a giant, accessible pool of data: it starts with small amounts of data (a puddle), grows into something more structured (a pond), and eventually scales into a vast lake where different parts, or “coves,” represent different segments of your data in the sales cycle. For sales, these coves could correspond to various stages of your pipeline, customer behaviors, and other important factors.