Nice thinking, Nuno P. — I love this thread and how you're framing scoring. You're talking about building a global scoring model derived from everything in the CRM, then layering on enrichment from other tools. Salesforce Data Cloud, anyone?
There are really two solid ways to approach this, and I totally see where Pat H. and Dan Rényi are coming from. Salesforce and HubSpot both offer out-of-the-box solutions for lead and account scoring. Personally, I like Marketing Cloud Account Engagement (formerly Pardot) for this — though it's often underutilized or not set up correctly.
You're basically describing the two ends of a spectrum I see play out a lot:
On one end, you've got the full-stack enrichment and scoring beast — Clay + Clearbit + Apollo + behavioral tracking + firmographic enrichment — all piped into a custom ML model. It's amazing if you've got the data, budget, and a dev team to keep it all running. It sounds like you had that previously. But it's not just about building the system — it's about maintaining trust in it and refining it over time. That can easily turn into a nightmare, and most teams fall short with the upkeep. Doesn't Chris Walker's Passetto aim to do something like this?
On the other end, you've got a Salesforce Flow that updates a score or flag based on a few key fields (email type, job title, company size, country, intent signal). It's simple but effective — and more importantly, it gives teams a way to test hypotheses and start having better conversations about lead quality.
That said, what you're describing is bigger than just lead scoring. You're talking about a predictive model that listens across the entire CRM — Leads, Contacts, Accounts, Opportunities, and even Custom Objects. That's a much more complex architecture. A Flow can definitely prototype this — it's quick, has no code, and is great for iterating — but once you're triggering logic across many objects and records, you'll likely hit DML limits or run into orchestration complexity.
That's where Salesforce Data Cloud starts to make sense. It's designed to unify data across Salesforce (and beyond), consolidate it into a single profile, and apply segmentation, calculated insights, or even AI-driven predictions in real-time. If you're already deep in the Salesforce ecosystem, it's a powerful way to score based on everything without building brittle automation chains.
So, wherever you start — I'd recommend this general path:
Diagnose what's working (and what's broken) inside Salesforce.
Score based on fields your team already tracks and trusts.
Layer in external enrichment only when it improves actionability
You don't need to track every signal like it's a Chris Walker masterclass — just start with the 20% of inputs that drive 80% of conversions. Your sales team probably already knows what those are. Start there, and refine.
