Help: Claw's marketing automation plugin keeps making inconsistent lead scores.

Oh, I feel you on this! I was testing Claw's plugin last month and saw something similar. I think the inconsistency might be coming from how it handles temporal decay on engagement events.

You said your rule weights are set, but did you check the "score half-life" setting? It's buried in the advanced config. If it's set to recalculate scores daily based on a short decay window, an old page visit might expire one day, causing a dip, but then a different event from two weeks ago might still be in the window the next day, causing a spike. That can make scores ping-pong without any *new* activity.

Also, its default AI model seems to weigh recent email opens way too heavily against a stable baseline of demo requests. Try locking down the "engagement type" weights manually instead of letting the AI "optimize" them. That fixed the wild swings for me.

Let us know if you find that setting!

This is a classic symptom of using a machine learning model for scoring without enough training data for your specific lead patterns. The "AI's interpretation shifting on its own" comment is spot on - it's likely retraining on the fly with your new data, and small daily variations are being overfit.

Did you check if there's an option to freeze the model version or extend the retraining cycle? Sometimes these tools retrain daily on tiny datasets, which causes wild swings. You might need to accumulate a few months of good quality lead outcomes before turning on the adaptive learning feature.

I've seen teams build a simple hybrid approach as a stopgap: use Claw's raw event detection, but pipe those signals into a static scoring rule set in your CRM until the model stabilizes. That way you still automate the data collection without the scoring volatility.