Most dashboards show what happened, not what state you’re in. Teams often react too late because growth slows gradually, early warning signals are noisy, and metrics contradict each other.
By the time ROAS, revenue, or CAC clearly worsen, the decision window has already closed.
"What growth regime are we currently in?"
"When did the regime shift actually occur?"
"Is this slowdown temporary or structural?"
"Are we scaling efficiently—or forcing growth?"
"Should budget strategy change right now?"
An HMM assumes the business operates in hidden states (regimes) that you don’t observe directly. You only see noisy signals (revenue, ROAS, CAC).
The model infers the most likely underlying state and estimates transition probabilities between them. Think of it as: “Reading the weather system, not just today’s temperature.”
The Problem
Growth decelerates before KPIs collapse.
What It Reveals
A transition from expansion to saturation.
Decision Enabled
Adjust strategy before waste accumulates.
The Problem
Scaling playbooks are applied too long.
What It Reveals
When aggressive scaling stops working.
Decision Enabled
Move from expansion to efficiency mode.
The Problem
A big launch inflates short-term metrics.
What It Reveals
Whether the underlying regime actually changed.
Decision Enabled
Avoid mistaking spikes for structural improvement.
The Problem
External shocks distort performance.
What It Reveals
Temporary regime vs long-term damage.
Decision Enabled
Avoid overcorrecting during short-term turbulence.
The Problem
Explaining performance feels subjective.
What It Reveals
Objective regime classification with probabilities.
Decision Enabled
Align leadership on the right posture.
SpendSignal uses HMMs as a meta-layer over all other models.
Specifically:
This prevents the most expensive mistake in marketing: applying the wrong strategy at the wrong time.
Instead of “ROAS is down 8% MoM”, you see:
The insight: "This isn’t a bad week. It’s a different phase."
No. It infers the current underlying state from observed signals.
Yes. HMMs explicitly model probabilities of transitioning both ways (e.g., Recovery → Growth).
Only if you enjoy reacting late.