How do you know which customers need help right now?

Most teams rely on health scores to answer this. The logic seems sound: aggregate a bunch of signals into a single number, color-code it green/yellow/red, and let teams prioritize accordingly. It feels like progress. You've taken messy, scattered data and turned it into something simple and actionable.

Except it isn't actionable. And that's the problem.

The backwards-looking trap

Health scores are fundamentally backwards-looking. They tell you a customer dropped from green to yellow. They don't tell you why. And they definitely don't help you do something about it.

Think about what actually happens when a score changes. A CSM sees a yellow flag on an account. Now what? They have to go investigate. Pull up the account history. Check product usage. Review support tickets. Scan through email threads. Try to piece together what went wrong and when. Then they have to diagnose the root cause and figure out what intervention might help.

The score just created a bunch more work. It's an alert that generates tasks, with no solution attached.

And by the time that score changed, the problem had already happened. The customer had already stopped using a key feature. They'd already missed their onboarding milestones. They'd already started evaluating competitors. The score is telling you about yesterday's problem while you're trying to plan for tomorrow.

We describe this internally as a smoke detector that goes off after the house burns down.

Why scores break constantly

There's another issue that anyone who's managed health scores knows too well: they break all the time.

The weights are wrong. The thresholds don't account for different customer segments. A customer with low login frequency gets flagged as at-risk, but they're actually a power user who accesses everything through an API. Another customer looks green because they're logging in daily, but they're actually stuck in an implementation that's gone sideways.

Teams end up in an endless cycle of recalibrating the model, adjusting weights, adding new signals, removing noisy ones. The score becomes a project in itself, constantly needing maintenance while still failing to predict the outcomes you actually care about.

The fundamental issue is that health scores try to measure relationship sentiment. They're attempting to answer "how does this customer feel about us?" by proxy through usage data and engagement signals. But sentiment is a lagging indicator. By the time sentiment shifts, the underlying problems have been compounding for weeks or months.

A different starting point

Trig approaches this from a completely different angle. Instead of measuring relationship sentiment, Trig measures actual customer performance against the outcomes they need to achieve.

This sounds like a subtle distinction, but it changes everything.

• Relationship sentiment asks: "Is this customer happy?"
• Customer performance asks: "Is this customer succeeding?"

A customer can be happy but failing to adopt the features that will make them successful long-term. A customer can be frustrated with a specific issue but still on track to hit every milestone that matters. Sentiment and performance are related, but they aren't the same thing. And performance is what actually predicts retention and expansion.

How Stages work

At the core of Trig's approach is a concept called Stages. Every customer exists somewhere on a journey: onboarding, activation, expansion, retention. Trig knows where every customer sits in that journey and what milestones matter at each stage.

So instead of asking "is the customer logging in?" Trig asks "have they completed the setup steps that actually drive value?" Instead of asking "how many support tickets have they opened?" Trig asks "have they hit the activation criteria that predict long-term success?"

Each stage has objectives that define what healthy behaviour looks like. These objectives represent the specific milestones and behaviours that matter for customers at that point in their journey. For a customer in onboarding, the objectives might include completing account setup, inviting team members, and importing their first dataset. For a customer in activation, the objectives shift to actually using core features, establishing regular usage patterns, and hitting initial value metrics.

These objectives can be categorized as must-haves (critical milestones that strongly predict success) or nice-to-haves (additional indicators of progress that strengthen the signal). This gives teams a precise understanding of where each customer stands relative to where they should be, grounded in concrete milestones rather than abstract sentiment.

From descriptive to prescriptive

Traditional health scores are descriptive. They describe a state. They tell you a customer is yellow. But they leave all the interpretation and action to your team.

Trig is prescriptive. When Trig identifies a customer who hasn't completed a key milestone, it doesn't just flag them. It knows exactly what that customer needs to do next because the stage and objectives framework has already defined what success looks like at this point in their journey.

Signals surface customers who need attention before problems compound. These are specific notifications tied to meaningful milestones: "This customer is in week 3 of onboarding and hasn't completed the integration step that 90% of successful customers complete by week 2."

Campaigns then deliver timely, contextual outreach to move customers toward success. The intervention matches the gap. A customer who hasn't invited team members gets a different message than a customer who hasn't set up their first workflow. The outreach is specific because the system understands the specific problem.

Timing matters more than you think

The closer an intervention arrives to the moment of need, the more effective it is.

Think about your own experience as a customer of any software product. If you get stuck during setup and receive a helpful email the next day with exactly the guidance you need, you feel supported. If you get that same email two weeks later, it feels irrelevant. You've either figured it out yourself, found a workaround, or given up entirely.

The window for effective intervention is often measured in days, not weeks. Traditional health scores, with their lagging indicators and weekly review cadences, consistently miss this window. By the time the score changes and a CSM investigates and decides on an action, the moment has passed.

Trig collapses the gap between "customer needs help" and "customer receives help." Because the system is tracking specific milestones in real-time and has predefined responses for specific gaps, interventions happen at the moment they're most likely to work.

What this means for your team

Your team stops firefighting and starts focusing on customers who genuinely need human attention.

Many customers just need the right nudge at the right moment: a helpful resource, a reminder about a feature they haven't tried, a prompt to complete a setup step they abandoned halfway through. Trig handles these automatically, reaching out to customers and driving them forward without requiring your team to identify the gap, craft the message, and send it manually.

This frees your CSMs to focus on the accounts where human judgment and relationship-building actually matter: strategic accounts, complex implementations, customers facing unique challenges that don't fit neatly into a predefined playbook.

For customers who aren't managed directly by your team at all (the long tail of smaller accounts that most CS teams simply can't cover), Trig can manage them entirely. These customers still get timely, relevant interventions based on where they are in their journey and what they need to do next. They just don't require headcount to make it happen.

A new approach to post-sales

This is what we mean when we talk about Trig being more than a product. It's a fundamentally new approach to post-sales.

The old way treats post-sales as a monitoring problem. Watch the numbers, flag the risks, react when things go wrong. It's defensive, reactive, and scales linearly with headcount. Most teams can only afford to actively manage their top 10-20% of accounts.

Trig treats post-sales as a performance problem. Define what success looks like at each stage of the customer journey. Measure every customer against those criteria. Intervene automatically when customers fall behind. It’s an approach that scales with your customer base, not your team size.

The system links the business outcomes you want to achieve (retaining and growing customers) to driving deeper value for your customers through your product. When customers succeed, they stay.

When they stay, revenue compounds.