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This guide shows you how to use Signals to identify at-risk customers and create targeted interventions.

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Understanding signals

Signals automatically surface customers who are falling behind. Rather than manually hunting for problems, Signals tell you exactly who needs attention and why.

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What signals show you

Each Signal tells you:
  • Which objective customers are stuck on
  • How many are affected
  • Revenue at risk (from CRM data)
  • How far behind they are compared to average

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Prerequisites

To generate Signals, you need:
Stages configured and live
Objectives defined with completion criteria
Customers actively in stages
Sufficient completions for meaningful averages (10+)

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The signals dashboard

Navigate to Signals in the main navigation to see: Summary metrics:
  • Total customers at risk
  • Total revenue at risk
  • Number of active Signals
Signal feed:
  • List of current Signals
  • Sorted by revenue impact
  • Click any Signal to see details

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Drilling into a signal

Click on a Signal to see:
  1. Which customers are affected (list with key attributes)
  2. How long each has been pending
  3. Revenue associated with each
  4. Quick action to create a job

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Acting on signals

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Reviewing the signal

Before creating a job, review:

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Creating a job from a signal

1

Click the Signal

From the Signals dashboard, click into the Signal you want to act on
2

Review affected customers

Check the list to understand who’s included
3

Click 'Create Job'

This pre-populates the audience with the Signal’s customers
4

Configure the job

Set goal, duration, and messaging specific to this issue
5

Launch

Go live to start the intervention

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Job strategy for signals

Address the specific blocker: These customers are stuck on a specific objective. Your message should directly address that issue.
Keep it timely: They’re already behind. Act quickly once you see the Signal. Set appropriate duration: They’ve been slow, so give them reasonable time—but don’t let it drag on.

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Signal workflow example

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Scenario: Onboarding slow completers

Signal appears:
Step 1: Review
  • Click into the Signal
  • See the 12 customers listed
  • Notice 8 are self-serve, 4 are enterprise
  • Mix of industries and sizes
Step 2: Decide Worth intervening? Yes—profile completion is a key onboarding step, and £34K revenue is significant. Step 3: Create Job
Step 4: Launch and Monitor
  • Go live
  • Monitor completion rate
  • Review results after 7 days
Step 5: Iterate
  • 8 complete → Success
  • 4 exit → Need different approach? Manual CSM outreach?
  • New Signal appears next week with fresh slow completers

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Patterns and best practices

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Act quickly on signals

Signals show customers already behind. Delay compounds the problem.

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Don’t over-intervene

  • Customers shouldn’t receive too many automated messages
  • Some slowness may be acceptable (enterprise often moves slower)
  • Use exclusions to prevent job overlap

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Review recurring signals

If the same Signal keeps appearing: Recurring Signals may indicate systemic issues, not just individual customer problems.

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Measure job impact

After running Signal-driven jobs:
  • Did recipients complete faster than non-recipients?
  • Did the intervention reduce the Signal population?
  • What message content worked best?
This closes the loop and validates your approach.

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Prioritising signals

When you have multiple Signals, prioritise by:

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Revenue at risk

Higher revenue = higher priority, generally.

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Stage importance

Early stage Signals (onboarding) often deserve priority—these customers haven’t yet realised value.

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Intervention feasibility

Some Signals are easier to act on than others. A clear onboarding step is easier to nudge than a complex integration.

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Segment

If you have segments that matter more (enterprise, high-value), prioritise Signals affecting those.

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Advanced: Signal-driven workflows

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Automated job triggers

Instead of manually creating jobs from Signals, you can set up jobs that automatically target slow completers:
This creates a standing job that catches customers as they become slow completers.

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Combining signals with cohorts

Create cohorts based on Signal-like criteria:
Then use this cohort for multiple purposes:
  • Job targeting
  • CSM alerts
  • Executive reporting

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Common questions

Continuously as customer data updates. New slow completers appear as they cross the threshold.
Signals require sufficient completions for meaningful averages. Generally 10+ completions for stability. With less data, averages are less reliable.
Thresholds are configured by your Trig implementation team. Future versions may expose configuration in the UI.
They’re removed from the Signal. If they completed via job, the job tracks this as completion.
Current version shows active Signals. Historical tracking is planned for future releases.

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Troubleshooting

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”No Signals appearing”

  • Are stages configured and live?
  • Are there objectives with completion criteria?
  • Are customers in the stages?
  • Are there enough completions for averages?

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”Signal customers not entering job”

  • Does the job audience match the Signal criteria?
  • Are there exclusions blocking entry?
  • Is the job live?

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”Intervention not working”

  • Is messaging specific to the blocker?
  • Is timing right?
  • Do customers understand what to do?
  • Is the goal achievable?

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Summary

Using Signals effectively:
  1. Review regularly — Check Signals daily or every few days
  2. Act quickly — Don’t let slow completers get slower
  3. Be specific — Address the exact blocker in your messaging
  4. Measure impact — Track whether interventions improve completion
  5. Look for patterns — Recurring Signals may indicate systemic issues
  6. Iterate — Use what you learn to improve future interventions
Signals transform reactive customer success into proactive intervention. Use them to catch problems before they compound.