New mobile apps to keep an eye on
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What new social media mobile apps are available in 2023?
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Use new social media apps as marketing funnels
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Try out Twitter Spaces or Clubhouse on iPhone
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What app are you currently experimenting on?
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RevOps leaders have built their reputations on making sense of chaos.
Connecting data. Fixing workflows. Keeping GTM teams aligned.
But here's the reality:
Everyone wants faster, better revenue decisions — yet most teams still rely on gut feel.
Dashboards help, but they’re not always trusted.
Your CRO wants accurate pipeline health, but you're stuck wrangling manual updates.
Your CS team needs to reduce churn, but risk only surfaces when it’s too late.
Marketing wants better lead scoring but only trusts what’s in front of them.
This is where predictive RevOps becomes essential. Not as just another layer of tech — but as a new operating rhythm designed to drive revenue outcomes.
This is your practical field guide to leading that shift.
Step 1: Focus on Revenue Decisions — Not Just Dashboards
Start by mapping the real, revenue-impacting decisions your GTM teams make every day:
- Which leads should SDRs prioritize this week?
- Which accounts show early signs of churn?
- What’s our realistic revenue forecast next quarter?
Now ask: what signals actually inform those decisions today?
Chances are, it’s a messy mix of:
- Incomplete CRM fields
- Rep intuition
- Weekly Slack threads
Moving beyond gut feel means defining the revenue decisions that can be made predictive — and identifying the data you already have to support them.
Step 2: Don’t Wait for Perfect Data
You don’t need a massive data warehouse project to start.
Modern predictive platforms can connect directly to live systems — Salesforce, HubSpot, Snowflake, Mixpanel, Stripe — and unify just enough to model what matters.
Start small and prove value fast:
- Build a lead scoring model on top of Salesforce + HubSpot signals
- Train a churn predictor using CS activity + product usage
- Predict PQLs based on activation patterns + firmographics
Focus on the revenue outcomes your teams care about — and build trust by pushing predictions into the tools they already use.
Step 3: Operationalize, or Don’t Bother
Here’s the truth: if your predictive scores live in a dashboard that no one checks, they won’t move revenue.
To make predictive work in RevOps, it has to be:
Embedded in your GTM systems (e.g., scores inside Salesforce or HubSpot)
Explainable so reps understand why an account scored high
Action-triggering — tied to automations, alerts, or task flows
One RevOps leader we worked with started surfacing churn risk scores right in the CS team’s view.
Result? A 12% increase in retention.
Not because the model was perfect — but because it was used.
Step 4: Align the Forecast with GTM Reality
Want your CFO to stop second-guessing the forecast?
Bring behavioral data into the picture.
When forecasts include:
- Sales stage velocity
- Engagement recency
- Historical rep behavior
- Product usage patterns
…you don’t just get a static number — you get a live signal of what’s actually happening.
And that makes pipeline reviews far less painful.
Final Thought: Upgrade Instinct with Intelligence
Intuition matters. You've earned it.
But gut feel alone won’t scale predictable revenue.
Your role as a RevOps leader is evolving:
From reporting to enabling action.
From aligning tools to unlocking decisions.
From retrospective insight to predictive performance.
And that shift starts with one question:
Which revenue decision will you make predictive first?
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