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 don’t need another dashboard.
They need better revenue outcomes.
Faster pipeline progression. Higher win rates. Lower churn. More predictable forecasting.
Yet most SaaS companies are stuck spending hours slicing reports, reviewing pipeline stages, and debating gut-feel forecasts — while revenue opportunities slip away.
Here’s the truth:
The problem isn’t your data. It’s what your stack can’t do with it.
RevOps Doesn’t Need More Data — It Needs Revenue Activation
Modern GTM teams sit on a goldmine of signals:
- CRM opportunity stages
- Lead engagement in HubSpot or Marketo
- Product usage data in Snowflake
- CS health scores in Gainsight
- Support tickets, billing events, web sessions
Yet the critical revenue-driving decisions — who to prioritize, who’s at risk, which deals will close — still rely on:
- Incomplete CRM fields
- Static playbooks
- Weekly hunches
This isn’t a data problem.
It’s an activation gap that’s costing real revenue.
The Limits of the Traditional GTM Stack
Your stack was built to:
âś… Track activity
âś… Automate workflows
âś… Generate reports
What it wasn’t built to do:
❌ Unify fragmented data in real time
❌ Predict churn, conversion, or expansion opportunities
❌ Push recommendations back into the tools where decisions actually happen
In short, it lacks the connective tissue — the intelligent layer — needed to move from insights to revenue outcomes.
What a Predictive Data Layer Looks Like
RevOps needs something new: a revenue decision layer that sits across systems, connects live data, and turns intelligence into pipeline movement.
It’s not another BI dashboard.
It’s not just a data warehouse.
It’s not a one-off ML model.
It’s a layer that:
- Connects systems like Salesforce, Snowflake, HubSpot, Gainsight
- Trains predictive models on sales, marketing, and CS signals
- Continuously scores leads, accounts, and deals
- Pushes predictions, risk alerts, and prioritization cues directly into GTM workflows
- Explains why a lead scored high or a deal is at risk
And most importantly:
✅ It drives revenue action — not just analysis.
Why This Matters for Revenue Outcomes
The pace of GTM has accelerated.
Revenue teams can’t wait for end-of-quarter reviews to discover they missed target.
They need:
- Real-time prioritization to move pipeline faster
- Predictive visibility into churn and deal risk
- Cross-team alignment on the highest-value opportunities
According to McKinsey, companies using live, signal-based decision models in GTM operations see:
30–50% faster execution on strategic actions
Up to 20% higher conversion at key funnel stages
The opportunity isn’t more analytics. It’s operational intelligence — built into your stack.
Final Thought: From Reporting to Revenue Impact
You’ve already invested in a strong foundation: CRM, automation, data lakes, dashboards.
But if insights aren’t turning into action — in the moment, for the customer — RevOps is still leaving revenue on the table.
It’s time to stop optimizing dashboards and start activating the intelligence hidden across your stack.
Because the next evolution of RevOps doesn’t just connect systems.
It drives revenue decisions — with a smarter, predictive layer.
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