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For Customer Success Teams
Transform CS from Reactive Firefighting to Proactive Value Creation
Discover churn risks, expansion opportunities, and customer health drivers with AI-powered analytics that actually explain themselves.
See Scoop in Action
Your CS Platform Shows You What. But Never Why.
Black-Box Health Scores
Your health scores change, but nobody can explain the math. CSMs don't trust what they can't understand, leading to poor adoption and missed saves.
Static Segmentation
SMB/Mid-Market/Enterprise segments ignore how customers actually behave. You're missing expansion opportunities hiding in plain sight.
Analysis Bottlenecks
Waiting weeks for data team to run analysis means opportunities expire. By the time you get insights, it's too late to act.
Your CS App + CRM Can't Do This
Your CS platforms are great at workflows and tracking. But they can't discover why customers churn or expand.
How Scoop's Agentic ML Works for CS Teams
graph LR
A[Your CS Data
CRM + Product + Support] --> B[Scoop ML Engine] B --> C{AI Analysis} C --> D[Churn Risk Scores] C --> E[Expansion Segments] C --> F[Health Drivers] D --> G[Write to CRM Fields
+ Trigger CS App Playbooks] E --> G F --> G style A fill:#F8F9FD,stroke:#4763F5,stroke-width:2px style B fill:#4763F5,stroke:#4763F5,stroke-width:2px,color:#fff style C fill:#E3165B,stroke:#E3165B,stroke-width:2px,color:#fff style D fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style E fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style F fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style G fill:#4763F5,stroke:#4763F5,stroke-width:2px,color:#fff
CRM + Product + Support] --> B[Scoop ML Engine] B --> C{AI Analysis} C --> D[Churn Risk Scores] C --> E[Expansion Segments] C --> F[Health Drivers] D --> G[Write to CRM Fields
+ Trigger CS App Playbooks] E --> G F --> G style A fill:#F8F9FD,stroke:#4763F5,stroke-width:2px style B fill:#4763F5,stroke:#4763F5,stroke-width:2px,color:#fff style C fill:#E3165B,stroke:#E3165B,stroke-width:2px,color:#fff style D fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style E fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style F fill:#130417,stroke:#130417,stroke-width:2px,color:#fff style G fill:#4763F5,stroke:#4763F5,stroke-width:2px,color:#fff
Data Science for CS Teams. No PhD Required.
1
Explainable AI Models
Every prediction comes with the exact IF-THEN logic. CSMs see why scores changed and can explain it to customers.
2
Behavioral Clustering
AI discovers segments like "Power users who never contact support" automatically. Target the right plays to the right cohorts.
3
One-Click Analysis
From uploading data to actionable insights in minutes. No SQL, no Python, just point and click.
Concrete Plays You Can Run Day One
Early Warning Churn Detection
Data Fed:
Product usage, support tickets, NPS, payment status
Scoop Output:
Decision tree + churn probability written to Account.Churn_Risk__c
Action:
CS App fires CTA at 30% probability with exact risk drivers visible
Expansion Opportunity Discovery
Data Fed:
Seat utilization, feature adoption, user invites, contract tier
Scoop Output:
Clusters: "Growth-Ready", "At-Capacity", "Lagging Adoption"
Action:
Marketing targets "Growth-Ready" with upgrade offers automatically
Period-Over-Period Analysis
Data Fed:
All customer data with time stamps
Scoop Output:
Q4 churn linked to Feature Y usage < 5 events per seat
Action:
Product team prioritizes onboarding improvements for Feature Y
Transform Your CS Metrics
85%
Faster time to insight vs. traditional BI tools
3x
More accurate churn predictions with explainable AI
Minutes
Not weeks to go from data to actionable insights
Zero
Code required - if you can use Excel, you can use Scoop
Stop Guessing. Start Knowing.
Join CS teams who've transformed from reactive to proactive with Scoop's Agentic Analytics.
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