You’ve got a segment: new signups, churned accounts, high spenders, stalled deals. Scoop analyzes that group and shows you what actually makes it different—across every variable in your dataset.
No filters. No assumptions. Just a clear answer to: what defines this group?
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Why This Matters
Most teams track segments based on what’s easy to label.
But what if the real differences aren’t visible in your filters?
But what if the real differences aren’t visible in your filters?
Hidden Drivers of Conversion
Are these users converting faster because of campaign source—or something else entirely?
Root Causes of Churn
Is churn higher in this group because of engagement—or onboarding delay?
Missed Signals from Key Accounts
Are high-value accounts showing behaviors you haven’t been tracking?
What It Actually Does
Identify exactly what sets your segments apart—with no manual slicing or filtering.
This is what a data scientist would do in Python. Scoop does it automatically.
Let Scoop Tell Your Data's Full StoryThis is what a data scientist would do in Python. Scoop does it automatically.
Select a Group
Pick a segment (like users who signed up this week).
Compare to the Rest
Scoop automatically contrasts that group with your full dataset.
Analyze All Variables
It looks at dozens of fields—individually and in combination.
Surface What’s Distinct
It identifies what’s statistically unique about your group and explains it clearly.
How It Works
Scoop handles the heavy lifting so you can focus on the insight, not the analysis.
Step 1: Pick a Group
Select any segment—like churned accounts or fast-closing deals.
Step 2: Let Scoop Analyze
Scoop runs contrastive analysis behind the scenes, comparing your group across all dataset variables.
Step 3: Review the Results
Get clear, explainable traits that define your group—so you know what’s really going on.
Powered by Agentic Analytics
Most tools stop at filtering. Scoop keeps going.
When you pick a group, Scoop doesn’t just summarize—it investigates.It compares that group to the rest of your dataset, runs contrastive analysis behind the scenes, and tells you what stands out—with both context and clarity.
That’s Agentic Analytics:
AI that doesn’t wait for you to define logic. It takes initiative, runs structured analysis, and explains the results in plain language.
This is AI Data Discovery in action—answering questions you didn’t know to ask, and showing you what makes a group different before it affects outcomes.
Why Scoop is Different
Scoop delivers data science-level insights—without the data science.
What used to take hours in a notebook now takes one click.
Contrastive Machine Learning
Built on contrastive machine learning, not static filters or field comparisons.
Finds Non-Obvious Patterns
Discovers hidden patterns and combinations across your full dataset.
Handles Messy Data Automatically
Manages overlapping, redundant, or messy fields so you don’t have to.
Outputs Clear, Explainable Results
Gives you insights you can use and reuse—fast.
Use Cases That Actually Matter
These are real business questions Scoop helps you answer—questions you’d normally hand off to an analyst, but now you can just ask directly.
Marketing
- Compare leads who converted in under 3 days to everyone else.
- Find patterns in your highest-value inbound leads.
- Understand what makes this campaign’s signups different from last month’s.
Customer Success
- See what defines accounts that complete onboarding early.
- Understand who’s quietly disengaging—even when usage looks fine.
- Find out what sets long-term customers apart from those who churn quickly.
Sales & RevOps
- Analyze stalled deals—what’s different about them?
- Compare fast-closing deals to ones that drag.
- Understand what separates high-ACV accounts from the rest.
Frequently Asked Questions About Scoop's AI Data Analyst
What kind of analysis does Scoop AI actually run?
Scoop uses clustering, classification, and predictive models to identify patterns, segments, and relationships in your data. Then it uses LLMs to explain those findings clearly.
How is this different from a dashboard tool?
Dashboard tools show you what you already know to look for. Scoop AI runs analysis to uncover what you didn’t know to ask—then helps you drill deeper.
Can I use this without connecting live data?
Yes. You can upload a spreadsheet or use a static export from any tool. Scoop AI works with one-off data just as well as connected sources.
Do I need technical experience to use this?
No. Scoop was built so that operators, marketers, and CS teams can use it without knowing SQL or machine learning.
What kind of data works best in Scoop?
Tabular business data—things like CRM exports, campaign data, product usage logs, revenue metrics, etc. Anything that tracks actions, results, or user traits.
How fast does it work?
Most analyses run in under a minute. Larger datasets may take slightly longer, but Scoop automatically samples when needed.
Can I save or reuse the results?
Yes. You can persist segments, create filters, and use results in presentations or reports later.
What’s the difference between AI Chat and the other tools?
AI Chat is great when you have a specific question. The other tools—like predictors and clustering—are for when you don’t know where to start and need help finding the story.
Is this secure?
Yes. Your data is never shared or used to train external models. Everything runs securely within your session.