A spike in churn. A drop in signups. A quarter that just feels off. Dashboards might show you a number moved, but they won’t tell you what actually changed.
Scoop compares two time periods and runs a full analysis across your dataset—so you can catch the shift, understand what’s driving it, and respond fast.
Used by Brands You Know and Trust
Why This Matters
Change happens everywhere, all the time—across behaviors, traits, users, and segments.
If you’re not analyzing it, you’re guessing. And when you guess, you get:
If you’re not analyzing it, you’re guessing. And when you guess, you get:
Missed Revenue
Opportunities lost because you didn’t see what changed beneath the surface.
Misattributed Results
Blaming the wrong factors and doubling down on tactics that don’t work.
Wasted Time Fixing the Wrong Thing
Chasing metrics that aren’t the real problem while the real issue grows.
What It Actually Does
See deeper shifts across your business—not just surface-level changes.
Scoop compares two time periods and runs a structured analysis across your dataset. It finds what changed, explains why it matters, and gives you results you can act on.
Let Scoop Tell Your Data's Full StoryScoop compares two time periods and runs a structured analysis across your dataset. It finds what changed, explains why it matters, and gives you results you can act on.
Pick Two Time Periods
Compare this month vs. last, this quarter vs. the previous—any timeframe you choose.
Analyze Every Variable
Scoop scans your entire dataset—every field, trait, and behavior—automatically.
Detect Meaningful Changes
It runs a statistical comparison to detect real shifts, not noise.
Explain What’s Different
Summarizes changes in plain, useful language anyone can understand.
How It Works
Get clear, actionable answers—fastt
Step 1: Select Your Time Periods
Pick two periods to compare—any timeframe that matters to your business.
Step 2: Let Scoop Analyze Your Data
Scoop runs contrastive analysis behind the scenes, comparing your group across all dataset variables.
Step 3: Review Actionable Insights
Get plain-language summaries of what changed and why it matters—ready to share or dig into.
Powered by Agentic Analytics
This is AI Data Discovery applied to time.
When you run a comparison, Scoop doesn’t just surface deltas—it takes initiative.
That’s Agentic Analytics: AI that doesn’t just report. It investigates.
- Chooses the Right Statistical Approach
Selects methods based on your data and what you’re comparing. - Runs Analysis Across All Variables
Scans every relevant field—without you having to tell it what to check. - Filters Out Noise
Eliminates false positives so you focus only on what matters. - Summarizes the Findings
Delivers clear explanations so anyone can act on the results.
Why Scoop is Different
A full investigation—powered by Agentic Analytics.
Scoop doesn’t wait for you to define logic or build models. It thinks like a data scientist and runs the entire workflow for you.
Analyzes Your Entire Dataset
Goes beyond top-level KPIs to explore every field, trait, and behavior.
Uses Real ML to Detect Shifts
Employs machine learning and statistical methods to surface significant changes.
Finds Hidden Differences
Identifies shifts that aren’t obvious—even across combinations of variables.
Replaces Manual Data Science Workflows
Does what a data scientist would code in Python, automatically.
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
- What changed in lead behavior after the last campaign?
- Is the drop in conversion tied to timing, audience, or offer?
Customer Success
- Are this month’s new signups behaving differently than last?
- Did product usage shift after a feature release?
Sales & RevOps
- Are deals stalling more often—and if so, what changed?
- How are this quarter’s closed-won accounts different from the last?
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.