Comparative Analytics

Spot the Why Behind Every Difference

Compare any two groups in seconds and surface the exact factors that set them apart.

Compare Your Groups
Healthy Accounts
VS
At-Risk Accounts

The Comparison Challenge You Face Daily

📊 Surface-Level Differences

You can see that Group A performs better than Group B, but understanding the real drivers requires endless manual analysis.

🔍 Missing Interactions

Looking at one attribute at a time misses critical combinations. The magic often happens when Region × Plan × Usage align.

Analysis Paralysis

By the time you've created dozens of cross-tabs and pivot tables, the business has moved on and decisions are made on gut feel.

Why Traditional Analysis Falls Short

Capability Old Way in BI Dashboards Scoop Group Analysis
Analysis Method Create two reports, manually compare Single model weighs all variables simultaneously
Variable Interactions Can miss complex combinations Decision tree shows multi-attribute rules with lift
Refresh Process Duplicate filters, rebuild reports One-click refresh with new cohorts
Output Format Numbers and percentages only Narrative explanation + visual tree + raw rules
Actionability Results stuck in charts Probability scores sync directly to CRM

How Scoop Reveals Group Differences

1

Define Your Groups

Pick any filter for your focus group (churned customers, top performers, new pricing tier). Optionally compare against another group or everyone else.

2

Automated Analysis

Advanced ML builds a model that predicts group membership, weighing all variables to find the most distinguishing factors.

3

Clear Explanations

Get plain-English narratives, visual decision trees, and probability scores that sync to your CRM for immediate action.

Real-World Wins Across Every Department

💚

Customer Success

"What differentiates healthy vs. at-risk accounts?"

Tree reveals: Low logins + No integrations = 7× risk. Playbook auto-fires in Gainsight for proactive outreach.
🚀

Product Growth

"Why did Beta users activate faster?"

Drivers show: Invited ≥3 colleagues + New dashboard = 63% of lift. Roll out to all users immediately.
💰

Revenue Operations

"Why does Region A beat Region B this quarter?"

Finds: Localized collateral + Deal size <$15k as key divergences. Adjust enablement strategy.
📧

Marketing

"What's unique about campaign responders?"

Model highlights: First-touch webinar + Dev Manager persona. Refine targeting for 3× response rate.

From Question to Actionable Insight in 5 Clicks

Time: ~3 minutes. No SQL, no Python, no data science degree.

1

Select dataset & date range

2

Define focus group filter

3

Add comparison group (optional)

4

Click "Explain Groups"

5

Save scores to CRM

Why Business Users Love Group Analysis

💡

Immediate Clarity

Understand exactly what puts a record in or out of your target segment. No more guessing.

🔗

Multi-Factor Insights

Goes beyond surface KPIs to uncover hidden attribute interactions that truly matter.

🎯

Instant Action

Group probabilities become live CRM fields driving journeys, alerts, and playbooks.

"Change the group definition, rerun, and watch the narrative update instantly. Iterate at the speed of thought."

Turn Every Comparison Into an Actionable Playbook

Expose the precise levers distinguishing your segments.
Empower every team to act on them immediately.

Start Comparing Groups