ScoopDomain IntelligenceWhat if your best analyst never slept?
Domain Intelligence captures how your experts actually think — then runs those investigations across every location, every day, without being asked.
Not another AI bolt-on. This sits on top of your existing Snowflake, Power BI, or Tableau.
Wake up to completed investigations
Domain Intelligence runs autonomously — scanning your entire operation, flagging what matters, and delivering a finished report before your morning coffee.
Every week, DI does this automatically
No questions asked. No analyst required. Here's what happens:
Checked inventory levels, sales trends, and conversion rates across every location
Inventory growing faster than sales, conversion rates dropping — classic distress signals
24 months of traffic patterns, customer segments, category performance, returns data
Found when things changed, what led to it, and how it compares to healthy stores
Full report with findings, open questions, and prioritized next steps — ready when you are
Executive Summary
Three stores exhibit critical operational distress with inventory growing 12-18% while same-store sales decline up to 9%. Days Inventory Outstanding has increased 25-42% year-over-year.
⚠️ Critical Finding
All three stores show inventory accumulating faster than sales—capital is getting locked in products that aren't moving. Store B is most concerning: traffic barely growing while sales declined 9%.
| Store | Traffic | Sales | Inventory |
|---|---|---|---|
| Store A | +8% | -4% | +12% |
| Store B | +3% | -9% | +15% |
| Store C | +10% | -2% | +18% |
Key Findings
- Systematic overstock: All stores show inventory growing 12-18% while sales decline 2-9%, indicating demand forecasting failure
- Store A: Volatile traffic (3K-15K monthly visitors), improving sell-through (65%→80%), but losing mid-tier repeat customers (Silver -20%, Gold -24%)
- Store B: Conversion crisis—rate dropped from 38% to 26%. Platinum customers down $30K (-18%)
- Store C: Returns exploding—up 178% in apparel, 485% in accessories—totaling $545K despite strong transaction values
- Acquisition divergence: Store A gaining new customers (+424%), Store B struggling (-14%), Store C collapsing (-53%)
🔍 Store B Discovery Path
Store B showed different distress patterns. After 22 consecutive months of explosive growth (17-70% YoY), same-store sales turned negative for the first time.
Customer segmentation identified the revenue bleeding: Platinum tier (highest-value customers) down $30K (-18%), Bronze tier down $10K (-75%). Total customer spending declined from $322K to $282K.
Category analysis showed apparel declining 18% YoY while accessories remained relatively stable—suggesting targeted rather than systemic issues.
Open Questions
- Why does Store C experience 178-485% increases in returns when average transaction values remain strong—quality issues, sizing, or showrooming?
- What external factors drive Store B's conversion collapse from 38% to 26%—competitive pressure, pricing, or merchandising failures?
- Why are mid-tier repeat customers (Silver/Gold) churning at Store A despite improving sell-through—switching to competitors?
- What operational changes caused Store A's extreme traffic volatility from 3K to 15K monthly visitors?
Investigation Methodology
Universal Screening
Screened all stores against DIO, same-store sales, inventory growth, conversion rates
Threshold Flagging
Identified stores where inventory growth > sales growth, DIO increase > 20% YoY
Multi-Dimensional Diagnostic
24-month analysis across traffic, segmentation, category, merchandise flow, inventory
Pattern Recognition
Identified inflection points, leading indicators, peer comparisons
Insight Synthesis
Actionable insights, open questions, risk prioritization
We encode how your experts actually think
Through a structured onboarding process, we capture YOUR specific investigation logic — not generic analytics patterns.
Investigation sequences
The exact steps your analysts take when something looks off. "First check this, then compare to that, then look for this pattern."
Your specific thresholds
Not generic alerts. YOUR numbers. What's normal for YOUR business, YOUR segments, YOUR seasonal patterns.
Pattern recognition
The combinations that signal something specific. Not just "metric went down" but "these three things together mean this."
Prioritization rules
What matters most, in what order, for which stakeholders. So the right people see the right things first.
It sits on top of your stack — not instead of it
Domain Intelligence adds an investigation layer that makes everything you've already built more useful.
The insight: Copilot and Cortex are AI wrappers for your data. Scoop is an expert system that orchestrates analysis the way your best analysts would — automatically, at scale.
An analyst that scales.
Like giving every location its own dedicated analyst — running investigations, finding issues, and surfacing what matters.
Proactive briefings
Every morning, you get a briefing that your best analyst would give you — already investigated, already prioritized, waiting for you.
Every location, every day
Not just the ones that triggered alerts. Every location gets the same investigative attention your best analysts would give it.
Gets smarter over time
As you react to briefings, it learns. Threshold too sensitive? Pattern not relevant? Feedback loops make it better every week.
Ready to clone your best analyst?
See how Domain Intelligence can encode your team's expertise and run investigations automatically across your entire operation.
Book a Discovery Call30 min call • See it with your data • No commitment