Scoop

Scoop scales your operating playbook to the front line.

Scoop is an enterprise-grade AI platform that codifies your best operators' judgment on how they run their business, then uses it to investigate every location every reporting cycle, interpret your BI data, and generate action plans that boost revenue and margins.

Every location now has the expertise of the COO and regional managers, and there's no debate, just action.
VP
VP of Operations
Multi-unit F&B operator · 80+ locations

Dashboards aren't actionable. We solve that.

Interpreting dashboards, and identifying and investigating issues, takes judgment and time that frontline managers often don't have. Senior leaders have that judgment, but can't scale it to every location either.

So the frontline loses time, waiting for a coaching visit, a manager who happens to ask the right question, or worse, issues pile up until they cost margin. Scoop solves that.

Operations/Workspaces/Weekly operations, all regions☆Data through Sun, Sep 20, 2026SubscribeExportShare
OverviewSalesLaborInventoryStoresWeek Sep 14 to 20, 2026▾Region All▾Compare Same week LY▾
From your BI
Weekly operations, all regions
Data through Sep 20, 2026
Net sales, week
$77.3M▲ 2.0% vs LY
Saturday sales vs LY
+1.8%All 1,214 stores
Stores
1,21496 districts
Stores below LY
243last 5 wks
Net sales vs LY, weeklyAll stores
All daysSaturday
Stores below −10% on Sat.Sat. sales vs LY
StoreCityLast wk5 wks
3228Houston−28.4%−27.1%
4447Oklahoma City−27.9%−24.8%
1561Phoenix−24.8%−22.3%
3227Houston−25.9%−22.2%
Total, 21 stores−21.2%−18.2%
Net sales by regionWeek of Sep 14, $M
Saturday floor staff11 a.m. to 5 p.m., scheduled
Standard 6August 4 (−2) from Aug 10
Saturday sales vs LY by regionLast 5 wks
District 42Sat. conversion vs traffic, 12 stores
Stores by sales vs LYLast 5 wks, count
Lowest sales vs LYLast 5 wks
StoreCitySalesSat.
3931San Antonio−9.2%−18.4%
3228Houston−9.1%−27.1%
1194Milwaukee−8.7%−9.4%
3227Houston−8.3%−22.2%
3465San Jose−8.3%−9.8%
1686New York−8.1%−6.7%
District 42Sales vs LY by store, last 5 wks

Kestrel Outfitters is a fictional retailer. Figures are illustrative.

Here's how Scoop works.

01

How soon can we be live?

Implementing Scoop is straightforward, and takes as little as four weeks to pilot, with no forward-deployed engineers required. We can help, or you can implement it yourself, in the environment of your choosing.

Typical pilot timeline
1
Week 1
Discovery
2
Week 2
Data & metrics
3
Week 3
Codify playbook
4
Week 4
Pilot live

No forward-deployed engineers. We help, or you run it yourself.

Works with your existing data stack.

No rip-and-replace. IT typically provisions read-only access to your data warehouse in a day, or sets up an automated extract on a schedule. We haven't encountered a data environment we couldn't connect to.

BI & reporting
Power BI, Tableau, Looker, Google Data Studio
Data warehouses
Snowflake, BigQuery, Redshift, Databricks
POS & operations
Any POS or ops system with a data export
Labor & workforce
Any labor system with a data export
100+ data sources supported·Read-only access·Full implementation details
02

Which locations need a closer look?

Scoop scans every location in your business, flags anomalies and adverse trends against benchmarks, targets, and history, and identifies what needs a closer look. Nothing gets missed, ever.

Scoop handles well over 1000 locations with 40+ investigations every cycle for customers today, and prioritizes by impact and freshness; managers don't get told what they already know.

An org chart of all 1,214 Kestrel Outfitters stores: chief executive, 11 regions, and each region's districts, one square per store. Every store is checked. 52 need action this week; 21 of them are in Desert Southwest, Mountain and Texas, where the August labor model cut Saturday staff.

SevereModerateMildHealthy1,214 of 1,214 checked

52 of 1,214 stores need action this week. 21 share one cause: the August labor model cut Saturday staff.

  • Saturday staffing cut21 of 52
  • Footwear out of stock14 of 52
  • New manager, first 90 days9 of 52
  • Clearance markdowns late8 of 52
Each square is one store. Kestrel Outfitters is a fictional retailer. Figures are illustrative.
03

Why is Store 2053 down?

For every issue it flags, Scoop runs a root cause analysis: why it's happening, and whether it's a one-off or an emerging trend worth acting on before it hits the bottom line.

Root cause · Store 2053
Sep 1 to 14, 2026

Store 2053 is losing trips, not spend. It is a trend, not a one-off.

Severe
  1. Split sales into trips and ticket
  2. Ranked against 11 peers
  3. Traced to category
How Scoop got there
  1. FindingNet sales fell 8.4%, one of 3 SE2 stores down.
  2. EvidenceTransactions fell 11.2%, last of 12. Avg ticket rose 3.2%, 3rd of 12.
  3. CauseA stale Footwear wall. Sell-through is 41% against a 56% median, with 158 days on hand.

Sample report. Stores and figures are illustrative.

Playbook rule fired

Footwear aging: sell-through under 45% for 2 cycles. Escalate to an action plan.

04

What should the manager do about it?

Based on what it finds, and the operating playbook you've codified, Scoop generates corrective action plans, ranging from a helpful hint to a high-priority imperative, depending on your culture and the severity of the issue.

Action plan · Store 2053
Sep 15, 2026

Start with the Footwear wall. It is the one fix that moves both sell-through and trips.

Built from your playbook rule: Footwear aging, under 45% for 2 cycles
1
High priority
Reset the Footwear wall with a weekly aged stock walk

Why: sell-through is 41%, lowest in SE2, with 158 days of Footwear on hand.

  1. 1Walk the wall with the category lead every Monday; pull anything past 120 days.

Goal: 41% to 56% · Store manager · Due Oct 13

Also in this plan
  • 2
    Medium priorityAdd a second floor associate Friday to Sunday, 12 to 6.Goal: Conversion 20.0% to 22.0% · Store manager
  • 3
    HintAsk Store 2178 how it sets its Footwear front table.Goal: 2178 turns Footwear at 66% · District manager

Sample report. Stores and figures are illustrative.

05

Does every manager know what to do?

Every owner in the management chain gets an individualized briefing: what's happening in their business, why, and what they need to do about it. Frontline managers get their location briefing; district managers get an overview of their territory. Nothing gets missed.

District overview
Sep 15, 2026
District SE2

Net sales grew at 9 of 12 stores, but transactions fell at 8. The shared work is Footwear sell-through.

What this cycle shows

Growth is coming from ticket, not trips. All 5 stores flagged for review sit below the 56% median.

Sample report. Stores and figures are illustrative.

Store brief
Store 2053
Severe

Holding ticket but losing trips. The lead is Footwear.

Trips are the store-specific gap. Transactions fell 11.2%, last of 12.

06

Did they act on it?

Scoop tracks every suggested action. Managers can accept, defer, or reject with a reason, creating a closed loop that improves performance over time. Updating Scoop is as simple as walking it through a new or modified investigation in plain English.

Since last report · District SE2
Sep 15, 2026

Store 2114 finished its Hardlines action. Transactions moved from −9.1% to −6.8%, and it dropped from Severe to Moderate.

Last cycle's actions, as the managers decided
  • Accepted
    Store 2114. Rebuild Hardlines transaction volume.Done. Transactions −9.1% to −6.8%.
  • Deferred
    Store 3071. Tighten weekday staffing to traffic.Deferred: new schedule starts Oct 1.
  • Rejected
    Store 2445. Rerun the loyalty sign-up script.Rejected: already run in August.

Sample report. Stores and figures are illustrative.

Playbook updated

“If a store defers the same staffing action twice, escalate it to the district manager.”

07

Is it paying off?

Customers cite improved performance visibility, faster decision making, and stronger frontline performance. As with other AI tools, newer or less experienced managers see the fastest improvement, but everyone benefits, and they like using it.

“The specific customers we are missing has been eye-opening.”
District Manager · National specialty retailer
Illustrative

What raising the floor looks like: the weakest locations close the gap while the best hold steady.

Weakest locationsTop performers
Illustrative curves showing the pattern, not customer data.

Built for security, connected to what you already use.

Scoop does not share your data or your operations with anyone outside the teams and systems required to deliver your implementation. We maintain strict separation between client engagements. Scoop became SOC 2 certified in 2025.

Layers on top of your existing BI stack: Power BI, Tableau, Looker, and 100+ more

Power BI
Tableau
Looker
Snowflake
BigQuery
Redshift
+ 100 more

Want to run Scoop without a dedicated analyst? See how self-serve works.

Book a discovery call

Reach out to start a two-way conversation about your industry, your performance variations across locations, and whether Scoop is the right fit for you.

Questions, answered