An ROI you'll love, in as little as 4 weeks.
Implementation isn't a software installation. We connect the systems you already run, bring their data into one standard, and train Scoop on how your best operators run the business. In as little as four weeks it's live: investigating every location, every cycle, and delivering plain-language action plans to the right people. You'll walk away with better margins and an organizational asset that outlasts the tool.
What raising the floor looks like: the weakest locations close the gap while the best hold steady.
Implementing Scoop was straightforward and was mostly configuration work. For a smallish department like ours, that's a huge boon. We don't have engineers to spare.
The obstacles are real. We designed around them.
Scarce management time
Your best operators are busy running the business. Training Scoop has to fit inside a few structured conversations, not a project that competes for their week.
Limited IT support
Most IT teams can't take on a long integration project. Implementation has to work with a day of read-only access, not a quarter of engineering time.
Data spread across many systems
Performance data sits in finance, point of sale, scheduling and inventory systems that name things differently. Implementation has to bring them together without a data warehouse project first.
Skepticism about AI
Managers who've seen AI initiatives come and go are right to be cautious. Adoption has to come from a tool that makes their week easier, not another report to check.
Pilots live within 4-5 weeks, full rollout within 12. Here's how.
Connect your systems.
Scoop connects read-only to the systems you already run: your BI or data warehouse, and where needed point of sale, scheduling, finance, inventory or practice management. If it all sits in one warehouse, this can take a day. Flat files work too.
Six systems connected for 1,214 stores, all read-only.
- BI and data warehouseSales, margin, plan
- Point of saleTransactions, ticket
- Workforce schedulingHours, shifts
- Inventory and replenishmentOn hand, sell-through
- Finance and accountingStore P&L
- Store traffic countersFootfall
Kestrel Outfitters is a fictional retailer. Figures are illustrative.
Scheduled flat-file exports work too. Nothing changes in the source systems.
Normalize the data.
Each system names stores, managers and metrics its own way. Scoop’s AI maps them to one standard and sends anything it isn’t sure about to your team to confirm, before a single report goes out.
1,211 of 1,214 stores matched across three systems. 3 go to a person.
Kestrel Outfitters is a fictional retailer. Figures are illustrative.
- “Net sls”Net sales
- “Worked hrs”Labor hours
Keep it in sync.
Stores open and close and managers move. Scoop rechecks its mappings every cycle, applies the clear changes, and flags the rest for a person, so reports never drift onto a stale hierarchy.
Everything else stayed in sync. 3 changes need a person.
- New store
A Lakewood, CO store appears in point of sale. It isn't in the store hierarchy yet.
Add storeNot now - District change
Scheduling lists 13 stores under District 42 Denver Metro. The hierarchy has 12.
ReviewNot now - Possible closure
One Mountain region store has recorded no sales for 30 days.
Mark closedNot now
Kestrel Outfitters is a fictional retailer. Figures are illustrative.
The fix applies to every report from this cycle on, for every role.
Train it.
Training is straightforward. Scoop needs between 8 and 10 hours of your best operators' time: walking through their reports, investigating patterns and benchmark anomalies, and building corrective action plans. That gets encoded into a customer context stack (an ontology) that makes it predictable and repeatable. Scoop works the way you do. Nothing needs to change. You tell it how you want to run your business.
8 to 10 hours of operator conversations in, a working context stack out.
- Decision contextLayer 3
When to investigate, what counts as a problem, what to fix first.
- Investigation contextLayer 2
The checks your best operators run, in the order they run them.
- Semantic layerLayer 1
Store, net sales, labor hours: defined once, used everywhere.
Kestrel Outfitters is a fictional retailer. Figures are illustrative.
Footwear aging: sell-through under 45% for 2 cycles.
Versioned and readable by your team.
Define the output briefings.
No manager wants overload. This step defines, quickly and from existing templates, what each manager gets every Monday morning, or whatever your cadence is: key metrics, trends, color-coded alerts, root cause explanations, and action plans. We give you multiple options to pick from, refine, and iterate on, so it stays simple.
Net sales grew at 9 of 12 stores, but transactions fell at 8. The shared work is Footwear sell-through.
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.
Holding ticket but losing trips. The lead is Footwear.
Trips are the store-specific gap. Transactions fell 11.2%, last of 12.
Pilot with a small team.
We typically reach pilot in four to five weeks. A forward-looking region with meaningful performance variance across locations works best. The implementation team iterates on the reports with that management chain until they're bought in and using it every day.
An org chart of all 1,214 Kestrel Outfitters stores. Only the Mountain region's 40 stores are live in the pilot.
Pilot: one region, 40 stores.
Mountain, its districts and its stores, live and iterating.
Scale out.
After the pilot, we roll out incrementally, or all at once, as we've done with some customers. Scoop supports multiple operating units with different definitions and even different languages, which are best addressed with their own pilots. In a rollup, each new acquisition goes through steps 1 to 3 and then joins the same reports.
An org chart of all 1,214 Kestrel Outfitters stores, all 11 regions live.
Scaled: all 11 regions, 1,214 stores.
Every region, every district, every store, on the same playbook.
Scoop goes where your data and infrastructure live.
Deployable in your environment. Talk to us about your specific requirements.
Scoop hosts
The fastest way to get started. We set up the infrastructure, maintain it, and run inference on our side.
Your VPC
Scoop is fully containerized. Deploy it into your own AWS, Google Cloud, or Azure account, wherever your data already lives.
Self-managed / private cloud
For the strictest security requirements, run and manage Scoop entirely within your own private cloud.
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.