Capabilities · Retail Tech Consulting
We work on business problems through packaged programs where the work has been productized, and through embedded engagements where it hasn't been.
02 · The work we take on
The list isn't exhaustive, but in our experience the retail businesses generally suffer from one or more of these problems. Depending on the need, we address them through our decision intelligence programs or through embedded engagements.
Marketing is generating demand for SKUs the operations side can't fulfill in time, while you are pushing budget toward products the team can ship. Two functions optimizing in parallel, not in sync. The cost shows up as stock-outs on hot SKUs and discounting on the rest, every cycle.
Sales has been booked. Now the question is which orders ship first, which vendors get prioritized, and how to sequence deliveries against current inventory and production lead times. Most teams answer this in spreadsheets and Slack threads. The cost is: missed commitments, expedited shipping, and broken vendor relationships.
By the time the shift in what customers are buying surfaces internally, the marketplaces are already two cycles ahead. New entrants are winning the listing positions. The brand isproducing for last quarter's demand pattern while the assortmentthat's actually moving has already moved on.
The brand’s promise in the marketing assets sounds different than what actually happens at the 47th outlet on a Tuesday afternoon. Standards exist on paper, but execution drifts, between outlets, between shifts, between regions. The gap widens faster than any team can manuallymonitor it across a multi-location footprint.
Working capital is sitting in the wrong places. The slow-moving SKUs accumulate. The hot SKUs run dry. Both problems compound every cycle. The slow inventory locks up cash that could be funding what's actually selling, and the stock-outs train customers to look elsewhere.
Sales productivity is uneven across the field force, and the reasons aren't visible from headquarters. Some outlets convert. Some don't. Some reps win category share. Others lose it back. The patterns that would explain the gap stay buried in systems that don't talk to each other and reports nobody reads in time to act.
03 · How we work
Mechanism 01
We have successfully solved the problems enough time to package themethodology (fixed scope, defined deliverables, known cadence).We offer three retail specific programs today that are built inside your existing data stack to ensure no data leaves your organization.
Mechanism 02
For problems where the work doesn't fit a package, either because the scope is still being shaped, or because no program exists yet. A senior consultant plus delivery team, on a monthly retainer, working inside your business. Composition is designed per engagement; engagements renew by outcome, not by fixed scope.
04 · Our retail programs
These are the packaged programs we have shipped many times over the years. Each one is built inside a modern data platform, typically Microsoft Fabric, Snowflake, or Databricks. Let’s have a view on which fits your work best.
An outside-in read of what's moving in the marketplaces where you sell, turned into specific decisions such as what to list, push, price, produce next etc.
A decision-intelligence layer that joins marketing demand signal with operational reality, so you stop driving demand for what you cannot fulfill, and avoid sitting on dead stock no one is asking for.
Computer-vision-powered intelligence on store activities, operational standards, brand-experience consistency, customer signal, across every outlet, etc. on a continuous loop.
05 · FAQ
Four things we get asked early. We have put the answers here so you can decide whether a working session is worth your time.
If you know the decision you want to close and the scope is clear, the Program approach fits. If the work spans multiple decisions, or the scope is still being shaped, Embedded Delivery fits. We usually figure this out together in the first working session, and we'll tell you which one we would recommend.
Yes. We tell clients which stack is best for the work (Microsoft Fabric, Snowflake, or Databricks) based on what they are trying to do and where their team already is. If a migration makes sense, we will say so. If staying where you are makes sense, we will say that too.
Yes. The work belongs to you at handoff. No SaaS subscription. No licensing. The intelligence layer, the code, and the documentation transfer fully. Your team owns and runs it.
The engagement budget depends on scope, duration, and team composition. We will discuss budget directly in the working session, once we understand what you are trying to solve and over what timeline. We would rather size it accurately than anchor you to a number that doesn't match your work.
06 · Insights
Most retailers have foot-traffic counters. Few use the data to do anything useful. Here’s what’s actually possible and what most teams miss when they install sensors and stop there.
Read article
Walk into a retail store today and you are not just browsing, you are generating data. Here’s how footfall analytics and smart-store systems turn that data into store-layout, staffing, and inventory decisions that actually moves revenue.
Read article
Your eCommerce business generates massive amounts of data every day and most of it is stranded in silos. Here’s how advanced analytics turns that scattered data into demand forecasts, attribution clarity, and decisions that actually move revenue.
Read articleRetail consulting that ends with a system, not a deck.
08 · Ready when you are
A working session with a senior team member — 30-45 minutes, focused on your category, your data sources, and your current decision cadence. No commitment. No pitch deck. We leave you with useful thinking either way.
Founded 2020 · 5+ years of retail decision intelligence work · Engagements delivered across North America, Australia, and India · Partnerships and methodology details on About
