Retail
Every Store, Every SKU, One Clear View
Allston Yale builds retail analytics for mid-market retailers and e-commerce brands in Texas and across the USA. We help lean IT and merchandising teams turn sales, inventory, and customer data into one clear view they can act on.
01
You Find Out What Sold After It's Too Late to Restock
Retail moves faster than most reporting. Sales sit in the POS, stock in another system, and the online store keeps its own numbers, so by the time the report agrees, the winner has sold out and the dud has eaten a markdown. We close that gap so what is selling stays visible now.
02
What Retail Analytics Covers
Retail data analytics runs from the shelf to the P&L. It tracks sales by store, channel, and SKU, inventory turns and stock-outs, gross margin and markdowns, and the basket and conversion numbers that decide whether a good day was actually profitable.
Most retailers start with one blind spot. Often that is store-level performance nobody can compare quickly, or inventory that only reconciles at month-end, and we build out from a number your merchants and finance team both watch.
03
Built for Lean Retail IT Teams
A mid-market retailer rarely has a data team; it has buyers, store managers, and a stretched back office. We build retail store analytics a small IT team can maintain, so visibility into what is selling does not hinge on one analyst’s weekly spreadsheet.
04
From POS, E-commerce, and Inventory to Dashboards People Trust
Your data lives in the POS, the e-commerce platform, the ERP, and the inventory or merchandising system, plus the inevitable spreadsheets. We bring those together into data analytics your buyers and finance team can read at a glance, instead of three systems that never agree.
Done well, Power BI for retail puts one trusted view of sales and stock in front of merchants and leadership at once, so the Monday meeting is about what to reorder and what to mark down, not about whose number is right.
05
Knowing What Sells Before the Season Ends
The forward look is where the margin is saved. Predictive analytics in retail reads the trend in sales and stock to flag what will sell out and what will stall, so you reorder and mark down early instead of discovering both at the end of the season.
The same foundation powers customer analytics in retail, turning loyalty and transaction data into a read on who buys what, who is about to lapse, and which promotions actually pay for themselves.
06
Built on Power BI and Microsoft Fabric
We build retail analytics on Microsoft Power BI for the dashboards and Microsoft Fabric for the data platform underneath. For the reporting craft see our Power BI consultant page, and for the platform see our Microsoft Fabric consulting page.
Most retailers start with retail business intelligence in Power BI done well on the metrics that drive the business, then grow into Fabric as online, in-store, and supplier data multiply. We help you separate a real platform need from an upgrade that can wait.
What working with Us Looks like
Plenty of analytics firms will hand a retailer a generic dashboard and leave. We learn how your stores and channels actually make money first, build to that, and document everything so your team keeps control long after we step back.
32%
INCREASE IN DECISION SPEED
27%
REDUCTION IN OPERATIONAL COSTS
2.4x
INCREASE DATA UTILIZATION
96%
DATA ACCURACY IMPROVEMENT
Data-Driven Demand Forecasting with Analytics Data Platform
Analytics Data Platform Facilitating a Greener Future
Common Questions
Can you connect our POS and e-commerce systems?
Yes. We regularly pull from POS, e-commerce platforms, the ERP, and inventory or merchandising systems, through their databases, extracts, or interfaces. We do not replace those systems; we make the data they hold usable in one place.
Can we see sales and stock close to real time?
Often, yes. With Microsoft Fabric handling streaming sales and inventory feeds, dashboards can refresh close to live for what needs it, like store sales or stock levels, while slower measures update on a normal schedule. We match the speed to the decision.
Can this help with forecasting and markdowns?
It can. Once sales and inventory data are reconciled, the same foundation can forecast demand and flag markdown risk, so buyers act on a ranked list rather than a hunch. We start simple and add sophistication as the data proves out.
How long until we see something useful?
A first dashboard on a priority area, sales by store, inventory, or margin, usually lands in weeks. We get one trustworthy view in front of your team early rather than waiting to model every channel, then build out from there.
Talk to Us About Your Stores
If your team is stitching sales and stock together by hand or finding out about a stock-out too late, a short conversation will show what is possible. Book a time and we will walk through your data and where the fastest win is.
