For over two decades, Retail Link was the system Walmart suppliers used to access their sales data, inventory levels, and operational metrics. It was clunky, it was slow, and it required a dedicated analyst (or two) to make sense of the data. But it worked, and the entire Walmart supplier ecosystem built processes around it.
Then Walmart replaced it with Scintilla.
If you're a Walmart supplier navigating this transition — or if you're new to the Walmart ecosystem and only know Scintilla — this guide covers what changed, what the data actually looks like, and how to get the most out of the new system.
What Was Retail Link?
Retail Link was Walmart's proprietary supplier portal. It gave suppliers access to:
- Point-of-sale data at the store and item level
- Inventory positions across stores and distribution centers
- Forecast data from Walmart's replenishment systems
- Scorecard metrics like instock percentage, OTIF (On Time In Full), and sales comparisons
The system was web-based but felt like it was built in the early 2000s — because it was. Pulling reports required navigating through multiple screens, setting date ranges manually, and exporting data into Excel for any meaningful analysis. Power users learned to use Retail Link's query builder, but it had a steep learning curve and strict data limits.
Despite its limitations, Retail Link was the definitive source of truth for Walmart supplier performance. Every buyer meeting, every line review, every quarterly business review was grounded in Retail Link data.
Enter Scintilla
Scintilla is Walmart's next-generation data platform for suppliers. Rather than a portal you log into and run queries, Scintilla delivers structured data files — primarily Excel workbooks — on a weekly cadence.
Here's the fundamental shift: Retail Link was a query tool. Scintilla is a data delivery platform.
Instead of logging in to pull the specific report you need, Scintilla pushes a standard set of datasets to you every week. You get the same data every supplier gets, organized into well-defined workbooks with consistent column structures.
The 13 Core Scintilla Datasets
Every week, Walmart suppliers receive up to 13 datasets through Scintilla:
| Dataset | What It Contains |
|---|---|
| Item Table | Your full item catalog with UPCs, descriptions, departments, categories |
| Sales & Inventory | Store-level sales, units, on-hand inventory, weeks of supply |
| eComm Sales | Online sales data (walmart.com, pickup, delivery) |
| eComm Inventory | Online fulfillment center inventory positions |
| eComm Instock | Online instock percentages by item |
| Vendor Scorecard | Walmart's official supplier scorecard metrics |
| Tender Analysis | Purchase orders issued by Walmart, quantities, amounts |
| Store MUMD | Mark-Up / Mark-Down data — pricing changes and margin impacts |
| Store Demand Forecast | Walmart's demand forecast for your items at the store level |
| Order Forecast | Expected upcoming orders from Walmart's replenishment system |
| DC Metrics | Distribution center inventory, receipts, and shipment data |
| Future Valid Item Store | Which items are authorized at which stores going forward |
| Modular Plan Metrics | Planogram and modular data — where your items sit on the shelf |
Each file follows a naming convention: {supplierID}_{supplierName}_{datatype}_weekly_{weekcode}.xlsx
For example: 104874_FOREVER GREEN_salesandinventory_weekly_021526.xlsx
What Changed From Retail Link
1. Data Delivery vs. Data Pull
This is the biggest change. You no longer log in and build queries. The data comes to you in a fixed format on a fixed schedule. This is better in some ways (no more wrestling with query builders) and worse in others (you can't easily do ad-hoc lookups for a single store or single day).
2. Weekly Granularity
Scintilla data is weekly, aligned to Walmart's fiscal calendar. Retail Link supported daily data queries. If you relied on daily store-level data for promotions or rapid response, this is a real change in capability.
3. Standardized Columns
Every supplier gets the same column structure within each dataset. This sounds minor, but it's a significant improvement. In Retail Link, the exact fields you got depended on which report you ran and how you configured it. With Scintilla, column names are consistent — things like all_links_item_nbr, store_number, pos_sales_dollars, on_hand_quantity.
One important caveat: column names use underscores and abbreviations, and they don't always match what you'd expect. Always verify the actual column headers in your files before building any automated process.
4. Fiscal Week Alignment
All Scintilla data is organized by Walmart's fiscal week. Walmart's fiscal year starts in late January or early February, so Week 1 is typically the first full week of February. This matters because if you're comparing year-over-year, you need to align fiscal weeks, not calendar weeks.
5. No Built-In Visualization
Retail Link had (basic) built-in charts and dashboards. Scintilla is raw data — Excel files. If you want charts, trends, or dashboards, you need to build them yourself or use a platform that does it for you.
How to Adapt Your Process
Build a Weekly Data Pipeline
Since Scintilla delivers data on a fixed weekly schedule, build a process that matches that cadence:
- Sunday/Monday: New data drops. Download your 13 datasets.
- Monday/Tuesday: Load the data into your analysis tool (Excel, a database, or an analytics platform).
- Tuesday/Wednesday: Review key metrics — sales trends, instock changes, ordering gaps, scorecard movements.
- Thursday/Friday: Take action on findings — contact your buyer about gaps, adjust forecasts, prepare for the next week.
Track Week-Over-Week Trends
With weekly data, trend analysis becomes critical. A single week's numbers are noisy. But 4-week, 13-week, and 52-week trends tell you whether your business is growing, shrinking, or holding steady.
Key trends to track:
- Sales dollars and units (store + eComm separately)
- Instock percentage (both store and online)
- DC ordering volume (are DCs ordering consistently?)
- AUR (Average Unit Retail) (pricing shifts impact everything)
Compare TY vs. LY
Scintilla scorecard data includes both This Year (TY) and Last Year (LY) comparisons for most metrics. Use these to separate genuine performance changes from seasonal patterns. A 15% sales dip looks alarming until you realize the same dip happened last year at this time.
Cross-Reference Datasets
The real power of Scintilla comes from combining datasets. No single file tells the full story:
- Sales & Inventory + DC Metrics → Are stores running low because the DC isn't shipping?
- Order Forecast + Tender Analysis → Is Walmart ordering what the forecast predicted?
- Future Valid + Demand Forecast → Are your authorized stores aligned with where demand is forecasted?
- Modular + Sales → Are your shelf positions correlating with sales performance?
Automate What You Can
If you're still manually opening Excel files, copying data into a master spreadsheet, and building pivot tables every week — you're spending hours on work that should take minutes. The structured nature of Scintilla data makes it ideal for automation. Whether you use Python scripts, a database, or a purpose-built analytics platform, automating your weekly data load pays for itself almost immediately.
The Opportunity in the Transition
Here's the thing about the Retail Link to Scintilla transition: most suppliers are still figuring it out. Many are doing the bare minimum — downloading files, glancing at the scorecard, and moving on.
The suppliers who thrive are the ones who treat Scintilla data as a strategic asset. They build processes to load it consistently, track trends over time, combine datasets for deeper insights, and show up to buyer meetings with data-backed recommendations.
The data Walmart gives you through Scintilla is comprehensive. Thirteen datasets covering sales, inventory, supply chain, forecasting, and store-level authorization. The question isn't whether the data is there — it's whether you're using it.