Know what your customers will buy before they do.
Predictive demand forecasting for non-subscription commerce. We anticipate each account’s next purchase from the signals you already have.
| Customer | Product | Week 23 | Week 24 | Week 25 | Action |
|---|---|---|---|---|---|
| C-04821 | Classic Tee — Black M | 0.87 | 0.12 | 0.04 | Email Now |
| C-11247 | Wool Coat — Navy L | 0.05 | 0.23 | 0.91 | Pre-Stock |
| C-08390 | Linen Shorts — Sage S | 0.74 | 0.31 | 0.08 | Email Now |
| C-15602 | Cashmere Scarf — Cream | 0.02 | 0.68 | 0.15 | Restock |
4 of 12,847 predictions · Updated 2 hours ago · Next refresh: Monday 06:00 UTC
The Problem
Your customers don't subscribe.
They come back when they're ready.
Traditional forecasting assumes predictable patterns. Non-subscription commerce doesn't work that way.
Stockouts on your best sellers
Size 8 in black is gone again. Your top variant sells out while odd sizes collect dust.
Overstock eating your margins
You ordered based on gut feel and last year's numbers. Now you're marking down 30% of inventory.
Blind email campaigns
You're blasting the same promotion to everyone because you don't know who's ready to buy.
New launch guesswork
Every product launch is a coin flip. How many units? Which sizes? You won't know until it's too late.
Proven Results
Numbers that speak for themselves
Forecast accuracy on Olist e-commerce dataset
Traditional forecasting baseline
Validated on real e-commerce datasets
How It Works
From data to decisions in three steps
Deploy In Your Environment
StratTab runs as a container in your cloud environment with read-only access to your data warehouse. Your data never leaves your infrastructure.
Compatible with Snowflake, BigQuery, Databricks, and Postgres. Setup takes under an hour.
We Build Your Forecast Model
Our AI analyzes purchase patterns at the customer × product × week level, generating a sparse synthetic fact table with purchase probabilities.
Hierarchical reconciliation ensures forecasts are consistent from the top line down to individual SKUs.
Get Predictions In Your Warehouse
Receive forecasts directly in your data warehouse. Query via SQL, power your email campaigns, and optimize inventory decisions.
Predictions write to your analytics schema. Use any BI tool or downstream system you already have.
Capabilities
Built for non-subscription commerce
Every feature designed for the unique challenge of predicting when customers will come back — without a subscription to tell you.
Warehouse-Native Deployment
Runs in your cloud environment. Your data never leaves your infrastructure. No security review nightmares.
Customer × Product × Week Forecasting
Granular predictions at the individual customer and product level. Not aggregate SKU guesses.
Synthetic Fact Table Output
Predictions in the same format as your transaction tables. Query with SQL. No black boxes.
Hierarchical Reconciliation
Bottom-up forecasts that sum correctly to top-line targets. Consistent across all aggregation levels.
Intermittent Demand Handling
Purpose-built for sporadic, non-subscription purchase patterns that break traditional models.
SQL-Native Integration
Join predictions to your existing dimension tables. Works with any BI tool or downstream system.
Use Cases
Purpose-built for your industry
Fashion & Apparel
Predict size and color demand across seasonal collections. Reduce overstock on slow variants while never missing size 8 in black.
30% reduction in variant-level stockouts
Problems We Solve
- ✓Size/color variant stockouts
- ✓Seasonal collection planning
- ✓New launch quantities
- ✓Markdown optimization
Stop guessing.
Start forecasting.
Join data-driven brands that predict demand instead of reacting to it. See what StratTab can do with your data.
No credit card required · Setup in under an hour · 12+ months of order history recommended