How a retail store reduced stockouts by 40% using AI
Based on real results from SynapseOne beta users. Names and specific data have been modified to protect participant privacy.
The challenge
“Distribuidora del Centro” is a convenience store and retail distributor with 8 years in the market. They handle approximately 500 active products including groceries, beverages, dairy, and cleaning supplies.
Before using SynapseOne, they faced three recurring problems:
- Weekly stockouts on their 20 best-selling products
- Emergency purchases from alternative suppliers with markups of up to 15%
- Accumulated inventory of slow-moving products taking up valuable space
The solution
They decided to try SynapseOne. The process was simple:
Day 1: They exported their sales history from the last 6 months from their POS system. A CSV file with basic columns: date, SKU, quantity sold, current stock.
Day 2: They uploaded the file to SynapseOne. In minutes, the system processed the data and generated individual forecasts for each product.
Day 3: They reviewed the AI-generated recommendations: which products to buy, how many, and with what priority. They also uploaded price lists from their 3 main suppliers (one was a PDF, processed automatically by SynapseOne’s AI).
Week 1: They purchased following the system’s recommendations for the first time.
The results
30 days
- ✅ 40% fewer stockouts on priority products
- ✅ 25% reduction in emergency purchases
- ✅ Identified 15 slow-moving products they stopped auto-reordering
60 days
- ✅ Freed $3,200 in capital tied up in slow-moving inventory
- ✅ Now comparing offers from 3 suppliers before each purchase (vs 1 before)
- ✅ Team spends 4 fewer hours per week on manual ordering
90 days
- ✅ Estimated savings of $1,800/month combining fewer stockouts, fewer emergency purchases, and lower tied-up inventory
- ✅ Inventory turnover improved 22%
- ✅ Team satisfaction: “Now we buy with confidence, not fear”
How did they achieve this?
Three key factors:
1. Clean historical data
They didn’t need perfect data. SynapseOne is designed to work with real-world data (missing values, outliers, inconsistencies). With just 6 months of sales, the AI was able to identify patterns.
2. Per-product forecasting
Each of the 500 products received individual forecasts with 30, 60, and 90-day horizons. The AI automatically detected seasonality (beverages in summer, dairy in December, etc.), using machine learning techniques for demand forecasting.
3. Actionable recommendations
Not just numbers. The system generated specific recommendations: “Buy 150 units of PROD-001 (high priority, 5 days of stock left)” and “Reduce order of PROD-002 (slow-moving, 45 days of stock).”
What’s next for them?
Distribuidora del Centro is now in an optimization phase. Next steps:
- Integrate forecasting with their weekly ordering system
- Add more suppliers to the offer comparison module
- Explore automated purchase suggestions
Results like these for your business?
Every business is different, but the principles are the same: historical data + AI = better purchasing decisions.
SynapseOne lets you start with just a CSV file of your sales. No installation, no complex setup, no long-term contracts.
Ready to be the next success story?