Scaling D2C revenue 3× with predictive inventory and AI-led marketing
Snicsnac, a direct-to-consumer snack brand, was struggling with stockouts on hero SKUs and wastage on slow movers. Durrani Tech deployed demand forecasting ML and rebuilt their performance marketing stack.
Client
Snicsnac
Industry
E-commerce
Services
Duration
6 months
3×
D2C revenue growth in 6 months
67%
reduction in stockout incidents
2.4×
ROAS improvement across paid channels
18%
reduction in inventory waste
The Challenge
Snicsnac had 40% stockout rate on their top 10 SKUs during peak seasons and 20% waste on slow movers. Their Meta and Google ad accounts were running on manual bidding with no attribution beyond last click. The marketing team had no visibility into which channels drove actual purchases.
Our Approach
We ran a full data audit, connecting their Shopify store, Meta Ads, Google Ads, and warehouse management system into a unified first-party CDP. A demand forecasting model was trained on 18 months of order history alongside weather, event, and competitor pricing data. We rebuilt their ad account structure with server-side conversion tracking.
The Solution
Deployed an LSTM-based demand forecasting model serving daily reorder recommendations. Rebuilt ad accounts with value-based bidding and first-party audience seeding. Created a custom attribution model giving weighted credit across touchpoints. Revenue grew 3× within two quarters.
Results.
3×
D2C revenue growth in 6 months
67%
reduction in stockout incidents
2.4×
ROAS improvement across paid channels
18%
reduction in inventory waste
Stats are representative of outcomes achieved.