Stop paying for RTOs you could have seen coming.
Implement pre-dispatch risk analysis and protect your margins starting today.
RTO Prediction AI
Know Which Orders Are Likely to Come Back Before You Ship Them
Every RTO carries the full cost of a wasted round trip: forward shipping, reverse shipping, repackaging, and a lost sale. Most of that cost is avoidable if high-risk orders are flagged before dispatch rather than discovered after a failed delivery. Shiplystic's AI-Powered RTO Prediction scores every order for return risk at the point of booking, using historical delivery patterns across address, courier, payment mode, and customer behavior.
Pre-Dispatch Scoring
Multi-Factor Model
Auto Interventions
Address Confirmed
Prepaid Converted
What It Does
Clock Dial Showcase — Auto-rotating features around the platform core.
RTO AI
Engine
Pre-Flight Scoring
Zonal AI Model
Risk Buckets
Prepaid Switch
Self-Learning
Pre-Dispatch Automated Risk Scoring
Evaluate every shipment immediately upon booking to determine return probability—acting before shipping fees are generated rather than after delivery attempts fail.
Instant Pre-Flight CheckMulti-Factor Predictive AI Engine
Analyzes combined indicators: address validity score, pincode performance histories, zonal courier success margins, payment terms (COD vs Prepaid), and customer record profiles.
30+ Risk Signal VectorsDynamic Actionable Risk Categorization
Categorizes orders dynamically into risk thresholds (Low, Medium, High), triggering programmatic resolution workflows without reviewing each transaction manually.
Low / Med / High BucketingAutomated Order Intervention & Prepaid Triggers
Executes custom actions for high-risk orders: flags for address verification outreach, requires prepaid-only terms, or holds dispatch for support agent inspection.
Auto WhatsApp / COD LockContinuous Machine Learning Feedback Loop
Updates calculation parameters automatically. The machine learning engine feeds actual delivery successes and return results back into core prediction logs to continuously refine forecasting models.
Real-Time Model TuningWhy It Matters
Shift from reactive return processing to proactive payout protection.
Reducing RTO rate by even a few percentage points has an outsized impact on margin, because the cost of a returned shipment is roughly double a normal one — and that's before counting the lost sale. Most RTO-reduction strategies act after a delivery has already failed. Prediction changes the timing entirely: it lets you intervene — confirm an address, switch to prepaid, or hold for manual review — before the shipping cost is even incurred.
How It Works
Five steps mapping risk profiles and executing automatic corrections before dispatch.
Order Placed
Order is loaded from sales channels and enters the Shiplystic system.
Scored Instantly
The AI model parses customer history, zone delivery rates, and address parameters.
Intervention Trigger
High-risk bookings trigger address verify alerts or prepayment request links.
Standard Path
Verified and low-risk orders clear directly to packaging without shipping delays.
Model Learns
Delivery outcomes route back to train weights, improving accuracy over time.
Who This Is For
Designed for merchant teams looking to eliminate RTO margin leaks.
COD Sellers
COD-heavy brands where cash collection risk and high undelivered ratios limit growth capacity.
Enterprise Sellers
Sellers with large volumes who need automated rules rather than reviewing every order manually.
3PL Operators
Operators looking to reduce return freight waste across multiple client portfolios programmatically.
Finance Teams
Finance leaders who want measurable, data-driven return reductions over arbitrary policy changes.
Frequently Asked Questions
Understand the mechanics of pre-dispatch risk assessment and reduction workflows.
What data does the RTO prediction model use to score an order?
The model analyzes address quality scores, pincode-level historical delivery success rates, courier partner delivery reliability in that zone, payment mode (COD vs. prepaid), and historical customer order patterns. We also analyze buying velocity, device markers, and regional cash-on-delivery success rates to generate the score.
What happens automatically when an order is flagged high-risk?
High-risk orders trigger configured interventions. The order is placed on a temporary hold and triggers an automated WhatsApp message offering a discount if they convert to prepaid, or requiring address confirmation before dispatch.
Does prediction accuracy improve over time, or is it a fixed model?
The model is designed to improve continuously as more delivery outcomes are fed back into it. Our current trained models achieve a 92% RTO prediction accuracy rating after parsing 10,000+ local deliveries, helping brands recover up to 25% of potentially lost sales.
