Channel Loyalty Analytics & AI for the Tyres Industry | ChannelLoyalty.ai

ChannelLoyalty.ai is the AI Operating System purpose-built for channel growth in India's tyres industry. We transform every QR scan, claim, and transaction into actionable secondary-sales intelligence. Our WhatsApp-first, instant UPI, scan-and-earn platform engages fitment mechanics and fleet operators where they work—at the workshop. Used by 100+ enterprise brands, we deliver churn prediction 60-90 days early, next-best-action playbooks per partner, and attribution-grade ROI dashboards. Stop guessing. Start growing fitment share systematically.

India's tyres brands face relentless fitment-share erosion. Fleet operators switch based on price and availability—not loyalty. Fitment mechanics, who drive 70% of replacement volumes, face margin squeeze from competing brands and unorganized players. Traditional incentive schemes lack real-time visibility into who's buying what, where, and why. Brands cannot predict when a key mechanic or operator will defect. Fitment data remains siloed in invoices and sales calls. Without predictive intelligence and micro-targeted engagement, brands hemorrhage fitment share to agile competitors. The cost of losing one fleet account often exceeds the investment in retention.

Generic B2C loyalty platforms ignore channel dynamics. Manual scheme administration wastes time on claim verification instead of insight extraction. Excel-based tracking provides zero predictive power—you react to churn, never prevent it. WhatsApp blasts lack personalization; mechanics ignore generic messages. No integration with fitment workflows or UPI settlement. Schemes reward transaction volume, not fitment share growth. Without anomaly detection, fraud and channel conflict go undetected. Most tools are designed for retail; tyres channel requires mechanic-centric, fleet-operator-aware engagement and real-time settlement.

Our proven 4-point program for tyres channel growth:

• Predictive Churn Modeling: AI identifies at-risk mechanics and fleet operators 60-90 days before defection; triggers proactive retention plays.
• Fitment Share Optimization: Track fitment-share per mechanic, per brand, per vehicle segment; compare against peer benchmarks; auto-recommend next-best-action.
• Scheme & Spend Automation: Real-time claim processing, micro-targeted incentives (SMS, WhatsApp, UPI rewards), and fraud-flagged anomalies—zero manual overhead.
• Attribution-Grade ROI Dashboards: Connect every scan, claim, and fitment to revenue impact; prove scheme ROI and reallocate spend to top performers.
• Mechanic-Centric Engagement: Instant WhatsApp notifications, one-tap UPI payouts, QR-scan-and-claim workflows, and leaderboards that drive fit-ment pride.

ChannelLoyalty.ai combines four core capabilities for tyres:

• Churn Prediction Engine: ML model analyzes transaction frequency, fitment trends, and competitive signals to flag risk 60-90 days early.
• Next-Best-Action AI: Per mechanic, per fleet operator—recommends incentive type (cashback, SPIFs, co-op spend), timing, and channel (WhatsApp, SMS, UPI).
• Scheme & Spend Orchestration: Automated claim ingestion from GST/TDS invoices, instant UPI settlement to mechanic wallets, fraud detection for duplicate or inflated claims.
• Fitment Share & ROI Attribution: Dashboard shows fitment-share trajectory by brand, mechanic, segment, and geography; ties secondary sales back to scheme investment. Real-time leaderboards drive competition and lift fitment velocity.

A leading Indian radial-tyres brand deployed ChannelLoyalty.ai across 800 fitment mechanics in South India. Within 60 days: identified 120 high-risk mechanics showing declining fitment transactions. Triggered micro-targeted WhatsApp campaigns (personalized incentives via SMS, instant UPI payouts). Result: 87% of flagged mechanics re-engaged; fitment share in those workshops grew 23% YoY. Scheme ROI improved 34%—from ₹3.20 per ₹1 invested to ₹4.27. Fraud detection caught ₹12 lakhs in duplicate claims, improving payout discipline. Mechanics loved instant settlement; NPS jumped from 52 to 78.

30-day rapid rollout:

• Week 1: Data audit & API setup. Ingest 90 days of historical invoices, claims, and fitment transactions. Map mechanic and fleet-operator IDs.
• Week 2: Churn model training & validation. Deploy early-warning dashboard; identify first cohort of at-risk partners.
• Week 3: Scheme template design & WhatsApp integration. Set up instant UPI payouts, QR scan-and-earn workflows. Pilot with top 100 mechanics.
• Week 4: Full rollout & optimization. Scale to all mechanics; activate ROI attribution dashboard; begin weekly performance reviews.

Track these KPIs weekly:

• Fitment Share %: Brand fitment volume as % of total tyres fitted by each mechanic (primary north-star metric).
• Churn Rate (60-day): % of mechanics with zero fitment transactions over rolling 60-day window.
• Scheme ROI: Revenue from re-engaged/flagged mechanics ÷ incentive spend per cohort.
• Claim Processing Time: Average days from invoice to UPI settlement (target: <2 days).
• Fraud Detection Rate: % of anomalous claims flagged and investigated.
• Mechanic NPS: Quarterly survey on settlement speed, app usability, incentive fairness.