How Spinny Built a Real-Time Inventory-to-Intent Matching Engine With WebEngage.

At Spinny, delivering a seamless customer experience at scale depends on how quickly we can respond to real-time customer and inventory signals. One of our key challenges was connecting dynamic inventory with users who had already shown intent, while keeping every interaction timely and relevant. With WebEngage, we built an automated engagement framework that brings together inventory updates, customer preferences, and behavioral signals. This has helped us reduce manual intervention, improve execution speed, and deliver more relevant, data-driven customer journeys at scale.

Rahul Kheterpal

General Manager Marketing, Spinny

At Spinny, delivering a seamless customer experience at scale depends on how quickly we can respond to real-time customer and inventory signals. One of our key challenges was connecting dynamic inventory with users who had already shown intent, while keeping every interaction timely and relevant. With WebEngage, we built an automated engagement framework that brings together inventory updates, customer preferences, and behavioral signals. This has helped us reduce manual intervention, improve execution speed, and deliver more relevant, data-driven customer journeys at scale.

Rahul Kheterpal

General Manager Marketing, Spinny

20X

Increase in conversions compared with the previous manual approach.

12%

Contribution to Spinny’s overall revenue.

Summary

Spinny partnered with WebEngage to build a real-time inventory-to-intent matching engine that connected newly available cars with customers who had already shown purchase interest.

  • Matched new inventory with customer preferences and behavioral signals.
  • Triggered journeys instantly when new cars became available.
  • Used segmentation and personalization to identify the right buyers.
  • Delivered direct-to-car experiences through deep links to relevant listings.
  • Combined WhatsApp and Push Notifications to improve customer reach.

Turning New Inventory Into Real-Time Customer Demand

Spinny is a full-stack platform for buying and selling certified used cars through a digital-first experience supported by home and hub test drives.

When a car became available, the opportunity was highly time-sensitive. Customers who had already shown interest needed to be connected with relevant inventory before their intent diminished.

The earlier approach relied on broad campaigns and manual effort, creating delays between inventory availability and customer communication.

They needed a system that could identify relevant users instantly and connect them with the right vehicle at the right moment.

WebEngage Solution

WebEngage helped Spinny create a real-time inventory relay using the Relay feature.

When a new car was added, the journey was triggered automatically. The system matched inventory against customer preferences using behavioral and intent signals.

The matching logic considered:

  • Body-type preference
  • Browsing behaviour
  • Model-level interest
  • Lead activity
  • Previous product-page views
  • Standard or MAX inventory eligibility

Instead of directing customers to a generic inventory page, they created direct-to-car experiences that connected customers with the exact vehicle they matched.

The engagement model included:

  • Real-time inventory triggers
  • Preference-based matching
  • Segmentation
  • Personalization
  • Suppression logic
  • WhatsApp-first communication
  • Push Notification fallback
  • Direct product-page deep links

The Business Impact

Spinny results card

  • Real-time inventory-to-intent matching
  • Daily automated execution
  • Preference-level personalization
  • Direct product-page deep links
  • Reduced manual campaign effort

The Bigger Picture

Spinny moved from scheduled, broad communication to a real-time engagement model built around inventory availability and customer intent.

Every new listing became an opportunity to reconnect with customers who had already shown interest. Personalized matching reduced the gap between customer preference and available inventory.

This created a scalable framework where inventory signals, behavioral data, and automated journeys worked together to deliver more relevant vehicle discovery experiences.

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