The Customer

The customer is a fast-growing India-based B2B e-commerce platform supplying automotive spare parts to independent mechanics across multiple cities. City-specific incentive programs—cashback, milestones, and rewards—play a central role in driving order frequency, cart value, and long-term mechanic retention.

These incentives are core growth levers, not auxiliary features. Accuracy, timeliness, and transparency directly impact mechanic trust and repeat usage. As geographic expansion accelerated, incentive logic became increasingly complex and harder to manage operationally.

What Triggered the Change

Cashback and milestone programs were managed through a combination of spreadsheets, scripts, and manual validation by operations teams. Weekly reward computation required significant coordination and review.

While workable at smaller scale, this model did not support growth from approximately 2,500 active mechanics per month toward a target of 70,000. Manual processes increased error risk, slowed execution, and created heavy dependence on engineering for rule changes.

Leadership identified incentive logic as a scalability bottleneck rather than a growth accelerator.

The Challenges

Manual, Error‑Prone Incentive Operations

Eligibility checks and reward calculations relied on manual effort. This consumed operational bandwidth and delayed weekly payouts.

Fragmented, City‑Specific Logic

Each city ran distinct schemes with different thresholds and conditions. Logic lived across scripts and queries, making updates slow and risky.

Limited Business Agility

Incentive logic resided in backend code. Even small changes required engineering involvement, slowing experimentation.

Performance Constraints

Existing coupon and reward APIs responded in ~800ms–1s, preventing real-time incentives at checkout.

No Central Governance

There was no single source of truth for incentive logic, making version tracking, testing, and rollback difficult.

Why the Previous Approach Fell Short

As incentives became more central to growth, operational weaknesses surfaced quickly.

Operations teams spent time validating numbers instead of optimizing schemes. Engineering teams became bottlenecks for business logic changes they did not own. Real-time incentives were impossible, as rewards were computed post-transaction.

Instead of accelerating growth, incentive systems began to limit it.

What the Customer Needed

The platform required a system that could:

• Model complex, city-specific incentive rules cleanly
• Allow frequent business-driven changes without code deployments
• Generate verifiable weekly outputs for finance and operations
• Integrate with coupon systems via APIs
• Execute decisions within sub‑200ms latency
• Act as a governed, centralized source of truth

The Solution: How Nected Was Implemented

The customer implemented Nected as a centralized decision and rule-execution layer for all incentive logic.

City‑Wise Cashback and Milestone Rules

Decision tables and workflows modeled each city’s incentive structure independently, making logic easier to understand and safer to evolve.

Business‑Owned Rule Management

Business and analytics teams manage incentive rules directly through Nected’s UI, eliminating day-to-day engineering dependency.

Weekly Outputs for Verification

In the initial phase, Nected generated weekly eligibility and reward reports (Excel/PDF), allowing operations and finance teams to validate outcomes before payout execution.

Progressive Automation of Coupon Issuance

After validation, decision outputs were integrated with downstream systems to automate coupon creation and issuance via APIs.

Low‑Latency Decision Execution

Nected was configured to execute cart-level incentive logic within a sub‑200ms target, enabling real-time rewards during checkout.

Centralized Governance and Versioning

All incentive logic now lives in one system with version history, testing, and rollback capabilities.

Before vs After Transformation

Quantitative Outcomes

• 100% elimination of manual weekly cashback computation  
  Weekly reward eligibility, milestone evaluation, and cashback calculations now run automatically through a governed decision layer. Operations teams no longer depend on spreadsheets, manual checks, or cross-team coordination, reducing execution time and removing human error from recurring incentive cycles.
• Sub‑200ms decision latency for cart‑level incentives  
  Incentive eligibility and discount logic executes in near real time during checkout, replacing post‑transaction reward computation. This allows incentives to actively influence cart conversion, order value, and purchase decisions instead of being applied retroactively.
• Scalable incentive architecture validated for 70,000 mechanics  
  Incentive logic now scales independently of operations effort. City expansion, new schemes, and mechanic growth no longer introduce proportional operational overhead or system instability.

Qualitative Outcomes

• Higher business agility
  Incentive experiments and rule changes happen without engineering delays.
• Improved mechanic trust
  Rewards are accurate, predictable, and timely.
• Lower operational risk
  Versioned logic reduces errors during scheme changes.
• Clear ownership and accountability
  One system defines how incentives operate across the platform.

Why the Customer Chose Nected

The decision centered on transforming incentives from a slow, back-office process into a real-time, scalable growth engine that could directly influence checkout behavior and mechanic engagement.

The platform needed a system where incentive logic could evolve as fast as the business itself. Business teams understood city-level schemes, milestones, and growth levers best, but previously lacked a safe way to translate that knowledge into production logic. Nected closed this gap by allowing business teams to define, test, and iterate on incentive rules directly—without relying on backend code changes or engineering release cycles.

At the same time, engineering and leadership required confidence that this flexibility would not introduce performance risk, governance gaps, or operational instability. Nected provided a governed decision layer with predictable latency, clear ownership, and full traceability, ensuring incentives could scale without becoming a source of errors or outages.

• Decision tables and workflows for complex incentive modeling  
  City-specific cashback schemes, milestones, and thresholds could be expressed in structured, readable formats that reduced ambiguity and made changes safer.
• Business-friendly rule management without code  
  Analytics and operations teams manage incentive logic independently, removing engineering bottlenecks while preserving control.
• API-first, low-latency execution  
  Incentive decisions execute at checkout speed, enabling real-time discounts and rewards that influence purchasing behavior.
• Phased rollout with verification and control  
  The team moved from manual validation to full automation incrementally, reducing risk while maintaining trust in outcomes.

Together, these capabilities allowed the platform to scale incentive programs aggressively—across cities and mechanic cohorts—without scaling operational complexity, engineering dependency, or execution risk.