Churn Reduction & Merchant Re-activation

Role

Lead — Continuous Improvement & Retention Operations

Team

Sales Support, Customer Support, Data, Product, Finance, Ops

Tools

Tableau dashboards, CRM, automated SMS triggers, internal ticketing workflows

Philosophy

Predictive retention + proactive merchant support + experience-driven loyalty

01

Context

Merchant churn directly impacts revenue, terminal utilization, and long-term market competitiveness. The organization historically treated churn as a lagging event, calling merchants only after they left.

The goal was to build a predictive and proactive churn engine focused on experience, communication, and support recovery.

Business Challenge

Pre-Intervention Reality

  • • No churn segmentation or journey view
  • • Support and sales did not coordinate on retention
  • • Payout perception significantly impacted merchant trust
02

Problem

Deep analysis uncovered two main themes driving merchant churn.

1. Experience-Driven Churn

40% of churn linked to payout experience — not system performance; merchant perception of payout timing created trust issues.

Churn Analysis Dashboard

Churn root cause analysis showing payout perception as primary driver

2. Operational Gaps

"We were reacting to churn instead of preventing it. Merchants left before we even knew they were unhappy."

— Retention Team Insight

03

Ideation

Goal: Intervene early, automate touchpoints, personalize recovery.

01

Churn Segmentation

Region, MCC, payout behavior, complaints, ticket history, annual volume-based merchant buckets.

02

Playbooks

Tailored scripts for at-risk vs churned vs pull-out merchants with empathy-driven messaging.

03

Triggers

SMS automation + CRM extraction + weekly dashboards for proactive intervention.

04

Ownership

Dedicated retention squad created with clear KPIs and accountability.

05

Experience Fix

Transparent payout communication model to rebuild merchant trust.

04

Process

A phased approach combining analytics, automation, and organizational change.

Phase 1 — Analytics & Segmentation

Merchant Segmentation Model

  • At-risk: 20–60 days inactive
  • Churned: > 60 days inactive
  • Pull-out intents: Captured via support system

Phase 2 — Retention Engine Build

Retention Process Flow

Automated retention workflow from detection to recovery

Phase 3 — Experience Intervention

"We moved from reacting to churn to preventing churn through proactive outreach and payout clarity."

— Program Reflection

05

Implementation

Execution balanced technical automation with organizational change management and merchant experience improvement.

Technical Implementation

Organizational Implementation

Retention Playbook Components

  • Detection: Automated identification of at-risk merchants
  • Outreach: SMS + phone calls with empathy scripts
  • Support: Fast-track issue resolution for churned merchants
  • Recovery: Personalized incentives and payout clarity
06

Results

The retention program delivered measurable impact across churn reduction, merchant reactivation, and revenue recovery.

8%
Churn Reduction
Month-over-month decrease
718
Merchants Reactivated
Returned to active status
SAR 12M
TPV Regained
Revenue recovery
SAR 2.7M
Churn Cost Avoidance
Retained value

Strategic Outcome

"We transformed churn from a reactive cost center into a proactive retention engine that protects revenue and builds merchant loyalty."

— Strategic Impact

Next Project

Lean Process Implementation