Improving Automation for SME Retention Without High-Cost Infrastructure

The Problem: The client was losing 40% of leads due to delayed follow-ups and inconsistent customer engagement. They lacked the budget or in-house skill to implement traditional enterprise-grade AI tools.

The Work

Applied Strategy & Systems Thinking
Designed behavior-based automation flows (e.g., missed calls, cart abandonment) for three businesses to improve retention and engagement.
Relevance to Education: Demonstrates how intelligent automation can support student retention and proactive interventions within digital learning systems.

The Impact

Response time improved by 65%, and the conversion rate from lead to sale increased by 38% in 90 days. The system was fully automated, low-maintenance, and cost-effective — a replicable model for automation-first readiness in under-resourced contexts.

Why It Matters

This case helped shape my broader thinking on AI accessibility for SMEs proving that you don’t need enterprise AI to deliver intelligent systems. You need local context, smart logic and systems that work from the ground up.

Faith Ombewa is a digital policy strategist and AI research analyst working at the intersection of AI ethics, policy and global inclusion. Her work focuses on analyzing research behind the development of AI models and systems in order to build frameworks that support AI adoption, readiness and equitable access for SMEs and in underserved economies; grounded in real-world constraints, not Silicon Valley assumptions.

Tools Used

  • Go High Level
  • Zapier
  • AI-powered chatbots
  • CRM workflows
  • Customer behaviour data
  • Notion

Skills Highlighted

  • Automation design
  • CX strategy
  • Behavioral Segmentation
  • Decision system logic
  • Low-code system architecture
  • Stakeholder onboarding
  • Customer journey mapping
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