VOL. XCIV, NO. 247

MOAT TYPE BREAKDOWN

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Tuesday, December 30, 2025

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Demand moat

Switching Costs General Moat

42 companies · 50 segments

A demand-side moat where customers face meaningful pain (time, money, risk, disruption) to switch providers. Use this generic label when switching costs are real but do not fit more specific categories (data/workflow lock-in, design-in qualification, format lock-in, procurement inertia, etc.).

Domain

Demand moat

Advantages

5 strengths

Disadvantages

5 tradeoffs

Coverage

42 companies · 50 segments

Advantages

  • High retention: customers renew to avoid the cost and risk of switching.
  • Pricing resilience: modest price increases can stick because replacement is expensive.
  • Long customer lifetime: once embedded, relationships persist for years.
  • Efficient growth via expansion: incumbents can upsell because they are already trusted and integrated.
  • Lower competitive intensity: challengers struggle to justify switching pain without a step-change benefit.

Disadvantages

  • Not permanent: strong competitors can win with a step-change product or painless migration.
  • Stored-up churn: dissatisfaction can accumulate and trigger sudden rip-and-replace events.
  • External shifts: standards, regulation, or platform changes can lower switching friction.
  • Trust fragility: major outages, breaches, or service failures can override switching pain.
  • Requires investment: must keep product and service quality high to prevent replacement projects.

Why it exists

  • Operational disruption: changing vendors interrupts workflows and creates downtime risk.
  • Migration complexity: moving configurations, rules, integrations, and historical context is costly.
  • Retraining and change management: users must relearn habits, processes, and internal playbooks.
  • Contractual and relationship inertia: renegotiations, approvals, and stakeholder coordination slow change.
  • Risk asymmetry: switching introduces failure modes that the incumbent already solved.

Where it shows up

  • B2B SaaS and enterprise infrastructure (admin configuration, integrations, permissions)
  • Critical operational vendors (payroll, accounting, payments, compliance tooling)
  • Outsourced services embedded in processes (IT managed services, BPO, logistics providers)
  • Regulated or audited workflows (security, privacy, reporting, quality systems)
  • Consumer ecosystems with history and personalization (preferences, libraries, saved data)
  • Any category where implementation and change management are non-trivial

Durability drivers

  • Deep embedding in workflows and mission-critical usage (critical path dependence)
  • High implementation complexity (customization, integrations, permissions, automation)
  • Demonstrated reliability and trust (security, uptime, support quality)
  • Continuous product improvement that maintains “good enough” advantage vs challengers
  • Customer success and relationship depth (executive alignment, ROI proof, roadmap influence)

Common red flags

  • Retention is high but usage is low, suggesting inertia masking weak value
  • Customers routinely multi-source and swap vendors with minimal disruption
  • Churn clusters around renewals, showing contracts were the only barrier
  • Competitors consistently win with migration assistance, implying switching costs are overstated
  • Major incidents cause immediate churn, meaning trust is the real moat, not switching friction

How to evaluate

Key questions

  • What are the real switching costs (migration effort, downtime risk, retraining, contract friction)?
  • Who bears the cost internally (IT, ops, finance), and how politically hard is change?
  • Can the customer run systems in parallel to reduce switching risk, or is it a big-bang cutover?
  • What events trigger switching (incidents, price hikes, consolidation, leadership change)?
  • Do competitors offer migration tooling or interoperability that collapses the switching cost?

Metrics & signals

  • Gross logo retention and churn reasons (how often customers actually replace you)
  • NRR and renewal pricing (ability to raise prices without churn)
  • Implementation length and customization depth (time-to-go-live, number of integrations)
  • Usage criticality (daily use, workflows dependent, number of internal stakeholders)
  • Incident and support metrics (outages, SLA adherence, ticket volume and resolution time)
  • Competitive displacement rates (losses in re-bids, rip-and-replace frequency)
  • Customer health signals (usage decline before churn, NPS/CSAT trends)

Examples & patterns

Patterns

  • Embedded vendors that survive because replacement projects take quarters and carry risk
  • Operational systems where configuration and training create meaningful inertia
  • Service providers where relationship knowledge and processes are hard to re-create
  • Consumer tools where history and personalization increase reluctance to switch

Notes

  • Use this label when the switching cost is real but the source is mixed or unclear. When possible, prefer a more specific moat label for sharper analysis.
  • Switching costs buy time. Long-term durability still depends on delivering value and avoiding trust-breaking failures.

Examples in the moat database

Curation & Accuracy

This directory blends AI‑assisted discovery with human curation. Entries are reviewed, edited, and organized with the goal of expanding coverage and sharpening quality over time. Your feedback helps steer improvements (because no single human can capture everything all at once).

Details change. Pricing, features, and availability may be incomplete or out of date. Treat listings as a starting point and verify on the provider’s site before making decisions. If you spot an error or a gap, send a quick note and I’ll adjust.