Switching costs are the one-time financial, procedural, and psychological burdens a customer must absorb to move from one supplier to a competing one. When those burdens are high enough that the benefit of switching no longer outweighs the friction of leaving, the incumbent gains pricing power and durable revenue even without a beloved product. The central tension of this moat is that it is built on customer captivity rather than customer love — the relationship can be profitable and sticky while being, at the margin, resented. That makes switching costs one of the most durable but also one of the most quietly eroding moat sources: it holds firmly until a competitor finds a way to absorb the switching cost on the customer's behalf.

How it's formed

The economic foundation was formalized by Michael Porter in Competitive Strategy (1980), who treated switching costs as both a barrier to entry and a lever that reduces buyer power. The deeper microeconomic theory comes from Paul Klemperer (notably his 1987 and 1995 work, and Farrell & Klemperer's 2007 survey), which shows that switching costs split a market into a sequence of mini-monopolies over individual locked-in customers, and that firms compete fiercely ex ante to capture customers they can later harvest — hence introductory discounts, "free" setup, and even below-cost penetration pricing.

Practitioners (Pat Dorsey, Morningstar) decompose switching costs into recognizable types:

• Financial / contractual: termination fees, lost loyalty balances, new hardware purchases, multiyear contracts. (Gillette's razor-and-blade model is the archetype — the cheap razor locks in repeat blade purchases.)
• Procedural: the time, retraining, and data migration to learn and reconfigure a new system. This dominates enterprise software (SAP, Oracle databases) and is why ERP systems are notoriously sticky.
• Relational / integration: deep workflow entanglement, where the supplier is embedded in the customer's own processes. Auto-parts suppliers designed into multi-year OEM vehicle programs (vehicle platforms typically run several years) are a classic case.
• Psychological / risk: fear of disruption where the cost of failure is high — payment processors, medical devices, mission-critical infrastructure.

How it's used in practice

Analysts hunt for switching costs indirectly through financial symptoms rather than direct measurement:

• Low, stable customer churn and long average customer tenure.
• Net revenue retention (NRR) above 100% — in SaaS this signals that locked-in customers expand spend faster than others leave; it is the single most-watched proxy for switching-cost stickiness.
• High and persistent gross margins plus the ability to push through price increases without volume loss (pricing power being the output of a real moat).
• Qualitative integration depth: how many of the customer's workflows, datasets, or downstream systems would break on exit.

The asymmetry of the moat also dictates strategy: because firms must compete to acquire customers before they can exploit them, a switching-cost business is often most attractive when it is winning the land-grab phase (gaining share at low or negative early margins) and most cash-generative once the installed base is mature.

Adoption, debate & evidence

Switching costs are a mainstream, well-accepted pillar — one of the four moat sources in Morningstar's framework (alongside intangibles, network effects, and cost advantages). In Morningstar's coverage they have been described as the third most common moat source, applying to roughly 21% of a ~1,500-company universe (per a Morningstar analyst article; the exact figure is dated and coverage-specific, so treat it as illustrative rather than current).

The honest caveat that even moat proponents stress: switching costs rarely stand alone. The same Morningstar work reported that ~88% of its switching-cost companies also carried a secondary moat (most frequently intangible assets) — implying that pure switching-cost stickiness is often insufficient on its own. Academic IO theory adds a more contested wrinkle. The dominant theoretical view — Klemperer's 1995 survey concludes there is a "strong presumption" that switching costs make markets less competitive (i.e., raise prices and profits on net) — supports the moat case. But this is not unambiguous: the ex-ante competition to acquire customers can dissipate much of the ex-post rent, so whether a switching-cost business is genuinely attractive depends on how restrained acquisition competition is (Klemperer 1995; Farrell & Klemperer 2007). Empirically the picture is mixed: Dubé, Hitsch & Rossi ("Do Switching Costs Make Markets Less Competitive?", 2009) find that at switching-cost levels seen in real data, equilibrium prices can actually fall, and studies of telecom/800-number portability show that reducing switching costs increases competition — confirming the rents are real but also that regulators and rivals actively target them.

Strengths & limitations

When it works: high-consequence, deeply-integrated, mission-critical relationships — enterprise databases/ERP, payments rails, embedded industrial components, clinical systems — where the cost of a botched migration dwarfs any price the incumbent charges.

When it fails:

• A competitor subsidizes the switch (the recurring killer — paying migration costs, offering free conversion tools, automated data import).
• Technology resets the integration layer (cloud/API standards, open data formats, interoperability mandates) and collapses procedural costs.
• The moat breeds complacency: captive, unhappy customers defect en masse the moment a credible escape appears (the alternative-competition risk Morningstar flags, e.g., home-sharing eroding hotel franchise stickiness).

The #1 misuse: confusing high prices today with a durable moat. Pricing power is a symptom; if it rests on customer resentment rather than genuine value, it is borrowed time. The analyst must ask whether the switching cost is widening, stable, or being actively dismantled — a static snapshot is misleading.

Sources

• Morningstar — "Switching Costs Boost Firms' Competitive Advantage" (prevalence ~21%, ~88% with secondary moats; auto-parts, hotels, advertising, publishing examples). Figures are dated/coverage-specific.
• Pat Dorsey, The Little Book That Builds Wealth (2008) and Morningstar interviews — four-moat framework; "captive not loyal" SAP/Oracle point.
• Michael Porter, Competitive Strategy (1980) — switching costs as entry barrier / buyer-power lever.
• Paul Klemperer, "Competition when Consumers have Switching Costs," Review of Economic Studies 62(4):515–539 (1995) — "strong presumption" that switching costs make markets less competitive; ex-ante/ex-post pricing tension. Plus Farrell & Klemperer, "Coordination and Lock-In" (2007) survey.
• Dubé, Hitsch & Rossi, "Do Switching Costs Make Markets Less Competitive?", Journal of Marketing Research (2009) — empirically, prices can fall at realistic switching-cost levels (counterweight to Klemperer's theory).
• Corporate Finance Institute; Wall Street Prep; VanEck Moat Investing — practitioner definitions, types, and Gillette / self-storage / auto-parts examples.
• Empirical: studies on 800-number / telecom number portability (switching-cost reduction increases competition).

Dispute flagged: theory (Klemperer 1995) presumes switching costs are net value-accretive to incumbents; some empirical IO work (Dubé et al. 2009) finds the opposite at realistic cost levels, and the ex-ante land-grab can compete away ex-post rents. The truth is conditional on market structure and the intensity of acquisition competition.