Switching Costs: How 35 Top Websites Use It

What is Switching Costs?

Switching costs are the practical price a customer pays to leave a product for a competitor — lost integrations, reconfigured workflows, retraining a team, or migrating data — and they exist on a spectrum from trivial to prohibitive regardless of how satisfied the customer is. On a marketing page, this shows up as messaging about integration depth, data portability, or workflow customization, framed around how deeply the product embeds into a customer's existing operations.

Switching costs accumulate naturally the longer a product is in use, more integrations connected, more historical data accumulated, more team members trained on a specific workflow, which is part of why retention curves usually improve for customers who make it past the first few months. A company can also design for this deliberately, by making integrations easy to add and hard to casually walk away from, or by encouraging workflow customization that increases a customer's investment in the specific way they've configured the product. The ethical line matters here: switching costs built from genuine value the customer would miss, like accumulated data or a customized workflow, are a legitimate retention strategy, while switching costs built from deliberate lock-in, like proprietary formats that block data export, invite regulatory scrutiny and customer resentment once discovered. A page can lean into real switching costs honestly, highlighting integration depth or workflow investment as a reason customers stay, without ever implying data will be held hostage if someone wants to leave.

How do top websites use Switching Costs?

Real examples from our audits — each excerpt is what our analysis found on the live page.

• raycast.comscores 63/100

  Ecosystem as Moat and Growth Loop

  Thousands of community extensions create a classic network-effects moat: more builders → more extensions → more value → more users. The API section invites users to build, triggering IKEA-effect investment that compounds switching costs.

• asterode.aiscores 42/100

  Switching Costs — Built-In Lock-In Through Memory Layer

  The memory and pages features create natural switching costs — the more context and saved pages a user accumulates, the harder it becomes to leave. This is ethical lock-in through value accumulation, not dark patterns.

• simonara.appscores 55/100

  Switching Costs — People Vault Data Accumulation

  The People Vault and gift history create natural data lock-in. The more users add, the more valuable the product becomes and the higher the switching cost — a well-designed retention mechanic.

• thedecentproposal.comscores 40/100

  Switching Costs — Integration Stickiness via CLI and API

  CLI, API keys, JSON schema, and webhook integrations create workflow-level stickiness. Once developers integrate proposal generation into their pipelines, switching costs become significant — a strong retention moat.

• vercel.comscores 58/100

  Network Effects — Multi-Provider AI Ecosystem

  By positioning as a gateway to all AI models and all frameworks, Vercel creates a hub effect — the more providers connect, the more valuable the platform becomes, and the higher the switching cost for developers already integrated.

• linear.appscores 62/100

  Network Effects — AI Agent Ecosystem as Moat

  The AI agent integration ecosystem creates network effects and switching costs simultaneously. As more tools connect via MCP, Linear becomes a hub — making it harder to leave and more valuable to join.

• notion.soscores 68/100

  Switching Costs — Deep Product Ecosystem

  Notion positions itself as a deep ecosystem where more usage creates more value. The Company HQ structure and cross-tool search create high switching costs — once a team builds their workspace, leaving means losing accumulated structure and context.

• figma.comscores 58/100

  Switching Costs — Deep Integration Positioning

  By positioning Figma as the connective tissue between design and development (MCP, Dev Mode, shared systems), the page communicates high ethical switching costs — leaving means rebuilding the entire design-to-code pipeline.

When does Switching Costs backfire?

Switching Costsfails when it's vague, misplaced, or manufactured. These issues came up in real audits:

• No Switching Cost Signals

  The page gives no indication of what makes Minibord sticky — a gap that weakens the long-term retention case for evaluators.

• Switching Costs — No Stickiness Mechanics Visible

  Users can recreate their work anywhere — there's no visible reason to return to Screenshot Otter specifically next time.

• Switching Costs — Not Addressed for Repeat Raises

  The platform's stickiest feature — the reliability score — is mentioned but its retention power is never made explicit to founders.

• Switching Costs — Not Surfaced as a Selling Point

  You're not leveraging the stickiness of your product as a competitive moat.

Switching Costs vs Endowment Effect: what's the difference?

Switching costs are structural and objective: the actual integrations, data, and configuration a customer would lose by leaving, which exist whether or not the customer feels attached to them. Endowment effect is psychological: a customer values what they already have simply because they possess or use it, independent of whether leaving would carry any real practical cost. A customer can feel a strong endowment effect toward a barely-used free trial with zero real switching cost, and conversely feel no attachment at all to a heavily integrated setup that would be genuinely painful to migrate away from.

Read the full Endowment Effect guide

How do you apply Switching Costs?

Increase switching costs ethically: integrations, data accumulation, workflow customization, team adoption.

What else should you know about Switching Costs?

35 of the 72 sites we've audited use Switching Costs, but 5 of them execute it in a way that costs points — presence and execution aren't the same thing. It's most often confused with Endowment Effect, which solves a different problem — see the comparison above.