---
title: "Switching costs"
description: "Accumulated history, configuration and habit make leaving painful regardless of how good the product is. In the sample this is the most half-hearted tag of all: the moat is real, but it is rarely enough on its own."
canonical: https://moa.giglabo.com/moats/5/
locale: en
---

# Switching costs

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- Sheet 5 / 35

## Passport

- **Rock**: Locks
- **Depth**: 2 · Excavator
- **Time to dig**: 1–3 years
- **Capital**: ○ · low
- **Solo**: ✓ solo-reachable
- **AI**: ↓ under attack
- **Rent**: ✗ not for sale

## Sample

- **Share of apps**: 4.4%
- **No-rate**: 24%
- **Median price**: $15

Figures from the canivibecodeit sample. No-rate is the share of apps carrying this tag that cannot be vibe-coded — a proxy for structural strength. Only the first thirteen mechanics were measured.

## Essence

Accumulated history, configuration and habit make leaving painful regardless of how good the product is. In the sample this is the most half-hearted tag of all: the moat is real, but it is rarely enough on its own.

## How it is built

### Salesforce and Jira — growing into the processes

Years inside the system accumulate custom fields, automations, reports, integrations and — above all — trained people whose qualification is tied to the tool: a Salesforce admin is a profession in itself. Leaving means not a change of software but a re-engineering of company process plus retraining. The moat is not dug with features but with depth of configurability: the more the customer has set up themselves, the harder they are to move.

### Apple — the ecosystem lock

iMessage (leave and you fall out of the group chats), iCloud with the photos and backups, purchased apps, a Watch that works only with an iPhone. Every element is weak, the sum is close to insurmountable: switching means replacing everything at once. The pattern: multiply the points where the user's history accumulates, and tie the products to each other.

### QuickBooks — a lock held by a third party

What holds the customer is not only the transaction history but the accountant who knows only QuickBooks. The switching cost is externalised into an ecosystem of specialists trained on your product. Certifications and partner training are a way to dig this moat with other people's hands.

## How it is bypassed

### Linear and HubSpot — importers and white-glove migration

The standard counter-attack is to move everything out of the incumbent in one click: Linear imports from Jira, HubSpot migrates from Salesforce, and for large accounts a team does the move for you. A moat made of data holds exactly until a competitor invests in a good importer; after that only the habits are left.

### Notion — greenfield instead of conversion

Do not argue with people who have already grown in; take the ones who have not grown into anything yet — new startups, new teams, new projects. For a new user the switching cost is zero, and in five years yesterday's greenfield is the market. A patient bypass: the incumbent keeps its base and stops getting new customers.

### AI migration and regulated portability

Agents already move configuration, history and content between systems at almost no cost, and the routine part of the switching cost is falling. A telling episode from March 2026: Claude shipped import-memory — the whole accumulated memory carried over from ChatGPT in two copy-pastes. The main lock of AI assistants, months of trained context, became a two-minute procedure, and ChatGPT itself became the export tool: "let me download my own data" cannot be blocked. Regulation pushes in the same direction with GDPR portability and open banking. What remains is the human half of the lock — habit and retraining — and that is its weakest layer.

## Verdict

Build it with depth of configuration, accumulated history and an ecosystem of trained people. Bypass it with importers, with new users, and with automated migration — this moat is getting cheaper to cross faster than most.

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