---
title: "Proprietary data"
description: "Data that cannot be reassembled at a sane price: indexes, crawls, live feeds, archives, maps, unique datasets. The formula of the moat is capital × time: even with the money, a rival needs years to accumulate the history."
canonical: https://moa.giglabo.com/moats/3/
locale: en
---

# Proprietary data

> Markdown twin of https://moa.giglabo.com/moats/3/ — the same content as the HTML page, a fraction of the bytes.
> Every page of this site has one: append `.md` to any URL, or `index.md` to a directory URL.
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- Sheet 3 / 35

## Passport

- **Rock**: Assets
- **Depth**: 2.5 · Drill rig
- **Time to dig**: 3–10 years
- **Capital**: ◐ · medium
- **Solo**: ✓ solo-reachable
- **AI**: → eroding
- **Rent**: ~ partly

## Sample

- **Share of apps**: 11.5%
- **No-rate**: 57%
- **Median price**: $29

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

Data that cannot be reassembled at a sane price: indexes, crawls, live feeds, archives, maps, unique datasets. The formula of the moat is capital × time: even with the money, a rival needs years to accumulate the history.

## How it is built

### Ahrefs and Semrush — crawling as capital construction

Ahrefs has crawled the web continuously with its own bot for more than ten years and keeps a historical index of links. To repeat it you would have to build the infrastructure of a small search engine and then wait years for the history to accrue — today's backlinks can be collected, ten years of their movement cannot. The moat is double: hardware and software, plus time that cannot be reproduced.

### Waze — the users generate the data

Waze never bought traffic data; drivers create it by the simple act of driving with the app open. That is a data flywheel: more users → more accurate traffic → a more useful product → more users. The moat reinforces itself at no collection cost, while a challenger first has to find users it cannot attract without the data.

### AllTrails and Strava — a user-generated archive

Years of user tracks, reviews, photographs and heatmaps. Each unit is cheap, the aggregate cannot be reproduced: you cannot pay for fifteen years of other people's hikes. User-generated content plus time is the cheapest way for a small team to build a data moat.

## How it is bypassed

### OpenStreetMap against commercial maps — open data covers 80% of the cases

Google and TomTom spent billions on cartography, but for a great many products OSM is enough: the community built a free alternative, and an entire industry grew on top of it (Mapbox among others). A data moat only protects the cases that need the genuinely unique part of the data; everything else is commoditised over time by open equivalents — Common Crawl does the same to proprietary crawls.

### Waze against TomTom and Navteq — change the collection technology

Navteq and TomTom built their moat with fleets of scanning cars, hundreds of millions in capital expenditure. GPS in every smartphone zeroed that investment out: Waze collected roads and traffic for free, through its users' hands. The lesson: a data moat is tied to the technology used to collect it, and a new technology — today, LLM synthesis from public sources pressing on directories like ZoomInfo — can make an expensive archive unnecessary.

### Buy the raw material wholesale

Wholesalers always grow around big data: DataForSEO and its kind sell crawl and SEO data as an API. The attacker does not need to rebuild the Ahrefs index — it buys the raw material and competes on interface, workflow and price. The moat does not disappear, but it shifts up the stack: only the part of the data nobody sells is still protected.

## Verdict

Build it with a flywheel — data as a by-product of use — plus time. Bypass it with open data, a new collection technology, or by renting the raw material from wholesalers.

## Related

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