README.md

---
pretty_name: "Let's Encrypt Adoption Among the Top 5,000 Companies"
license: cc-by-4.0
tags:
  - cybersecurity
  - web-technologies
  - technographics
  - ssl
  - tls
  - lets-encrypt
  - technology-adoption
  - company-data
  - business
  - websites
task_categories:
  - tabular-classification
  - tabular-regression
language:
  - en
size_categories:
  - 1K<n<10K
---

# Let's Encrypt Adoption Among the Top 5,000 Companies

## Overview

This dataset analyzes Let's Encrypt adoption across the world's top 5,000 companies.

It identifies companies whose websites use Let's Encrypt issued SSL/TLS certificates, providing a snapshot of Let's Encrypt adoption among large organizations.

The dataset is intended for technology research, cybersecurity analysis, technographic research, competitive intelligence, market analysis, and data science.

Source and full statistics: **[Let's Encrypt usage statistics on StackScan](https://www.stackscan.com/technology/lets-encrypt)** — global heatmap, usage by country and industry, top websites and companies, and the full list.

## Dataset Highlights

* 5,050 large companies, one row per company, no duplicate domains
* Every company in the file is a Let's Encrypt adopter — adoption is the selection criterion, not a column
* Every company has 5,001 or more employees
* Firmographic context included: industry, headcount band, country, locality, founding year, LinkedIn profile
* Suitable for research, visualization, segmentation, and machine learning projects

## What is Let's Encrypt?

Let's Encrypt is a free, automated, and open Certificate Authority that provides SSL/TLS certificates. It enables websites to deploy HTTPS without purchasing certificates from traditional commercial certificate authorities.

## Files

| File | Rows | Notes |
| ---- | ---- | ----- |
| `Lets-Encrypt.csv` | 5,050 | Same content as the spreadsheet; this is the file the dataset viewer reads |
| `Lets-Encrypt.xlsx` | 5,050 | Excel copy for manual analysis |

## Dataset Fields

15 columns. Coverage is the share of the 5,050 rows where the field is populated.

| Column | Type | Coverage | Description |
| ------ | ---- | -------- | ----------- |
| `Popularity Rank` | int64 | 100% | Website popularity rank; lower is more popular. Ranges from 5 to 1,959,064 |
| `Domain` | string | 100% | Primary website domain. Unique across the file |
| `Company Name` | string | 100% | Company or organization name, lowercased |
| `Company Size` | string | 100% | Employee band. Two values only: `5001-10000` (2,245) and `10001+` (2,805) |
| `Year Founded` | float64 | 73.4% | Founding year |
| `Industry` | string | 99.7% | Industry label, lowercased. 142 distinct values |
| `LinkedIn URL` | string | 100% | Company LinkedIn profile path |
| `Locality` | string | 85.1% | City or region, where available |
| `Country` | string | 100% | Company or website country. 140 distinct values |
| `TLD` | string | 100% | Top-level domain. 355 distinct values |
| `Language` | string | 0.6% | Detected site language. Largely empty |
| `Instagram` | string | 0.4% | Instagram handle. Largely empty |
| `Twitter` | string | 0.2% | Twitter handle. Largely empty |
| `YouTube` | string | 0.2% | YouTube channel. Largely empty |
| `TikTok` | string | 0.1% | TikTok handle. Largely empty |

The five social and language columns are present for schema compatibility with other StackScan exports and are populated for fewer than 1% of rows. Treat them as optional.

## Methodology

Websites were analyzed for technical fingerprints associated with Let's Encrypt. A company is considered a Let's Encrypt adopter when the relevant certificate or technology footprint is detected on its associated website.

Technology detection represents an observation at the time of collection and should not be interpreted as confirmation of an organization's complete infrastructure.

## Use Cases

This dataset can be used for:

* Technographic research
* Cybersecurity research
* SSL/TLS infrastructure analysis
* Market research
* Competitive intelligence
* Data science and machine learning
* Technology adoption analysis
* Academic research

## Important Notes

* Technology detection is based on publicly observable website signals.
* A detected Let's Encrypt certificate does not necessarily mean that Let's Encrypt is used across all of an organization's domains or infrastructure.
* Website infrastructure can change over time.
* Results represent observations from the dataset's collection period.
* The dataset should not be interpreted as an official statement from any company regarding its technology stack.
* Because every row is an adopter, this file supports questions of the form "what do Let's Encrypt adopters look like?" It cannot on its own answer "what share of large companies use Let's Encrypt?", which needs a comparable non-adopter sample.

## Citation

If you use this dataset, please cite it and link back to the source page.

**Plain text**

StackScan. (2026). *Let's Encrypt Adoption Among the Top 5,000 Companies* [Data set]. StackScan. https://www.stackscan.com/technology/lets-encrypt

**BibTeX**

```bibtex
@misc{stackscan_lets_encrypt_2026,
  author       = {{StackScan}},
  title        = {Let's Encrypt Adoption Among the Top 5,000 Companies},
  year         = {2026},
  publisher    = {StackScan},
  howpublished = {\url{https://www.stackscan.com/technology/lets-encrypt}},
  note         = {Dataset: \url{https://huggingface.co/datasets/stackscan/lets-encrypt}}
}
```

Source page: [Let's Encrypt usage statistics](https://www.stackscan.com/technology/lets-encrypt) — global heatmap, usage by country and industry, top websites and companies, and the full list.

## License

Released under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/). You are free to share and adapt the data, including commercially, provided you give appropriate credit.

Attribution must name StackScan and link to the source page:

> Data from [StackScan](https://www.stackscan.com/technology/lets-encrypt), licensed under CC BY 4.0.

For academic or published work, use the [citation](#citation) above instead.