---
pretty_name: "Let's Encrypt Adoption Among Large Companies and Organizations"
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:
  - 10K<n<100K
dataset_info:
  - config_name: default
    features:
      - name: Popularity Rank
        dtype: int64
      - name: Domain
        dtype: string
      - name: Company Name
        dtype: string
      - name: Company Size
        dtype: string
      - name: Year Founded
        dtype: float64
      - name: Industry
        dtype: string
      - name: LinkedIn URL
        dtype: string
      - name: Locality
        dtype: string
      - name: Country
        dtype: string
      - name: TLD
        dtype: string
      - name: Language
        dtype: string
      - name: Instagram
        dtype: string
      - name: Twitter
        dtype: string
      - name: YouTube
        dtype: string
      - name: TikTok
        dtype: string
    splits:
      - name: train
        num_examples: 5050
  - config_name: all-adopters
    features:
      - name: Popularity Rank
        dtype: int64
      - name: Domain
        dtype: string
      - name: Company Name
        dtype: string
      - name: Company Size
        dtype: string
      - name: Year Founded
        dtype: float64
      - name: Industry
        dtype: string
      - name: LinkedIn URL
        dtype: string
      - name: Locality
        dtype: string
      - name: Country
        dtype: string
      - name: TLD
        dtype: string
      - name: Language
        dtype: string
      - name: Instagram
        dtype: string
      - name: Twitter
        dtype: string
      - name: YouTube
        dtype: string
      - name: TikTok
        dtype: string
    splits:
      - name: train
        num_examples: 14697
  - config_name: commercial-ca-comparison
    features:
      - name: Popularity Rank
        dtype: int64
      - name: Domain
        dtype: string
      - name: Company Name
        dtype: string
      - name: Company Size
        dtype: string
      - name: Year Founded
        dtype: float64
      - name: Industry
        dtype: string
      - name: LinkedIn URL
        dtype: string
      - name: Locality
        dtype: string
      - name: Country
        dtype: string
      - name: TLD
        dtype: string
      - name: Language
        dtype: string
      - name: Instagram
        dtype: string
      - name: Twitter
        dtype: string
      - name: YouTube
        dtype: string
      - name: TikTok
        dtype: string
      - name: Certificate Authority
        dtype: string
    splits:
      - name: train
        num_examples: 10938
configs:
  - config_name: default
    data_files:
      - split: train
        path: Lets-Encrypt.csv
  - config_name: all-adopters
    data_files:
      - split: train
        path: All-Adopters.csv
  - config_name: commercial-ca-comparison
    data_files:
      - split: train
        path: Commercial-CA-Comparison.csv
---

# Let's Encrypt Adoption Among Large Companies and Organizations

## Overview

This dataset lists 5,050 large companies and organizations whose websites were found to use SSL/TLS certificates issued by Let's Encrypt. Each row carries firmographic context: industry, employee band, country, locality, founding year and LinkedIn profile.

Rows are ordered by website popularity rank, and the file covers the most popular slice of a larger pool of large organizations found to use Let's Encrypt. It is not a list of the world's largest or most popular organizations, and the rank is a property of the website rather than a measure of the organization's size or importance.

Collected in August 2026. Certificate choices change, so treat the data as a snapshot of that month rather than a current state.

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

Full Let's Encrypt statistics, including the global heatmap, usage by country and by industry, and the top websites, are published at [StackScan](https://www.stackscan.com/technology/lets-encrypt).

## Dataset Highlights

* Collected in August 2026
* 5,050 organizations, one row each, with no repeated domains
* Every organization in the file uses Let's Encrypt, so there is no adoption column. Adoption is the selection criterion
* Every organization has 5,001 or more employees
* 142 industries and 140 countries represented
* Not only private companies: 1,120 rows (22%) are government bodies, universities, schools, non-profits and similar institutions

## 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.

## Dataset Fields

Three files share the same 15 columns. The comparison file adds a sixteenth.

| Config | File | Rows | Contents |
| ------ | ---- | ---- | -------- |
| `default` | `Lets-Encrypt.csv` | 5,050 | The most popular adopters, by website popularity rank |
| `all-adopters` | `All-Adopters.csv` | 14,697 | Every adopter detected, including the 5,050 above |
| `commercial-ca-comparison` | `Commercial-CA-Comparison.csv` | 10,938 | Organizations using a commercial certificate authority and not Let's Encrypt |

```python
load_dataset("stackscan/lets-encrypt")                             # 5,050
load_dataset("stackscan/lets-encrypt", "all-adopters")             # 14,697
load_dataset("stackscan/lets-encrypt", "commercial-ca-comparison") # 10,938
```

`default` is kept for anyone already loading this dataset. For analysis, use `all-adopters`, because `default` is cut by website popularity and that cut is not neutral: it leans toward organizations in the United States and Germany, and toward government, retail and healthcare, relative to the full set.

Coverage below is for `Lets-Encrypt.csv`. It is a little lower in the full set, where `Year Founded` is 68.4% and `Locality` 78.6%, because less popular websites carry less firmographic detail.

| Column | Type | Coverage | Description |
| ------ | ---- | -------- | ----------- |
| `Popularity Rank` | int64 | 100% | Website popularity rank, lower being more popular. Ranges from 5 to 1,959,064. Rows are stored in ascending rank order |
| `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: `5001-10000` (2,245 rows) and `10001+` (2,805 rows) |
| `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% | Organization or website country. 140 distinct values |
| `TLD` | string | 100% | Top-level domain. 355 distinct values |
| `Language` | string | 0.6% | Detected site language |
| `Instagram` | string | 0.4% | Instagram handle |
| `Twitter` | string | 0.2% | Twitter handle |
| `YouTube` | string | 0.2% | YouTube channel |
| `TikTok` | string | 0.1% | TikTok handle |

The language and social columns are populated for fewer than 1% of rows.

## Comparison Group

`Commercial-CA-Comparison.csv` holds 10,938 large organizations that were found using a commercial certificate authority and were not found using Let's Encrypt. It is there so the adopter data can be measured against something rather than read on its own.

It was built with the same filters as the adopter data: 5,001 or more employees, company information required, collected August 2026. The two groups share no domains.

Columns are the 15 above plus `Certificate Authority`, naming the authority or authorities detected. 971 organizations were detected with more than one, written pipe separated.

| Certificate authority | Organizations | Share |
| --------------------- | ------------- | ----- |
| DigiCert | 4,787 | 43.8% |
| GlobalSign | 3,449 | 31.5% |
| Sectigo | 2,625 | 24.0% |
| GoDaddy SSL | 1,089 | 10.0% |

### What the comparison supports

Compare it against `all-adopters`, not against `default`. Both are complete populations under the same filters. `default` is truncated by website popularity, so comparing it to this file would measure that truncation as much as anything about certificates.

It supports asking how Let's Encrypt adopters differ from large organizations that buy commercial certificates, across industry, country, size and founding year.

It does not give an adoption rate. That would need a denominator of all large organizations, which no file here provides. Any percentage computed by dividing one file by another is meaningless.

Organizations can use more than one certificate authority. Those found with both Let's Encrypt and a commercial authority were removed from the comparison file, so the two groups stay separate at the cost of not representing mixed estates.

## Methodology

Websites were analyzed for technical fingerprints associated with Let's Encrypt. An organization 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 made in August 2026 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 made in August 2026.
* The dataset should not be interpreted as an official statement from any company regarding its technology stack.
* Every row of the adopter files is an adopter. `Commercial-CA-Comparison.csv` provides a matched group that does not use Let's Encrypt, which supports comparison between the two but still does not support an adoption rate.

## Citation

If you use this dataset, please credit StackScan and link to the source page.

Plain text:

StackScan. (2026). *Let's Encrypt Adoption Among Large Companies and Organizations* (data collected August 2026) [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 Large Companies and Organizations},
  year         = {2026},
  month        = {aug},
  publisher    = {StackScan},
  howpublished = {\url{https://www.stackscan.com/technology/lets-encrypt}},
  note         = {Data collected August 2026. Dataset: \url{https://huggingface.co/datasets/stackscan/lets-encrypt}}
}
```

Source page: [Let's Encrypt usage statistics](https://www.stackscan.com/technology/lets-encrypt).

## Access to More Data

The files in this repository are CC BY 4.0 and free for anyone to use, including commercially. No request or permission is needed.

StackScan also provides free access to larger and custom datasets for data journalists, academic researchers, non-profits and other organizations working on non-commercial projects. Ask through [stackscan.com](https://www.stackscan.com/technology/lets-encrypt).

## 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 above.