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This technographics dataset offers a complete over of the technology stacks used by businesses, sourced from job postings. With 40 million records, it reveals the tools and software companies rely on, helping businesses identify tech trends and target potential customers effectively.
5,199,866
companies
20,858
technologies
The technographics dataset has 3 files: technologies, companies and technograhics
| company_id | technology_id | company_name | confidence | first_date_found | last_date_found | jobs | jobs_last_7_days | jobs_last_30_days | jobs_last_180_days | first_date_found_source_job_description | last_date_found_source_job_description | technology_rank | technology_rank_180_days | rank_1_tie | rank_180_days_tie | relative_occurrence_within_category | jobs_source_final_url | first_date_found_source_final_url | last_date_found_source_final_url |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 53c6f3cca240d98b5e648d93115a2426 | 7 | DHL | low | 2024-03-12 | 2024-08-06 | 2 | 0 | 0 | 1 | 2024-03-12 | 2024-08-06 | 71 | 53 | 0.00015338599 | 0 | ||||
| f47c9278b0c8153c90eb7e73791083bf | 7 | Foreign & Commonwealth Office | low | 2024-04-24 | 2024-04-24 | 1 | 0 | 0 | 1 | 2024-04-24 | 2024-04-24 | 36 | 27 | 0.00022527596 | 0 | ||||
| 170b1d363bd8516fbf3a3eb05d4faff6 | 8 | Netflix | high | 2023-10-23 | 2024-08-30 | 18 | 0 | 1 | 10 | 2023-10-23 | 2024-08-30 | 1 | 1 | f | f | 0.6923077 | 0 | ||
| 530f21a73dc969866c85ce264a794ecd | 8 | Orbo.ai | medium | 2023-08-07 | 2023-09-15 | 2 | 0 | 0 | 0 | 2023-08-07 | 2023-09-15 | 1 | 1 | t | t | 0.5 | 0 | ||
| d7a9a3e2a98999afaa77e64983165058 | 8 | TikTok | medium | 1995-02-01 | 2024-09-17 | 19 | 1 | 2 | 8 | 1995-02-01 | 2024-09-17 | 2 | 2 | f | f | 0.39583334 | 0 | ||
| 110d0ce0f5db00524a5e4a908709ff99 | 8 | Envato | low | 2020-12-10 | 2021-12-24 | 2 | 0 | 0 | 0 | 2020-12-10 | 2021-12-24 | 1 | 1 | t | t | 0.4 | 0 | ||
| f1c768f1973bd404670d81a991ee6105 | 8 | Walmart | low | 2022-05-18 | 2024-05-07 | 5 | 0 | 0 | 1 | 2022-05-18 | 2024-05-07 | 3 | 3 | f | f | 0.12820514 | 0 | ||
| 03130557704ceb4addfa9b1718b232f5 | 8 | Wattpad | low | 2024-03-28 | 2024-03-28 | 1 | 0 | 0 | 1 | 2024-03-28 | 2024-03-28 | 2 | 1 | f | f | 0.2 | 0 | ||
| cdd16461ab27f5bce52a8d94f8632292 | 8 | Harvard University | low | 2024-08-30 | 2024-08-30 | 1 | 0 | 1 | 1 | 2024-08-30 | 2024-08-30 | 3 | 2 | f | t | 0.05263158 | 0 | ||
| de9402e6c300b9f0f44bc9166a4604fa | 12 | Squarespace | high | 2021-02-18 | 2024-08-28 | 27 | 0 | 2 | 8 | 2021-02-18 | 2024-08-28 | 1 | 1 | f | f | 0.96428573 | 0 | ||
| 3020e9df8fc8326d436b2680259c123b | 13 | Ajax Systems | low | 2024-07-26 | 2024-07-26 | 1 | 0 | 0 | 1 | 2024-07-26 | 2024-07-26 | 25 | 13 | 0.0011947431 | 0 | ||||
| 776828efa2737f017d05c533df1f8041 | 17 | Canva | high | 2019-05-02 | 2023-10-10 | 46 | 0 | 0 | 0 | 2019-05-02 | 2023-10-10 | 1 | 2 | f | f | 0.30872482 | 0 | ||
| 965b11a46418878a13732a04b3db07b3 | 17 | Nike | high | 2022-03-05 | 2024-08-07 | 35 | 0 | 0 | 1 | 2022-03-05 | 2024-08-07 | 1 | 1 | f | t | 0.35714287 | 0 | ||
| 65d6b2613559085ad3f5303cc65df6ad | 17 | IKEA | high | 2022-04-02 | 2024-09-17 | 164 | 1 | 4 | 39 | 2022-04-02 | 2024-09-17 | 1 | 1 | f | f | 0.4059406 | 0 | ||
| d7ed4ee1df437474d005188535f74875 | 17 | Zero | high | 2022-08-12 | 2024-01-02 | 10 | 0 | 0 | 0 | 2022-08-12 | 2024-01-02 | 1 | 1 | f | t | 0.5263158 | 0 | ||
| 64a171643c0344a180ec3242d0b614f9 | 17 | Aberdeen Appointments Agency | medium | 2022-09-26 | 2022-09-26 | 1 | 0 | 0 | 0 | 2022-09-26 | 2022-09-26 | 1 | 1 | f | f | 1 | 0 | ||
| a771a5a37055ebcd81f69ccb77ac9a9b | 17 | ADP | medium | 2022-01-23 | 2024-07-31 | 6 | 0 | 0 | 3 | 2022-01-23 | 2024-07-31 | 3 | 2 | f | f | 0.13043478 | 0 | ||
| 954e94d05347171a11f0341c68603456 | 17 | Advance Marketing | medium | 2023-08-23 | 2024-05-29 | 5 | 0 | 0 | 3 | 2023-08-23 | 2024-05-29 | 1 | 1 | t | t | 0.33333334 | 0 | ||
| 09e31a5bddc6d6628252a7bff57d5dce | 17 | Airbnb | medium | 2021-06-21 | 2022-12-02 | 14 | 0 | 0 | 0 | 2021-06-21 | 2022-12-02 | 2 | 2 | f | f | 0.17721519 | 0 |
| Column name | Data type | Description |
|---|---|---|
| company_id | str | ID of the company, meant to be used only as a join key between the company and the company_technologies datasets. Will change in the future |
| technology_id | int | ID of the technology |
| company_name | str | Company name |
| confidence | str | How confident we are that the company uses this technology |
| first_date_found | date | Date when the technology was first mentioned by the company in a job post, in the ATS URL or in the job description |
| last_date_found | date | Date when the technology was last mentioned by the company in a job post, in the ATS URL or in the job description |
| jobs | int | Number of jobs found mentioning this technology |
| jobs_last_7_days | int | Number of jobs from the given company mentioning this technology in the last 7 days |
| jobs_last_30_days | int | Number of jobs from the given company mentioning this technology in the last 30 days |
| jobs_last_180_days | int | Number of jobs from the given company mentioning this technology in the last 180 days |
| first_date_found_source_job_description | date | Date when the job description first mentioned the technology |
| last_date_found_source_job_description | date | Date when the job description last mentioned the technology |
| technology_rank | float | Rank of the technology within its category based on mentions in job postings |
| technology_rank_180_days | float | Rank of the technology within its category based on mentions in job postings over the last 180 days |
| rank_1_tie | bool | Indicates if this technology is tied for the most mentioned in its category |
| rank_180_days_tie | bool | Indicates if this technology is tied for the most mentioned in its category over the last 180 days |
| relative_occurrence_within_category | float | Measures the relative occurrence of this technology among other technologies in the same category, in jobs by this company |
| jobs_source_final_url | int | Number of jobs from the given company mentioning this technology in the ATS URL |
| first_date_found_source_final_url | date | Date when the job ATS URL first mentioned the technology |
| last_date_found_source_final_url | date | Date when the job ATS URL last mentioned the technology |
The technographics dataset is available in multiple formats and delivery options
| Methods | API download, Webhook, Amazon S3 |
| Frequency | Once, Daily, Weekly, Monthly, Quarterly, or Custom basis |
| Format | JSON, CSV, Parquet |
| Records in the dataset | 40M technographics, 21K technologies, 4M companies |
| Data fields | 30 fields |
| Records update last 30 days | 90% |
| Source | job postings |
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Frequently asked questions
Technographics is information about the technology and tools that businesses use, including hardware, software, and IT infrastructure. It provides data points such as stack list count, features, the number of companies using the tool, pros and cons, and more.
We collect the technographic data from job postings. We gather job listings from millions of companies monthly by tracking company websites, job boards, and other hiring platforms.
Technographic segmentation is the process of segmenting companies into different groups based on the technologies and tools they use. It helps us understand the needs and preferences of different segments and make data-driven decisions.
The technographic data is updated on a daily basis. We update the data by tracking the latest job postings and technologies.
You can get the technographic data by using TheirStack.com
You can get the technographic data for a specific company by using the company domain