Buying Intents Dataset
Every in-market company, in one daily file
- The complete buying intent dataset, refreshed daily
- 9,000+ topics across 14 categories, scored by confidence
- Delivered straight to your S3 bucket — ready for CRM enrichment, lead scoring, or warehouse-scale analytics
- Buying intent signals
- 351M
- Topics tracked
- 9.4k
- companies
- 12M
Trusted by industry leadersTrusted by the world's most innovative sales and marketing teams


























































Dataset
This dataset contains the following files
| company_id | keyword_id | keyword_slug | company_name | subcategory_slug | is_recruiting_agency | confidence | jobs | jobs_last_180_days | jobs_last_30_days | jobs_last_7_days | jobs_source_description | jobs_source_description_last_180_days | jobs_source_description_last_30_days | jobs_source_description_last_7_days | jobs_source_title | jobs_source_title_last_180_days | jobs_source_title_last_30_days | jobs_source_title_last_7_days | jobs_source_url | jobs_source_url_last_180_days | jobs_source_url_last_30_days | jobs_source_url_last_7_days | first_date_found | last_date_found | first_date_found_source_job_description | last_date_found_source_job_description | first_date_found_source_job_title | last_date_found_source_job_title |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| a2fe9051fe051f819bd739ef3e340377 | 145860 | 2-5d-packaging | NVIDIA | tools-electronics | false | medium | 2 | 2 | 1 | 0 | 2 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Tue Mar 03 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Apr 07 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Mar 03 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Apr 07 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 9f6290f4436e5a2351f12e03b6433c3c | 145860 | 2-5d-packaging | Apple | tools-electronics | false | medium | 19 | 2 | 1 | 1 | 19 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Fri Dec 16 2022 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Apr 30 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Dec 16 2022 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Apr 30 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 5ed0b5f41b21804e51e82664dc24e2dd | 144542 | 2-in-1-pcs | ASUS | personal-computer | false | low | 3 | 1 | 0 | 0 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Mar 16 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Mar 16 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| a95b436b6afe17af8b20f4f15f3f15ab | 152140 | 2d-animation | Khan Academy | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Jun 16 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 9414b97199d909061ce91aeb8faa421f | 152140 | 2d-animation | Tencent | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Thu May 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu May 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu May 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu May 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| f1e069787ece74531d112559945c6871 | 152140 | 2d-animation | GeeksforGeeks | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Wed Jul 24 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Jul 24 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Jul 24 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Jul 24 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| cdd16461ab27f5bce52a8d94f8632292 | 152140 | 2d-animation | Harvard University | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Tue Jun 27 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jun 27 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jun 27 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jun 27 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 5daded1785f90c4e2ca275cdf740b08b | 152140 | 2d-animation | The Washington Post | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Tue Apr 11 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Apr 11 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Apr 11 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Apr 11 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 98837de47acec3d57078529d1fe9417b | 147065 | 3-d-secure | Ticketmaster GmbH | transactions-payments | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Tue Jul 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jul 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jul 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Jul 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 844a3d6e07ae35f4625f7fbe70a96f71 | 147065 | 3-d-secure | ASOS.com | transactions-payments | false | low | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Wed Jul 23 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Sep 05 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Jul 23 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Sep 05 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 09e31a5bddc6d6628252a7bff57d5dce | 147065 | 3-d-secure | Airbnb | transactions-payments | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Wed Aug 04 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Aug 04 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Aug 04 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Aug 04 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 0f39a33ab76697cf557b327b01954672 | 147065 | 3-d-secure | BUZ | transactions-payments | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Fri Jul 28 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Jul 28 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Jul 28 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Jul 28 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 3c009c3bbadb06bfe9e124c4a345f1e7 | 147065 | 3-d-secure | Shutterstock | transactions-payments | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Wed Mar 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Mar 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Mar 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Wed Mar 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| dbc0599a2beb0b465695a5f4afe06cd5 | 153349 | 301-redirect | The New York Times | web | false | low | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Thu Nov 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Nov 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Nov 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Nov 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 110d0ce0f5db00524a5e4a908709ff99 | 153349 | 301-redirect | Envato | web | false | low | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Thu Dec 10 2020 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Jul 30 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | Thu Dec 10 2020 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Jul 30 2021 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| e39fa16df947a4ca653e2120c3cdda63 | 152141 | 3d-animation | WebMD | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Mon Oct 30 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Oct 30 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Oct 30 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Oct 30 2023 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| de4bd8ef4675ebb85a055955de76d0ee | 152141 | 3d-animation | HubSpot | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Mon Apr 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Apr 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Apr 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Mon Apr 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 03130557704ceb4addfa9b1718b232f5 | 152141 | 3d-animation | Wattpad | technology-other | false | low | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Fri Feb 20 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Feb 20 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Feb 20 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | Fri Feb 20 2026 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 12812ea78dbc80e6065f794c752272e9 | 152141 | 3d-animation | Udemy | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Tue Oct 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Oct 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Oct 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | Tue Oct 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) | ||
| 92a53bd7e3629533178c49353e04e92b | 152141 | 3d-animation | Netflix Animation | technology-other | false | low | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Sun Mar 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) | Sun Mar 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) | Sun Mar 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) | Sun Mar 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) |
Dataset Delivery
Ready-to-use files, delivered automatically
Fresh buying intent data in structured formats, delivered to your cloud storage on a daily schedule. No ETL pipelines to maintain.
Flexible Update Frequency
Choose how often your data refreshes — from hourly live feeds to quarterly snapshots, matching your pipeline's cadence.
Learn moreParquet & CSV Formats
Export your data in the format that fits your stack — columnar Parquet for analytics warehouses or CSV for universal compatibility.
Learn moreS3 Bucket Delivery
Get data delivered directly to your Amazon S3 bucket — no manual downloads, no polling. Set it and forget it.
Learn more60+ Data Fields with Coverage
Each job record includes 60+ fields spanning job details, location, salary, company firmographics, and technologies — with transparent fill-rate metrics.
See full dictionaryHow it works
Access your datasets in three steps
Get temporary credentials, explore available files, and download the data you need — using Python, AWS CLI, or ClickHouse.
Get credentials
Request temporary S3 credentials from our API. One POST request returns access keys, session token, bucket name, and allowed prefixes — valid for immediate use.
List available files
Browse the datasets bucket to discover available files. Use Python (boto3), the AWS CLI, or ClickHouse's s3 table function to list objects by prefix and date.
Download your data
Download individual files or sync the entire bucket to your local environment. Parquet and CSV formats are ready for direct analysis or ingestion into your data pipeline.
Data Quality
Built for accuracy and depth
Every buying intent signal is traceable, scored for confidence, and enriched with company metadata across 14 keyword categories.
9,000+ Topic Catalog
From compliance and regulations to strategic initiatives, equipment purchases, and operational activities — we track 9,000+ buying intent topics across 14 keyword categories.
Explore topicsBuying Intent Signals
Detect buying intent changes as they happen. Our platform processes new signals every minute from millions of job postings worldwide.
Learn about signalsCompany Database
Access buying intent profiles for companies worldwide. Each profile includes all detected topics with confidence scores and historical data.
Explore companiesTraceable to Source
Every buying intent signal links back to the original job postings. Verify any detection with direct access to the evidence — company, date, and job description.
How we source dataConfidence Scoring
Our three-tier confidence model (low, medium, high) estimates how strong a buying intent signal is, based on mention volume across job postings in the last 90 days.
How scoring worksFrequently asked questions