> ## Documentation Index
> Fetch the complete documentation index at: https://docs.peopledatalabs.com/llms.txt
> Use this file to discover all available pages before exploring further.
# July 2026 Release Notes
| Release Name | Dataset Version | Publish Date |
| :----------- | :-------------- | :----------- |
| July 2026 | v35.0 | 07/21/2026 |
**Welcome to our July 2026 release notes!**
We’ve got a jam-packed release filled with lots of exciting updates this month, including the public launch of our first “secret sauce” fields, a brand new set of Technology Fields, major improvements to our Job Posting Dataset, and a full visual refresh of our docs.
Check it out:
* **🍟 [PDLScores™ GA Launch](#pdlscores-ga-launch)**: Our secret sauce fields are now publicly available, go ahead - have a taste.
* 🔮 **[Technology Data Fields](#technology-data-fields)**: Signals into which tech stacks, platforms, service, tools and technologies a company may be using.
* 📈 **[Job Posting Improvements](#job-posting-data-improvements)**: Expanded coverage, improved data quality, and new [industry fields](#job-posting-industry-fields)**!**
* 🔧 [**Data Quality & Coverage Improvements**](#job-posting-data-improvements): Smarter primary job selection, more GitHub data, and a variety of education data improvements.
* **📊 [Freshness Updates](#freshness)**: This past month, we refreshed [37M+ resume experiences](#freshness), [40M+ locations](#freshness), and [detected 3M+ job changes](#job-changes) across our global dataset
***
## 📣 Announcements
**New Look, Same Docs**
Today we launched a full visual refresh of the docs, with clearer styling and improved functionality.
Content, navigation, and organization is the same, so all the information you need is still where you expect it to be.
We’ll be rolling out some continued updates throughout the rest of the year - stay tuned! 🎉
**Have feedback?**
Use the 👍 / 👎 buttons on any page, and you’ll be able to leave some additional comments as well.
***
## ✨ Release Updates
### PDLScores™ GA Launch
Person Data GA ✨ Product Update
**What’s New**
This month, our [PDLScores™ for Person Data](/docs/pdlscores-for-person-data) are officially GA and have left Early Access. These scores add a layer of intelligence to our Person data, helping you evaluate, rank, and prioritize profiles across your workflows.
This launch includes **two scores** (now included in our Person Base Bundles):
* [`profile_score`](/docs/fields#profile_score): Indicates whether a profile appears to represent a real person
* [`activity_score`](/docs/fields#activity_score): Indicates whether a profile appears to be actively maintained
This launch also includes a bundle of **score factors** associated with each score (available as a new premium add-on bundle):
* [`profile_score_factors`](/docs/fields#profile_score_factors)
* `attribute_fill_rate`
* `profile_age_months`
* `has_valid_url`
* `meets_connection_threshold`
* [`activity_score_factors`](/docs/fields#activity_score_factors)
* `connection_change`
* `profile_change`
* `months_since_last_end_resume`
**Why This Matters**
Profiles vary in richness and relevance depending on your use case, but every profile can be valuable in the right context.
PDLScores™ are designed to help you find the profiles that matter to you. By understanding **which profiles are more likely to be fraudulent or not** and **which ones are more actively maintained**, our scores provide an out-of-the-box way to quickly surface the profiles you care about.
If you need additional control beyond the out-of-the-box scores, the **score factors** allow you to leverage some of our underlying data to build and design your own customized scores.
**Common Use Cases**
Some common use cases we’ve seen are:
* Filtering and prioritizing records
* Improving downstream product quality
* Reducing operational and compute costs
* Detecting fraudulent or low-quality profiles
* Improving outreach and recruiting efficiency
* Optimizing search, matching, and entity resolution workflows
**Availability**
With this release, the `profile_score` and `activity_score` are now included in the [Person Base](/docs/person-data-field-bundles#base) and [Person M\&A](/docs/person-data-field-bundles#m%26a-bundles) bundles. Customers receiving those bundles will automatically receive the new scores in their Person records.
The score factors are also now available through a new [PDL Score Factors](/docs/person-data-field-bundles#pdl-score-factors) bundle offered as a premium add-on for our Person Data. If you would like access to the new score factors, please reach out to your customer account team.
**What’s Next**
This launch is our first time releasing data fields fully leveraging our own internal metadata and a little secret sauce 🤫. We plan to expand PDLScores™ to additional PDL datasets in future releases, so keep an eye out and [let us know your suggestions](https://feedback.peopledatalabs.com/)!
For field definitions, examples, and additional documentation, see [PDLScores™ for Person Data](/docs/pdlscores-for-person-data) and the [PDLScores™ section of the Person Schema](/docs/fields#pdlscores).
***
### Technology Data Fields
Company Data Beta 📐 Schema Change
**What’s New?**
This month, we’re adding a set of **highly requested Technology Data fields** to the [Company Data Schema](/docs/company-schema). These new fields make it easier to identify which platforms, services, tools, and technologies a company may be using.
**Technology Data Fields**
| FIELD NAME | FIELD TYPE | FIELD BUNDLE | FIELD DESCRIPTION |
| :------------------------------------------------------------------- | :--------------- | :-------------- | :----------------------------------------------------------------------------------------------------------------------------- |
| [`technologies_used`](/docs/company-schema#technologies_used) | `Array (Object)` | Technology Data | Fields representing the technologies likely in use by a company, along with information on the underlying signals of that use. |
| [`product_id`](/docs/company-schema#technologies_used) | `String` | Technology Data | A unique, hashed value that represents a specific technology |
| [`name`](/docs/company-schema#technologies_used) | `String` | Technology Data | The canonical name for the represented technology |
| [`num_job_posting_mentions`](/docs/company-schema#technologies_used) | `Integer` | Technology Data | The total number of mentions of the technology in company job postings. |
| [`num_resume_mentions`](/docs/company-schema#technologies_used) | `Integer` | Technology Data | The total number of mentions of the technology in resumes. |
**Example**
```json theme={null}
{
"technologies_used": [
{
"product_id": "aV8mYR0sZFCrWvdkco07nwi7tGTt",
"name": "Databricks",
"num_job_posting_mentions": 11,
"num_resume_mentions": 4
},
{
"product_id": "ZNJNyjIICYIBrhIOyxG5iQfQvzLt",
"name": "Apache Spark",
"num_job_posting_mentions": 6,
"num_resume_mentions": 5
}
]
}
```
**Why It Matters**\
Technology data can be a powerful intent signal, but traditional technographics are often outdated, difficult to validate, and disconnected from the broader workforce context.
These new fields make it easier to **filter, compare, and analyze companies at scale**:
* **Technologies used** helps you understand a company’s tech stack for lead qualification, recruiting, investment sourcing, or product adoption analysis.
* **Technology mention counts** provide additional context from our proprietary job posting and resume data.
By summarizing real-world technology mentions across resumes and job postings, these new fields provide a more current, connected view of the tools and platforms companies are likely using directly within our company dataset.
**Availability**
These fields will initially be available through the [Technology Data](/docs/company-data-field-bundles#technology-data) beta bundle for select Company Data customers. To ask about joining the beta, please reach out to your account team.
For more details, see the [`technologies_used`](/docs/company-schema#technologies_used) field reference, the [Company Data Field Bundles](/docs/company-data-field-bundles#technology-data) page, and the [Example Company Record](/docs/example-company-record).
***
### Job Posting Data Improvements
Job Posting Data Beta ✨ Product Update
**What’s New**
We’re excited to announce a major set of quality and coverage improvements to our Job Posting dataset, now live as part of the July 2026 v35.0 release.
**What’s Improved**
With this release, we’ve made several important improvements across the Job Posting dataset, including:
* **Expanded Coverage**\
We now track over **400,000** unique company career pages (up from 86,000), resulting in over **100,000** unique companies with active job posts (up from 60,000).
* **Higher Description Fill Rates**\
We dramatically reduced the number of job posts with `null` description fields - we now have >99% fill rate for active job posts.
* **Reduced Duplicate Postings**\
We made significant upgrades across our sourcing process to reduce the number of duplicate and low-quality records.
* **More Accurate Deactivation Dates**\
We improved the accuracy of our `deactivated_date` field to reduce the number of stale and outdated job posts in our dataset.
* **Added Company Industry Fields**\
We added new [company industry](#job-posting-industry-fields) (see [release update](#job-posting-industry-fields) below) fields to our job posting records, making it easier to search and filter job posts by company industry.
Coverage has been one of the most requested improvements to our Job Posting dataset, and we also know that data quality is critical for customers using job postings to power analytics, workflows, and business decisions.
Together, these improvements provide broader hiring visibility while also making the dataset more accurate, usable, and trustworthy.
**Where These Improvements Apply**
These improvements touch all our Job Posting products, including:
* [Daily](/docs/daily-deliveries-job-posting-data) and [Monthly](/docs/receiving-and-updating-data) Job Posting Data Licenses
* [Job Posting Search API](/docs/job-posting-search-api)
* [Job Posting Insights](/docs/company-data-field-bundles#job-posting-details), available through the Company Data Field Bundles
As a result, customers consuming Job Posting data in any form will be able to leverage the benefits from these improvements.
**Getting Started**\
If you’re an existing customer, reach out to your account team to run a data test.
If you’re new to PDL, you can [reach out to us here](https://www.peopledatalabs.com/job-posting-beta-sign-up).
Whether you’ve evaluated our Job Posting Data in the past, or are brand new to it, we highly encourage you to try out the improved dataset and see the results for yourself!
For a full field reference and current coverage numbers, see the [Job Posting Data Overview](/docs/job-posting-data-overview), [Job Posting Schema](/docs/job-posting-fields), and [Job Posting Stats](/docs/jp-stats).
***
### Job Posting Industry Fields
Job Posting Data Beta 📐 Schema Change
**What’s New?**
This month, we’re adding two new **company industry fields** to the [Job Posting Schema](/docs/job-posting-fields). These fields reflect the industry classification of the company, and are intended to simplify the process of filtering and searching for job posts based on company industry.
**Job Posting Industry Fields**
| FIELD NAME | FIELD TYPE | FIELD DESCRIPTION |
| :-------------------------------------------------------------------- | :--------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| [`company_industry`](/docs/job-posting-fields#company_industry) | `String` | The company's self-reported industry. It will be one of our [Canonical Industries](/docs/industries). This is enriched from the PDL Company dataset. |
| [`company_industry_v2`](/docs/job-posting-fields#company_industry_v2) | `String` | The company's self-reported V2 Industry. It will be one of our [Canonical V2 Industries](/docs/industries-v2). This is enriched from the PDL Company dataset. |
**Example**
```json theme={null}
{
"id": "ARasmflDTd4",
"company_industry": "computer software",
"company_industry_v2": "software development"
}
```
**Availability**
These fields are now included for all customers using Job Posting Data.
For Job Posting Search API customers, these industry fields are now available as parameterized field filters.
For more details, see the [Job Posting Schema](/docs/job-posting-fields), [Job Posting Data Overview](/docs/job-posting-data-overview), [Job Posting Search API field filters](/docs/reference-job-posting-search-api#field-filters), and [`company_industry`](/docs/input-parameters-job-posting-search-api#company_industry) / [`company_industry_v2`](/docs/input-parameters-job-posting-search-api#company_industry_v2) input parameter docs.
**We’d Love Your Feedback!**
Your input will help shape how we continue to expand and improve our Job Posting Data. Share your thoughts on these fields or suggest new ones via our [Roadmap Feature Request Board](https://feedback.peopledatalabs.com/)!
***
## 🚀 Data Updates
### Freshness
*The number of resume experiences and locations verified in our datasets (based on the [`job_last_verified`](/docs/fields#job_last_verified) and [`location_last_updated`](/docs/fields#location_last_updated) fields).*
**Monthly (v34.2 → v35.0)**\
*Freshness updates over the past month.*
| Dataset | Geography | Field | Records Updated |
| :------ | :------------ | :----------- | :-------------- |
| Resume | Global | `experience` | 37,163,425 |
| Resume | Global | `location` | 40,142,961 |
| Resume | United States | `experience` | 18,296,337 |
| Resume | United States | `location` | 19,611,032 |
### Job Changes
*The number of person records where the primary job experience changed in our Person Dataset (based on the [`job_last_changed`](/docs/fields#job_last_changed) field).*
**Monthly (v34.2 → v35.0)**\
*Job changes detected over the past month.*
| Dataset | Geography | Records Updated |
| :------ | :------------ | :-------------- |
| Resume | Global | 3,359,016 |
| Resume | United States | 1,120,846 |
***
## 🌐 Coverage
### Monthly Highlights (v34.2 → v35.0)
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :---------------- | ----------------- | ----------------- | ------------ |
| Total Records | 813,720,475 | 814,778,903 | 0.13% |
| `github_url` | 1,250,886 | 1,994,722 | 59.46% |
| `github_username` | 1,250,886 | 1,994,722 | 59.46% |
| `work_email` | 89,995,711 | 84,215,498 | -6.42% |
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :------------ | ----------------- | ----------------- | ------------ |
| Total Records | 2,464,638,503 | 2,465,129,875 | 0.02% |
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :------------ | ----------------- | ----------------- | ------------ |
| Total Records | 612,542,989 | 612,327,530 | -0.04% |
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :------------ | ----------------- | ----------------- | ------------ |
| Total Records | 478,374,559 | 478,902,930 | 0.11% |
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :------------------------- | ----------------- | ----------------- | ------------ |
| Total Records | 74,742,428 | 74,753,971 | 0.015% |
| `technologies_used` | – | 6,349,659 | – |
| `active_job_postings` | 65,535 | 108,549 | 65.64% |
| `deactivated_job_postings` | 65,535 | 108,549 | 65.64% |
| Linkage | Coverage in v34.2 | Coverage in v35.0 | Increase (%) |
| :--------------------- | ----------------- | ----------------- | ------------ |
| Total Records | 37,157,600 | 37,001,534 | -0.42% |
| Total Unique Companies | 65,553 | 108,626 | 65.71% |
| Total Active Postings | 4,508,761 | 6,188,347 | 37.25% |
### Commentary
* **Person Data**
* This month we saw a 59% increase in github-related fields in our resume slice.
* This month we saw a 6% decrease in our fill rate for `work_email` in our resume slice as result of our continued work to [improve the deliverability of our email fields](http:///changelog/october-2025-release-notes-v320#email-deliverability-improvements-person)
* **Company Data**
* We now have coverage of technology data for over 6.3M companies with the launch of our new [Technology Data fields](#technology-data-fields) this month
* We saw a 65% increase in our coverage of job posting related fields for our company data this month as a result of our broader [Job Posting improvements](#job-posting-data-improvements) described above..
* **Job Posting Data**
* This month we saw a 65% increase in the number of unique companies as a result of our broader [Job Posting improvements](#job-posting-data-improvements) described above.
***
## 🛠 Improvements and Bug Fixes
### Improvements
* **Improved Primary Experience Selection**
* We improved our selection logic for a profile’s primary (current) work experience by prioritizing full time employed roles over board member and advisory roles.
* **Industry Fields added to Job Posting Search API**
* The [`company_industry`](http:///docs/input-parameters-job-posting-search-api#company_industry) and [`company_industry_v2`](http:///docs/input-parameters-job-posting-search-api#company_industry_v2) fields have been added as [parameterized field filters](http:///docs/reference-job-posting-search-api#field-filters) to the Job Posting Search API. This update allows you to query the Job Posting API based on industry with cleaned and standardized inputs.
* **Better Name Cleaning**
* We updated our name-cleaning rules to allow valid profile names containing common English words (such as “cable”, “power”, “book”, etc).
* **Improved Education Date Validation**
* We removed education start and end dates where the recorded time span was greater than 15 years.
* **Refined CXO Title Tagging**
* We updated our executive-level tagging to prevent job titles containing phrases like “Office of the CEO” from being classified as cxo-level positions.
* **Updated School ID Format**
* We standardized school IDs to end in `_0000` instead of `_0` for greater consistency across the person dataset. Characters preceding the suffix remain unchanged.
* Example:
* Previous: `5Ic6qaBcxe2DlWHRIVFnZg_0`
* New : `5Ic6qaBcxe2DlWHRIVFnZg_0000`
### Bug Fixes
* **Duplicate Experience Summaries**
* We cleaned up millions of duplicated summaries caused by experience start and end dates being incorrectly parsed.
* **Incorrect Experience Merging**
* We fixed an issue where separate experience records with similar job titles could be incorrectly merged into a single record
* **Lingering End Dates for Current Roles**
* We fixed a bug where the end date for a current role was not being correctly updated if it was added then removed at a later time
* **Duplicate Education Records**
* We fixed an issue where matching education objects were not being properly merged resulting in duplicate education records
* **Phantom School Names**
* We corrected an issue where some profiles were being associated with incorrect schools. This was due to some education records referencing old LinkedIn URLs that were previously associated with different schools.
* **Inaccurate Locations**
* We corrected the location data for profiles that were not being assigned to San José, Costa Rica (and were instead being assigned to locations like “United States Air Force Academy, Colorado” or “San Jose, California”)