Released on 4/1/2021
Data Field Changes
Person Schema
Freshness
This quarter, we made great strides in updating our datasets and have updated job titles for over 315mm of our global profiles and locations for over 344mm. We also updated jobs for 88mm of our United States profiles and locations for 95mm. Most of the profiles with updated jobs have had their full resume refreshed, not just their current job.Coverage
We are continuing to make strides to link more PII to our core datasets. See some highlights below and click the links on each slice to see the full set of stats for each.API Dataset
Resume Dataset
Email Dataset
Mobile Phone Dataset
Commentary
- We’ve dramatically increased our mobile phone coverage by 72%. All of these new mobile phones are tied to a facebook URL and primarily bolster our global phone coverage.
- We’ve also increased the linkage of mobile phone to resume data by 72%, from ~7.4mm to ~12.8mm
- We’ve expanded the number of resumes in our person dataset, increasing the total size of our resume slice by ~10%, and increasing the fullness of our resume profiles. One metric for understanding the fill rates of our resumes is the job_start_date field, whose coverage increased ~45%
Improvements
- We’ve added the ability to enrich profiles using MD-5 hashed emails in our Enrichment API. These can be inputted in the email_hash parameter.
- Our canonical company coverage of our person dataset has improved from 65% to 69%
- We added deduplication processes that increased the work email coverage and mobile phone coverage in our resume slice
- Our internal data build/release were revamped to help us output more in each future release
- We are launching an internal API usage analysis tool so our customer success team can help optimize API usage to reduce errors and help customers increase the likelihood scores they get back.
- We will be releasing a new customer facing API dashboard at peopledatalabs.com/main
Bug Fixes
- We removed a data source with some inferred emails.
- We added additional filtering to remove a small set of records with an abnormally large number of phones or addresses.
- We fixed issues with foreign job title encoding
