People Data Labs is good.
Here's when we're the better fit.
People Data Labs (PDL) releases a new version of its person dataset once a month, and anything that changes in between waits for it. PDL is open about that, and its release notes show exactly what moved each month. We work differently. We send an update file every hour, to every customer. Whatever we've picked up since the last file is in it, and you pull it in whenever it suits your pipeline.
Some teams come to us to replace PDL at renewal. Others keep it for contact data and use us for people profiles. Either way, here's what you get:
New and changed records every hour, on every plan
We send an update file every 60 minutes, whatever your plan. Pull it in hourly, weekly, or monthly. The speed is the same for everyone, and re-reading a record you already have costs nothing.
Records that tell you when we last checked them
Every people record shows the date we last checked it, so you can see how old a field is before you trust it.
A switch that doesn't mean paying twice
Moving off PDL at renewal? We can ship you our data before your contract with us starts, so your engineers can integrate while PDL is still running. We'll also help you map your existing PDL records to our IDs.
The numbers behind the renewal decision.
Some comparison tables list MixRank without job postings data, or with numbers we outgrew years ago. Wherever you saw the comparison, here are our current numbers:
- people profiles with history back to 2013
- 1.2B+
- people-profile updates every month
- ~150M
- companies going back to 2013
- 120M+
- job postings, with history back to 2021
- 1.8B+
If you're building on PDL, one of these probably sounds familiar.
Most teams comparing us with PDL are building something on top of the data, such as a recruiting platform sourcing candidates, a sales tool writing personalized outreach, or a workforce analytics product mapping where a company's people sit. If that's you, you'll probably recognize one of these weeks:
Your renewal is coming up, and switching feels expensive.
You're not unhappy enough to rip anything out mid-contract, but you've started to wonder what's out there. Your worry is the overlap: paying two vendors while your engineers rebuild the pipeline.
Your users search the way people talk.
They type “sales leader” or a city name and expect sensible results. When job titles and locations have to match an exact format, your team ends up writing cleanup logic that should have come with the data.
Your product can't wait a month for a job change.
A sales tool that emails someone at their old company looks broken to the person using it. When we pick up a move, it reaches your feed within the hour, not at next month's release.
What changes when teams run PDL and MixRank on the same records.
Nobody switches data vendors on a hunch. The teams we talk to pick a sample they already know well, run it through both datasets, and compare the results line by line. These are the differences they point out most:
A result that surprised them.
One prospect ran a thousand company domains through both of us during a trial. Their words when they saw the results: “The difference is quite remarkable.”
Titles you can search.
We normalize job titles and map roles to a seniority and a function. A search for engineering leaders finds the VP of Engineering, the Head of Platform, and the CTO, without your team writing the mapping first.
When we would point you to PDL ourselves
PDL has one of the best developer experiences in this category. One analytics team we spoke with ran a careful two-round test across three vendors, and PDL clearly beat the other two. We'd rather you hear that from us.
Here's what they do well
Built for developers.
Five official SDKs, search in SQL or Elasticsearch syntax, and a free tier you can start on today.
Clear about what changed.
Every monthly release comes with public notes on what they refreshed, added, and removed. If your team likes versioned data it can QA before loading, that's a real advantage.
Pick PDL if:
You want to start free and grow into it. Their free tier lets an engineer test the API before anyone talks about budget.
Phone numbers are a core field for you. Customers tell us their phone enrichment works well.
You'd rather load one clean version a month. Some teams prefer a monthly snapshot they can check before it touches production. PDL is built for that.
Know these before you sign with any B2B data vendor. Including us
Most teams comparing us with PDL are keeping a product's people database current week after week. So the first question is about timing: when someone changes jobs on the second day of the month, when does your product find out?
In the next hourly update file after we re-check that profile. Every people record shows when we last checked it.
In the next monthly release of the person dataset. Records include a date for when the person's job last changed. Job postings refresh daily.
Job titles normalized, with roles mapped to a seniority and a function.
Search in SQL or Elasticsearch syntax across person and company records.
Every person gets a stable ID, with a mapping table of every profile URL we've seen for them.
Raw records from many sources merged into one person profile.
API, bulk feeds with hourly update files, a hosted database, or delivery into Snowflake, BigQuery, or Redshift.
API, five official SDKs, and delivery through Snowflake, Databricks, and Delta Sharing.
A sample on your own records before you sign, plus help mapping your existing records to our IDs if you're switching.
A free tier you can start on today.
The second question is easy to skip until you're switching vendors or selling your company: what are you allowed to do with the data you've already paid for once the contract ends? Ask every vendor, including us, and get the answer in writing.
This is a fair test and it's on your own records.
A spec sheet only goes so far. These three tests run on records you already know, and our data team will set up the sample and walk through the results with you. The first two come from a real customer's three-vendor evaluation.
The hand-check test
Pick a few thousand profiles your team has already looked up by hand. Send them to both vendors, and count which dataset matches what you found.
The count test
Pick 200 companies your product already covers and a few job titles you care about. Ask each vendor how many people match, and check those counts against what you can see on professional profiles yourself. The team that designed this test counted any vendor within 20% as a pass.
The job-change test
Pick a few hundred people you know changed jobs in the last 90 days. Send them to both vendors, and count which dataset has the new title and company.
Put our records next to theirs. We'll explain every difference.
Send us the specific fields where the two datasets disagree, and we'll tell you why, including the cases where we're the one who's wrong.