People Data Labs is good.
Here's when we're the better fit.
A new version of the dataset arrives 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, 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 fresher profiles. Either way, here's what you get:
A fresh update file every hour, for every customer
We send updates every 60 minutes, whatever your plan. Pull them in hourly, weekly, or monthly. The speed is the same for everyone, and it doesn't cost extra.
Records that tell you how fresh they are
Each people record carries two dates: when we last checked it and when we last fully refreshed it. You never have to guess how old a field is.
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 since 2013
- 1.20B+
- fields on every people record
- 250+
- companies tracked globally (40M+ active)
- 120M+
- job postings tracked, 24.5M+ open right now
- 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 like 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 of 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 needs to know who changed jobs this week.
A sales tool that emails someone at their old company looks broken to the person using it. You want to catch the move close to when it happened, without waiting for next month's release.
What changes when teams run PDL and MixRank on the same records
Most teams don't take our word for it, and they don't have to. The teams we talk to usually 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:
Fresher records.
This is what we hear most from teams that come to us after PDL: the profiles were checked more recently. Every one of our records shows when we last checked it, so you can confirm that in your own sample before signing anything.
A result that surprised them.
One prospect once 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 across the whole dataset and map every role 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 beat both of the others clearly. And we admire them for that.
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 pick it up. Every People record shows when we last checked it and when we last fully refreshed it.
In the next monthly release of the person dataset. Records include a date for when the person's job last changed and job postings refresh daily.
Job titles normalized across the dataset, with every role 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 that resolves old profile URLs to the current record.
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, 5 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 fight and it's on your own records
To be fair, you don't need a sales call to check any of this. You can run these three tests yourself, on records you already know, and let the results make the case. The first two below came straight from a real customer's evaluation, the same one PDL won against two other vendors, so it's a fair fight.
The count test
Pick 200 companies from your CRM 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 hand-check test
Pick a few thousand profiles your team has already looked up by hand. Run them through both datasets, and count which one matches what you found.
The freshness test
Ask each vendor for a truly random sample of the same size, and compare the last-updated dates. The pattern shows up fast.
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.