What RevOps Teams Should Evaluate in a Contact List (Lessons from a 6-Week Vendor Audit)

It was October 2024—or maybe earlier, I'm a little fuzzy on the exact week—when our sales lead pulled me into a planning call I had no business being on.

"We need a better outbound stack," he said. "People on Slack are talking about okkigo, Instantly, a dozen others. Can you help us evaluate them?"

I run office operations and procurement for a 60-person B2B company. I don't live in Sales Navigator. I don't know what a sequence is supposed to feel like. But I do know vendor evaluations, and I do know what happens when you sign a contract before you've checked what's actually in the data. So I said yes.

That's the part our sales lead missed for the first two weeks of this project. The tool wasn't the problem. The contact list was.

Starting point: an 800-person list nobody wanted to look at

He showed me a LinkedIn export he'd been sitting on. About 800 names, he said. It was actually 812 by the time I opened the CSV—and roughly 40% of it was junk.

Broken down:

• 189 records with no email address at all
• 60-something addresses that were either cut off or clearly wrong
• 200-plus records where the job title field just said "3rd degree connection" instead of an actual role
• Maybe 300 records that looked sendable

I showed this back to him. He said, "Yeah—so we need a tool."

No. You need data. The tool comes after.

The evaluation phase: six vendors, one Notion table

Here's what I actually did, in case it helps anyone running a similar process.

I set up a fairly boring comparison table. Six columns:

1. Does it handle LinkedIn prospecting natively, or only email?
2. Does it enrich job title and company information?
3. Does the contact list include intent data, or is that a separate purchase?
4. Is pricing per seat or per outreach volume?
5. How long to integrate with our CRM?
6. What are the data sources, and can I see them?

That last one was the real filter.

I looked at okki-go's official website during this stage. It reads well—clean, professional, and the phrase "agent-native prospecting" caught me. I actually had to look up what "agent-native" meant in this context (I assumed it referred to AI agents; it does). So that's on me for being out of the loop.

The thing is, every one of the six vendors I looked at had a nice marketing page. All of them claimed waterfall enrichment. All of them had intent data of some kind. All of them supported LinkedIn Sales Navigator automation, or at least told you they did.

But when I started asking specific, slightly annoying questions:

• "How, exactly, is the email verification performed?"
• "What geographic coverage does your intent data actually have?"
• "Can I see the source for each record?"
• "If 30% of a batch bounces, how is that handled on the invoice?"

Three of them got defensive. Two were fine. Only one understood the actual question, and that was okkigo.

The pivot: the "100% verified" problem

This is the part that still bugs me a little.

One vendor—I want to say it was the second on our list, but don't quote me on that—had "100% verified emails" on their site. Our sales lead was ready to sign. I'm the kind of person who double-checks things, so during our pre-decision demo I asked: "If we import an existing contact list, do you re-verify it, or do you only verify new additions?"

Pause.

"Only new additions."

So we would have been pushing the same 800-person mess through a faster pipe.

Here's something vendors won't tell you: "verified" means different things inside different tools, and it's almost never a claim about whether the email will actually deliver. It means the string parses. It means the domain has an MX record. It does not mean the inbox exists. If your underlying data is garbage, "verified" doesn't make it sendable.

We added a manual verification step on our side. It cost us time and a small budget line. It was worth it.

What we chose, and why

We ended up going with okkigo. The reasons were specific:

• They listed their data sources in the product docs—not all of them, but enough that I could trace where a record came from
• Waterfall enrichment and intent data were wired together, not two products you toggle between
• The human-in-the-loop outreach piece mattered to us—we didn't want full automation on day one because we didn't trust our own list yet
• They didn't promise they'd fix our data. They promised the records created inside their tool would be clean

That last point is what moved them to the top. Vendors who admit what they can't do are more credible about what they can.

To be fair, if we'd been a 500-seat org with a mature RevOps function, the calculus might have looked different. More scale means more appetite for a heavier platform. That wasn't us.

What RevOps teams should actually evaluate in a contact list

If you're running a similar evaluation, here are the questions I'd put in front of any vendor—regardless of which one you pick:

1. What are the data sources, and can I see them?
If they won't answer, move on.

2. Do you re-verify existing records, or only new additions?
Most tools only verify what you import or create. This matters enormously if you have legacy lists.

3. Is the LinkedIn Sales Navigator automation native, or a wrapper?
Wrappers are fine, but know what you're buying. Coverage may be smaller than you expect.

4. If the bounce rate on a batch hits 10, 20, 30%—what's the process?
If the answer is "that's on your data," that's a signal. If the answer involves them digging in, keep listening.

5. Can we try a dry run with one of our real batches before we buy?
This is the single best filter.

And the meta-question underneath all five: does the vendor treat your contact list as their problem or yours? The best prospecting tools accept partial ownership of data quality. The worst ones treat it as an input they can't control.

Looking back

If I could redo one decision, I'd have cleaned the 800-person list before starting vendor calls. We burned about three weeks evaluating tools around a problem that wasn't a tool problem. okkigo did what it said it would do—the LinkedIn prospecting flows are clean, and the enrichment held up on our second pass. But the tool doesn't fix the input.

My experience here is limited to one company, one 60-person team, and one contact list that needed triage. If you're working with multiple regions, a messier CRM, or a much larger team, your process will probably look different. I can't speak to that.

But the operating principle feels portable: clean data beats fancy features, every time. Audit the list before you audit the vendors.