What Should RevOps Teams Evaluate in a B2B Data Enrichment Platform? A 7-Point Checklist

When This Checklist Applies

If your team is shortlisting B2B data enrichment platforms — or you're looking at okki-go alternatives for agent-native prospecting — this checklist is for you. It's not a review. It's the sequence I run through before we sign anything, and it's the same sequence I wish I'd run three years ago before we locked into a two-year contract that looked fine on the demo.

Seven steps. No filler. Each one is something you can test inside a 30-minute trial, not a 3-week POC. If a vendor won't let you do that, that's already step seven.

Context: I run brand and quality compliance for outbound at a mid-market B2B company. I review campaigns before they hit inboxes. In 2024 I rejected roughly 18% of first drafts — mostly bad enrichment, sometimes bad copy, occasionally both.

Step 1: Map Source Coverage by Category, Not by Logo Count

Vendors love to say "80+ sources." That number is useless. What matters is whether the sources overlap with your ICP's actual footprint. A platform with 40 sources that includes regional business registries, niche industry directories, and product-specific job boards will outperform a 200-source platform that's 60% consumer data stretched thin.

Ask for a coverage map by source category, not a source count. If they can't produce it, you're buying a black box.

Checkpoint: Pull 50 of your own CRM records — ones you're confident about — and see how many the platform returns with correct title, company, and email. Under 60%? Walk.

Step 2: Test Data Freshness with a Time-Stamped Seed List

Data freshness is the difference between a 22% reply rate and a 4% reply rate. Not exaggerating (well, slightly — reply rates vary wildly by segment).

Here's the test I actually run: take 30 contacts who changed jobs in the last 90 days — you know this because you have a relationship with them. Feed them in. See how many the platform has updated.

Most single-source platforms will fail this. Aggregator-style platforms with waterfall enrichment tend to do better, but the spread across vendors is wide.

Checkpoint: Ask the vendor for their median time-to-update for title changes. If they can't give you a number, they don't track it, which tells you something.

Step 3: Confirm Whether It's Waterfall Enrichment or Single-Source

This is the one most RevOps teams gloss over. A single-source enrichment platform pulls from one database. A waterfall pulls from multiple sources in priority order until it finds a match.

In 2023 I compared two campaigns side by side — same ICP, same copy, same send window. One used a single-source provider, one used a waterfall setup. The waterfall campaign matched 74% of records against 51% for the single source. Reply rate was 1.9x. Same audience. Same everything else.

That's not a universal law. It's just what we saw, in our segment, in our territory.

Checkpoint: Ask specifically: "What happens when source #1 doesn't return a match?" If the answer is "it returns a null," that's not a waterfall.

Step 4: Check Intent Data Recency — Not Just Presence

Intent data is where a lot of vendors get vague. "We have intent data" can mean almost anything from "our data partner buys it quarterly" to "we scrape job postings in real time."

Two things to verify:

1. Recency window. Ask for the median age of intent signals surfaced to customers. If it's over 30 days, you're chasing stale demand.
2. Signal source. Is it first-party (your site behavior), second-party (partner co-op), or third-party (aggregated from public sources)? Each has a different shelf life.

Buyers change intent fast. A company "researching CRM" in March is often past that phase by May. If your intent layer is 90 days stale, you're not prospecting — you're archiving.

Checkpoint: Ask for a sample of the last 14 days of intent signals for a company you already know is in-market. If they can't produce it live, they're not pulling real-time.

Step 5: Verify Human-in-the-Loop Controls Actually Exist

This is where 'okki go human in the loop outreach' gets thrown around as a marketing term, and where most teams should slow down. "Human in the loop" should mean something specific:

• Can a human review, edit, or block a sequence before send?
• Is the review per-campaign, per-contact, or per-step?
• What's the audit trail if something goes wrong?

If the answer to the first question is "yes, but only at the campaign level," you don't really have a review layer. You have a submit button.

Look: full automation is fine for some segments. For enterprise, for regulated industries, for anyone with a brand that took a decade to build — you need an actual human gate. Ask what the gate looks like before you sign, not after.

Checkpoint: During the trial, try to interrupt a live sequence mid-send. If the platform won't let you, or it takes more than 2 clicks, note that. (Note to self: this is the thing vendors always rush past in demos.)

Step 6: Pressure-Test LinkedIn Scraping Boundaries

LinkedIn scraping is a minefield and the rules are not static. Vendors handle this differently. What you want from an evaluation standpoint:

• Where does the data come from? Public profiles? Partner-supplied exports? Browser extensions on user accounts?
• What's the exposure model? If the data pipeline breaks LinkedIn's ToS, whose account gets flagged — yours or theirs?
• What's the refresh cadence? Scraped data ages badly. A profile scraped in 2022 with a 2024 title change is worse than no data.

I'm not going to tell you which approach is 'right' — jurisdictions differ, and I only know the rules well enough to be careful. (This was accurate as of Q1 2025. LinkedIn's enforcement posture has shifted before; it will shift again.)

Checkpoint: Ask the vendor directly: "If a client's LinkedIn account gets limited because of how we pull your data, what's your process?" The quality of the answer tells you a lot about their compliance maturity.

Step 7: Calculate Cost per Verified Contact — Not Cost per Record

The sticker price will mislead you. So will the seat cost. What matters is cost per verified, enriched, ready-to-send contact.

"Total cost of ownership in data enrichment includes: base subscription, credit burn rate, failed enrichment attempts, enrichment calls that return partial matches, verification pass-through costs, and the human hours spent cleaning the output. The lowest quoted seat price is almost never the lowest total cost."

For reference, public pricing from major B2B data platforms in early 2025 ranged roughly from $99/user/month for entry tiers up to $2,500+/user/month for enterprise seats with intent and enrichment bundled. That's a 25x spread. But the seat price is the least interesting number. The burn rate per enrichment call is where your CFO will find the surprises.

Checkpoint: Build a simple spreadsheet: for 1,000 target contacts, what's your projected cost to reach 600 verified, enriched, ready-to-send records? That's the number to compare across vendors. So glad I started doing this before Q3 2024 — it flipped our shortlist entirely (we were about to sign with the cheapest option on paper).

Notes, Common Mistakes, and One Thing I'd Skip

A few things I've learned the hard way:

Don't skip the data-quality audit. It takes 4 hours. Every platform promises "98% accuracy." Set your own bar with your own data. It's the cheapest insurance you'll buy this quarter.

Don't evaluate on features alone. Features change quarterly. Match rates on your specific ICP don't lie. Push every vendor through the same 30-record test and score the results blind.

Don't assume a waterfall setup automatically wins. It usually does for coverage. But if your ICP is very narrow (say, plant managers at mid-size cold-chain logistics companies), a single specialized source can beat a wide waterfall. Context matters — and I only know this because we tested both.

Don't sign annual on the strength of a demo. Monthly trial, real data, your seed list. Thirty days beats thirty slides every time.

And one thing I'd skip entirely: comparison spreadsheets with 40 rows. Nobody reads them. Pick the 7 checkpoints above, score each vendor 1-5, and let the sum decide. It took me about 4 years and a dozen vendor contracts to figure out that the shortest checklist wins.

Between you and me, most of the 'evaluation frameworks' floating around out there are built to make the person who wrote them look thorough. What you actually need is a defensible shortlist and a test plan. Everything else is noise.