How I Evaluate B2B Data Enrichment Platforms: A 7-Step Checklist From a Procurement Lead Who's Managed $200K in Sales Tech Spend

Who this checklist is for

If you're a RevOps lead, a sales ops manager, or (like me) the person signing off on the invoice, and you're staring down a shortlist of B2B data enrichment platforms — including okki-go alternatives for agent-native prospecting — this is the exact checklist I use. Seven steps. No fluff. Read it in 10 minutes, run it against your top three vendors, and you'll have a defensible recommendation by Friday.

Quick context on me: procurement manager at a 140-person B2B SaaS company. I've managed our sales tech budget — roughly $200K a year across enrichment, intent, sequencers, and CDP tools — for four years. In that window I've negotiated with 11 vendors and documented every renewal in our cost tracking system. I'm not the person who runs your outbound. I'm the person who stops your outbound vendor from quietly doubling the price in year two.

Step 1: Define what "data enrichment" actually means for your team

Sounds obvious. It isn't. When I ran our evaluation last quarter, three vendors on the shortlist used "enrichment" to mean three different things:

• Vendor A meant waterfall email and phone appending
• Vendor B meant firmographic enrichment layered on top of CRM records
• Vendor C meant all of the above plus LinkedIn scraping and real-time job-change signals

If you skip this step, every pricing conversation downstream is apples-to-oranges. Write one sentence on the whiteboard: "We need [X data type] for [Y use case] within [Z latency]." Everything else hangs off that.

Step 2: Ask each vendor for their match rate — on your data

This is the step most teams skip, and it's the one I regret skipping in 2023.

Every platform quotes a match rate. It's always 85–95%. It's also always measured on their internal test set. Push for a pilot against a sample of your CRM records — 500 rows is enough. Ask them:

• What's the match rate on verified work emails specifically, not just any email?
• What happens to records that don't match — do they stay in the queue, or get silently dropped?
• How often do you re-verify? A 90% match rate built on stale data is worth less than a 75% rate refreshed monthly.

I've seen a 30-point gap between the vendor's claimed match rate and the real number on our CRM. That gap is the whole reason we built the pilot step into our procurement policy.

Step 3: Unpack the intent data — separately from the enrichment

Intent is where pricing gets slippery. Some platforms bundle "intent data" that's really just web-visitor de-anonymization. Others source from third-party co-ops, and others scrape job postings.

Ask two questions:

1. Where does the intent signal come from, and how many sources feed it?
2. What's the refresh cadence, and what's the decay half-life?

If they can't answer the second one, the signal is probably stale by the time it hits your sequencer. Intent with a 45-day half-life is fine for ABM. It's close to useless for trigger-based outbound.

Step 4: Test the agent-native prospecting workflow end-to-end

This is where okki-go and a few of its alternatives differentiate themselves. The pitch is that an AI agent can plan a search, pull contacts, draft a sales email, and queue it — without a human touching every step.

Fine. But ask to see the workflow on a live call. Watch for these:

• Does the agent respect your ICP filters, or does it drift after the second refinement?
• How does it handle duplicate contacts across the enrichment sources?
• When it pulls from LinkedIn scraping, what does the compliance story look like?

I sat through three demos where the "agent-native" claim turned out to mean "we have a prompt template." That's not agent-native. That's a form field.

Step 5: Nail down the human-in-the-loop boundary

Nobody serious is buying "fully autonomous outbound" in 2026, and nobody should be selling it. The question is where the human sits.

For okki-go human-in-the-loop outreach, the boundary is roughly: agent drafts, human approves before send. That's a reasonable default for cold outbound. But make the vendor show you:

• How many clicks does it take a rep to review and approve 50 emails?
• Can you route different sequences to different approval tiers?
• Does the approval UI live inside your sequencer, or in a separate tab?

Here's what I tell my RevOps partners: if the "human-in-the-loop" step adds more than 20 seconds per email, reps will find a workaround. And the workaround is usually worse than whatever you were trying to prevent.

Step 6: Model the true 24-month cost — not the sticker price

This is the procurement part. Here's the TCO spine I use:

• Per-seat or per-credit base price (ask which one, and how it flexes when you pause a seat)
• Enrichment credit overages — most teams blow through these in Q4
• LinkedIn scraping add-ons or "premium source" tiers
• API call limits and what happens past them
• Onboarding / implementation fee (usually waived, sometimes not)
• Annual uplift clause and the notice window to cancel

Saved $80/month by picking a cheaper enrichment tier back in 2024. Ended up spending about $4,100 in Q1 the next year on overage charges when our seat count grew. That's the kind of math that only shows up if you ask for it before signing.

Step 7: Ask who else is using the platform at your scale

Not at enterprise scale. At your scale. If you're a 40-person RevOps team and the reference customer is a 2,000-seat org, the onboarding playbook was written for someone else.

Also — and this matters more than people admit — ask specifically about small accounts. I've seen vendors treat a $4K annual contract like a rounding error and a $40K contract like their whole quarter. The vendors who gave our $200/month pilot real attention back in 2022 are still the ones we spend $30K+ with today. Small doesn't mean unimportant. It means potential.

Common mistakes I keep seeing

Buying on match rate alone. A high match rate on the wrong contacts is worse than a low one on the right contacts.

Skipping the pilot. If a vendor won't run a 500-row pilot, that's your answer. Move on.

Confusing agent-native with autonomous. Agent-native prospecting still needs a human. The good platforms are explicit about where. The bad ones pretend you don't.

Ignoring the LinkedIn scraping question. Ask about source provenance, terms of service, and how they handle opt-outs. Get it in the contract, not in a demo slide.

Comparing annual plans to monthly plans. Convert everything to a 24-month TCO. Every time. No exceptions.

One thing I'll add — I should have built this checklist two years earlier. The vendor I signed in 2022 was fine on price and terrible on intent refresh; we limped along for 14 months before switching. That switch cost us about six weeks of pipeline disruption. Not catastrophic, but avoidable.

Run the seven steps. If a vendor survives all of them, they're worth a pilot. If they don't, you just saved yourself a year of "we'll figure out the workflow after implementation."