What Should Revenue Operations Teams Evaluate in an Intent Data Platform? A 9-Step Checklist

Who this checklist is for

I'm a procurement manager at a 180-person B2B SaaS company. I've owned our go-to-market tooling budget — roughly $340,000 a year — for six years, negotiated with 40+ vendors, and logged every invoice in our cost tracking system. I'm not an SDR and I don't run pipeline. I'm the person who has to justify the renewal.

This checklist is for RevOps teams buying an intent data platform for the first time, or replacing one that isn't earning its line item. Nine steps, in the order I'd actually run them. Each one has a checkpoint — something you can verify with a document or a test, not a promise.

One thing up front: I have mixed feelings about intent data as a category. On one hand, it's the only thing that's meaningfully changed how our reps spend their mornings. On the other, half the platforms are reselling the same underlying signals with different dashboards. This checklist is how I tell them apart.

The 9-step evaluation checklist

1. Define what "intent" has to mean for your motion

Before you take a single demo, write one sentence: "We will act on a signal when ___." The options are usually contact-level intent (a named person showed buying behavior) for outbound, account-level intent for ABM prioritization, or both. Those are different products with different price points, and a vendor will happily sell you the expensive one.

Checkpoint: you can name the three signals that would make a rep pick up the phone this week. If you can't, you're not ready to evaluate — you're ready to define.

2. Get the signal source list in writing

Most intent data providers are aggregators. The underlying sources are a mix of content co-ops, review sites, job-posting crawls, technographic crawls, web-visit de-anonymization, and LinkedIn engagement signals. Two platforms quoting the same price can have wildly different coverage because one is licensing a co-op with thousands of sites and the other has forty.

Checkpoint: ask for the source list and the refresh cadence per source — as a contract exhibit, not a slide. Then ask which sources are first-party and which are licensed. That's where your renewal risk lives, because licensed feeds get renegotiated every year.

3. Test coverage on your own closed-won list

This is the step that separates a real platform from a good sales deck. Hand them a CSV with 200 closed-won accounts and 200 closed-lost accounts, stripped of labels. Ask them to score all 400 blind.

Checkpoint: if they won't run it, that's your answer. If they do, look at whether their high-intent scores skew toward the won list. If it comes out a coin flip, you're paying for noise with a nice UI on top.

4. Look past the headline provider and ask about the enrichment waterfall

Waterfall enrichment means the platform tries provider A, then B, then C, and takes the first hit. Marketing copy usually leads with the strongest provider in the chain — which might cover only 20% of your records. What actually matters is the fill rate at the bottom of the waterfall, and who eats the cost when nothing hits.

Checkpoint: ask for a per-tier fill rate on a sample of your own data, and confirm in writing whether you're charged for misses. I've seen three contracts where the answer was "yes" and nobody on the buying team knew.

5. Walk the LinkedIn prospecting workflow end to end

If your SDRs live in LinkedIn, intent has to meet them there or it's just another dashboard. Build a 25-account list from one intent signal, push it to your CRM, push it to LinkedIn, and time the whole thing.

Checkpoint: if it takes more than ten minutes or needs an engineer, it won't get used on a Tuesday afternoon in Q4. Our rule is blunt — if a rep can't go from signal to outreach in one sitting, the seat gets abandoned and you're paying for shelfware.

6. Score the developer integration before you score the UI

This is the step teams skip, and it's the one that decides whether the platform actually fits your stack. A good-looking interface with a broken API is a manual data-entry tool with extra steps.

Put these in writing:

• REST, GraphQL, or both? Which surface is versioned and supported long-term?
• Auth model — OAuth 2.0 with scopes, or static API keys?
• Rate limits per minute, per day, and per seat. And what happens when you hit one?
• Webhooks for intent signals, or do you have to poll?
• Is there a sandbox with realistic records in it, usable before you sign?
• Idempotency keys on write operations?
• Documented field-level mapping between their schema and your CRM objects?
• A public changelog and a deprecation policy with actual notice windows?

Checkpoint: have one of your own engineers — not the vendor's solutions architect — spend two hours in the sandbox. When we ran this, the okki go API integration had webhooks on intent signals and a sandbox with real records in it, which honestly shouldn't be as rare as it is. Their okki go developer integration docs also shipped a changelog, and that's the detail I check when I'm estimating whether I'll be redoing this work in 18 months.

7. Build the TCO model, not the quote model

The quoted price is roughly half the cost. Here's my standard list of line items to chase down:

• Seat minimums and annual prepay requirements
• Credit-based pricing — how many credits per verified contact, and do unused credits expire?
• Overage rates. Ask what a bad month actually costs.
• API call charges or an "integration tier" upsell
• Implementation or onboarding fees
• Data retention limits
• The renewal escalator — most contracts build in an uplift, often 5–8%
• The cancellation notice window

Checkpoint: ask for the full order form and MSA before they walk you through the pricing deck. I've never once found a hidden line item in the deck. It's always around page four.

8. Run a 30-day paid pilot with a written kill switch

Define success before you start. Something like: "30% of pilot accounts matched with contact-level data, and reps booked 10 meetings from intent-sourced accounts." Then get the exit terms in writing — data export, whether credits carry over, and how much notice you owe.

I'll admit my bias here. I nearly went with a cheaper platform on a 24-month term because the math on the spreadsheet was clean. My gut said no — the sales engineer kept deflecting whenever I asked about overage billing. The upside was $14,000 over two years. The risk was being locked into a tool our reps wouldn't use, with no exit and no leverage. I passed. Six months later, two people in my network were stuck in exactly that contract.

9. Read the data rights and compliance paperwork

Boring, and it's the one that matters most when legal shows up. Three things to get in writing:

• Your lawful basis for processing under GDPR Article 6 if you touch EU contacts. Legitimate interest is the usual answer, and it needs a documented assessment — not a hand-wave in a security questionnaire.
• CCPA/CPRA opt-out and deletion handling for California residents, including whether the vendor passes deletion requests downstream to its own sources.
• CAN-SPAM responsibility. Per FTC guidance on the CAN-SPAM Act (ftc.gov), the sender bears responsibility for the message — your vendor's data hygiene doesn't transfer that liability to them.

Checkpoint: get the DPA and the current sub-processor list. Also ask the unglamorous question: are you buying the data or licensing it? That determines whether you keep the enriched records after you leave.

Where teams usually get burned

A few patterns I've watched repeat — including once on my own watch:

• Buying intent data and changing nothing about the workflow. If the signal doesn't change who a rep calls on Monday morning, you bought a report.
• Treating intent as a lead list instead of a prioritization layer. It's a ranking input, not a quota filler.
• Signing a 24-month term for a discount. You're trading optionality for a number that looks good in one budget cycle.
• Letting the vendor define the success metric. "Engagement" is not a metric. Meetings sourced from intent accounts is.
• Forgetting the human cost. Every hour of SDR time spent working signals is a line item too, even when it doesn't show up on an invoice.

It took me three budget cycles and about fourteen evaluations to understand something that now seems obvious: signal quality matters less than the workflow you attach to it. A mediocre signal wired into a tight sequence beats a great signal sitting in a dashboard nobody opens. Vendors won't tell you that, because the workflow is your job, not theirs. Which is fine — it just means this checklist is really about what you're going to do with the data, not what the data is.