If you've ever been handed a 47-page intent data report at 4 p.m. and asked to turn it into pipeline by Tuesday, you know the feeling: half excitement, half existential dread.
In my role coordinating revenue operations for B2B sales teams, I've triaged 200+ rush implementations in the past five years. I'm the person RevOps leaders call when an AI outbound stack needs to be working by Monday, or when a license renewal decision has to be made in 48 hours. So let me start with the uncomfortable truth: there is no single answer to what you should evaluate in intent data. It depends on whether you've already bought it, and whether your team can actually act on it.
The trigger that changed how I think about this was in March 2024. Thirty-six hours before a board review, a VP asked me to justify a $60,000 intent data renewal. The dashboard looked impressive. Then I pulled actual usage: sales had logged 14 activities against 'high-intent' accounts in six months. The vendor wasn't bad. The data wasn't necessarily wrong. The workflow around it was broken. That's when I stopped asking 'which data is best?' and started asking 'what does this data have to do to earn its keep?'
How intent data actually works
Intent data is behavioral evidence that a company is researching a topic. Providers collect signals from ad clicks, content downloads, review sites, third-party cookies, and sometimes your own CRM or LinkedIn activity. They score those signals and label accounts 'high intent' when the behavior looks like someone comparing products or pricing.
That label matters less than how the data was produced. A high-intent score is a prediction, not a fact. It might mean the account is actively evaluating a solution. It could also mean an intern downloaded a whitepaper because their boss said 'research AI SDRs.' Don't confuse those two things.
Three scenarios, one framework
I organize every intent data conversation into three scenarios. The advice is different for each, but the framework underneath is the same: total cost of ownership, not sticker price. I got burned early in my career by comparing line items instead of total outcomes, and I've tried not to repeat that mistake.
- Scenario A: You're evaluating intent data from scratch.
- Scenario B: You already have intent data, but it isn't converting.
- Scenario C: You're trying to decide whether you need intent data at all.
Scenario A: You're evaluating intent data from scratch
If you're starting fresh, you can skip the mistakes I made. The no-brainer first step is a 'so what' test.
So what test: Show me the five most recent high-intent accounts in my ICP. For each one, what exactly should a sales rep do tomorrow morning? If the answer is 'upload them to a sequence and hope,' keep looking.
The counterintuitive part: more data isn't better. I once compared two intent platforms side by side—one with 3,000 signals, one with about 12. The wide platform sent alerts for companies researching adjacent topics. The narrow platform was mapped specifically to our buyer journey. It wasn't close. The narrow one won. When I look at intent data now, I ask about signal definitions before I ask about data volume.
Then I apply total cost thinking. The license price is only the beginning. You need to evaluate:
- Matching quality against your actual ICP.
- Contact-level coverage. Intent without an email or phone number is decoration.
- Integration time with Salesforce or HubSpot and your cold email platform.
- False-positive cost. A rep spending two hours chasing a 'high intent' account that isn't ready to buy is real money.
- The time your ops team will spend turning a raw feed into something sales will use.
Per FTC guidance (ftc.gov/business-guidance/advertising-marketing), claims like '3,000 intent signals' need to be truthful and substantiated. Ask the vendor to show you the list. Then ask which signals your ICP actually emits. When a vendor can't answer that, it's a red flag.
Scenario B: You already have intent data, but it isn't converting
This is the scenario I get called in for most. It's usually the ninth inning: license renewal in four weeks, sales team calling intent data 'the dashboard of false promises,' and RevOps ready to cancel.
Don't cancel yet. Triage first.
The most common issue I see is not data quality. It's follow-up ownership. An alert goes to a shared inbox, then to Slack, then somewhere between the CRM and the floor. By the time a rep picks it up, the window of relevance is gone. I'm not 100% sure whether that's a software problem or a people problem, but the fix is usually the same: route alerts into the tool your reps already live in and assign a task within 24 hours.
Here's a comparison that changed my perspective. One team took an average of 11 days to contact an intent alert. Another team, using the same vendor, created a task in HubSpot within 24 hours. The data was identical. The follow-up velocity was not. The fast team generated meaningful pipeline; the slow team generated a cancellation request. Seeing those two side by side made me realize that intent data is only as good as the workflow that sits on top of it.
So before you switch vendors, give yourself one quarter to fix the workflow. I calculated the worst case for one renewal decision: cancel, rebuy a new platform, spend two quarters rebuilding reports, and still have the same follow-up problem. The upside of canceling was a few thousand dollars a month. The risk was losing a year of behavioral history and resetting the learning loop. Switching before fixing is just exporting a broken workflow to a new platform.
Scenario C: Maybe you don't need intent data at all
This is the one that makes some vendors uncomfortable. Some RevOps teams simply shouldn't buy intent data.
If your target segment is SMB, your sales cycle is short, and your outbound team has fewer than ten reps, the total cost of intent data is hard to justify. You're better off with a clean contact database and a well-built cold email platform. An AI outbound tool like Artisan AI sales software, with an autonomous AI SDR (Ava) and CRM enrichment, can keep your reps busy with 300M contacts before you ever need an intent layer. Intent data is a multiplier for teams that already have a working outbound motion, not a substitute for absent fundamentals.
I told a client in 2025 to kill the intent pilot and put the budget toward CRM automation instead. Follow-up rates on existing leads doubled. The 'world-class intent plan' had been waiting for leads to enter the funnel—which the CRM had been doing all along. Granted, if you have a large enterprise sales team and a narrow ICP, intent data can be a game-changer. But you have to prove you can act before you spend more money on signals.
How to decide which scenario you're in
Here's the self-audit I use with our clients:
- Have you ever closed a deal from cold outbound? If no, work on that first. Intent data doesn't create responsiveness. It just points you to someone who is already thinking about a problem.
- Can you name the last five accounts your intent platform flagged? If no, the data isn't integrated into your workflow. That's Scenario B, not A.
- What would actually change if your intent feed disappeared tomorrow? If the answer is 'nothing,' cancel the renewal. I've been in all three scenarios, sometimes in the same quarter, and there's no shame in admitting this one.
The bottom line
Your revenue operations team should evaluate intent data by the size of the action it drives, not the size of the dataset. The TCO framework includes license cost, integration cost, process cost, false positives, and opportunity cost. Everything else is vendor marketing.
And if you're comparing Artisan AI B2B sales automation to other options, ask the same questions. How does the platform turn intent signals into next steps in a cold email platform or LinkedIn sequence? Where does the alert land? Who owns the follow-up? Take it from someone who has had to triage this at midnight: start with your workflow, not the data. The right data will follow.
