Demand Generation

Intent Data Is Mostly Hype. Here's When It Isn't.

Erik R. Miller 11 min read

Almost every B2B marketing leader I talk to has bought intent data. Most of them cannot tell me what return it delivered. The contracts run six figures. The vendors pitch boardroom-grade dashboards, surge scores, topic clouds. The reality, in most organizations I have walked into, is that intent data sits unused inside a CRM, generating noise nobody knows what to do with.

I am not anti-intent. I have used third-party intent platforms to surface accounts that became real pipeline. I have also watched teams burn budget on intent feeds that were measuring something — anything — and selling the output back to them as signal. The difference between those outcomes is rarely the platform. It is whether the team that bought the data ever built the operating system to act on it.

This is what I have learned about when intent data actually earns its place in the stack, when it becomes expensive shelfware, and the first-party signals that quietly outperform the dashboards that get all the budget.


The promise versus the reality

The pitch is seductive. A vendor sits across from your CRO and says: we will tell you which accounts are in-market right now, before your competitors know, so your sales team can call the ones with their hand half-raised. They show a heat map. There are color-coded surges. There is a slide with a logo grid of customers who, the vendor implies, used the data to triple their pipeline.

What the pitch leaves out is the work between the data arriving and pipeline being built. Intent data is not a list of buyers. It is a probabilistic signal — usually based on bidstream telemetry, content consumption on third-party publisher networks, or aggregated B2B research behavior — that someone, somewhere inside an account, looked at content related to a topic. That is meaningfully different from someone with budget, authority, and a defined evaluation timeline raising their hand.

Most teams treat the signal as if it were the second thing. Then they wonder why the conversion rate from "surging account" to "qualified opportunity" is in the low single digits.

Intent data does not tell you who is buying. It tells you where the room is warmer. Whether you actually find a buyer in that room depends entirely on what you do next.


Where intent data actually pays back

There are specific moments where a third-party intent feed earns its budget. They are narrower than the vendors suggest, but they are real.

Prioritizing a defined target list

If you already have a tight ABM list — say, three hundred named accounts you have decided are the right shape for your company — intent data can help you sequence them. The accounts surging on relevant topics this week get a Tier 1 motion this week. The dormant accounts move down the queue. The list itself is unchanged. Intent only changes the order of operations.

This works because the underlying account selection is already correct. You are using intent to allocate finite sales attention across accounts that already meet your ICP. You are not using it to find new accounts. The signal does not have to be perfect for that to be useful.

Identifying topic shifts inside named accounts

If a Tier 1 account that has been quiet for nine months suddenly surges on three topics tied to your category, that is a real prompt. Not a guarantee — a prompt. Something inside that company changed. Maybe a new VP. Maybe a contract renewal. Maybe a board mandate. Whatever it is, the conversation you have with that account now is different from the one you would have had a month ago. Intent data does not tell you what changed. It tells you the room is different. Your job is to walk in and find out why.

Surfacing dark-funnel research

Most B2B buyers spend the majority of their evaluation in dark-funnel mode — anonymous research on third-party publishers, peer review sites, communities, and YouTube. Form fills come at the very end, sometimes never. Third-party intent is one of the few honest ways to see this activity, because the buyer has not opted in to anything you own. Used carefully, it can compress evaluation cycles by surfacing accounts that are already deep in research before any of your forms get filled.

Reactivating closed-lost accounts

Closed-lost accounts that show fresh intent six months later are one of the highest-converting motions I have seen. The buyer already evaluated you, knows your category, and chose someone else. If they are surging again, something about the original decision is being revisited. That is a different conversation than a cold outbound, and it should be handled by an AE, not a BDR.


Where it falls apart

Most of the failures I have watched happen are not platform failures. They are operating model failures. The data shows up. Nobody owns what to do with it. Six months later somebody in the QBR asks why the intent platform is in the budget.

Treating signals like leads

The first failure mode is handing surge alerts to BDRs as if they were inbound MQLs and asking them to call. The conversion rate is awful, the BDRs lose faith in the data, and within two quarters nobody opens the dashboard. Intent surge is a prioritization signal for an existing motion. It is not a lead. The moment you treat it like one, you have broken it.

Buying topics nobody mapped to your ICP

Intent platforms let you select hundreds of topics. Most teams pick too many, weight them too evenly, and end up with a feed that surfaces noise. The topics need to be narrow, mapped to the specific buying questions your category triggers, and weighted by how predictive they actually are. Few teams do that work upfront, and the data is only as useful as the topic taxonomy underneath it.

No closed-loop measurement

If you cannot trace which surging accounts entered pipeline, closed, and at what velocity compared to non-surging accounts in the same segment, you cannot tell whether the intent feed is doing anything. Most teams do not build that measurement. They look at vanity metrics — surges this month, accounts touched, dashboards opened — and assume value. Without a control group, you are spending six figures on a feeling.

Letting the vendor own the workflow

Some intent platforms try to become the operating layer — workflows, alerts, sequences, all inside their UI. This works for a quarter and then breaks. Sales lives in the CRM. Marketing lives in the marketing automation platform. Anything that requires reps to log into a third tool to act on intent will lose. The data needs to flow into the systems where work already happens.


First-party intent: the part nobody talks about

While teams spend six figures on third-party intent feeds, the highest-quality intent signal in any B2B organization is sitting unused in tools they already pay for. First-party intent is what your own properties, content, and product can tell you about a buyer's behavior — and it is almost always more predictive than anything a third party can sell you.

A few signals I trust more than any third-party feed:

Pricing page visits from named accounts. If three different people from a target account hit your pricing page in the same week, that is a more honest signal than any topic surge. It is also free.

Demo or sales-page repeat visits. A second visit to a high-intent page within thirty days is one of the most predictive signals of opportunity creation I have ever measured.

Content consumption depth. Not whether someone downloaded a whitepaper — whether they came back, read more than one piece, and went deeper into the funnel of content. The progression matters more than the entry point.

Product engagement, if you have a self-serve motion. Activation milestones, feature usage, team invitations — first-party product signals that no intent vendor can match. They reflect real behavior, not inferred behavior.

Inbound chat or community questions. Someone asking a specific question in your community or on your site is showing intent in the most direct form available. These should never sit in a queue.

Most B2B teams have these signals already, sitting in their analytics platform, their marketing automation, or their product database. They are buried under dashboards nobody opens. Surfacing them in the CRM, at the account level, with simple rules, is more valuable than buying another third-party feed.


A framework for evaluating intent data

Before you renew, expand, or buy intent data, run the contract through five questions. If you cannot answer all five, do not sign.

The Five-Question Test

Before you spend on third-party intent

Owner Who is responsible — by name — for acting on this data every week? If the answer is "marketing" or "sales," it has no owner.
Workflow What specific motion does this signal trigger, in which system, with what cadence? If it does not flow into the CRM with a defined play attached, it will not get used.
Topics Have we mapped fewer than fifteen topics tied tightly to our buying questions? If you selected more than fifty, you have a noise problem already.
Measurement Can we compare surging accounts to a matched control group on pipeline conversion and velocity? If not, we cannot tell if it works.
Coverage Have we already surfaced our first-party signals in the same workflow? Buying third-party intent before exhausting first-party intent is putting on a second seatbelt before fastening the first.

If you can answer all five and still need more signal, intent data is probably worth it. If you cannot, the platform is not the problem. The operating model is.


The bottom line

Intent data is a tool, not a strategy. In the right hands — a tight ABM list, a clear topic taxonomy, a defined play attached to each signal, and a closed loop back to pipeline — it earns its budget. In most hands, it becomes another six-figure dashboard nobody opens.

The pattern is consistent. Teams that succeed with intent data treat it as one input into a motion they already had. Teams that fail buy it hoping it will be the motion. The platform cannot save you from a missing operating system. It can amplify a good one.

Before you sign or renew, build the operating model first. Map the topics. Name the owner. Wire the workflow into the CRM. Surface your first-party signals next to the third-party ones. Define the measurement. Then turn the feed on. Done in that order, intent data is one of the more useful tools in a modern B2B stack. Done in any other order, it is the most expensive way to feel busy.

— Erik R. Miller

Erik R. Miller

B2B marketing executive. Builder. Operator. 15+ years building revenue marketing functions across four continents. Plain talk on demand gen, ABM, and the operating models that make GTM actually work. Subscribe to The Operator for more.

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Frequently Asked Questions

What is B2B intent data?

B2B intent data is a probabilistic signal — usually based on bidstream telemetry, content consumption on third-party publisher networks, or aggregated research behavior — that someone inside a target account has looked at content related to a topic. It is meaningfully different from a buyer raising their hand. Intent data tells you where a room is warmer, not who is buying.

Does intent data actually work for B2B?

Yes, in narrow circumstances. Intent data earns its budget when you already have a tight ABM list and use it to prioritize which named accounts get attention this week, when surfacing topic shifts inside dormant Tier 1 accounts, when revealing dark-funnel research, and when reactivating closed-lost accounts. It fails when treated as a lead source, layered over a poorly-defined ICP, or measured without a control group.

What's the difference between first-party and third-party intent data?

First-party intent is behavioral signal from properties you own — pricing-page visits, demo-page repeat traffic, content consumption depth, product engagement, inbound community questions. Third-party intent is inferred from off-site activity by vendors who aggregate publisher behavior. First-party intent is more predictive of pipeline because it reflects actual buyer behavior on your own surfaces, not inferred behavior elsewhere. Most teams underuse first-party signal while overspending on third-party feeds.

How do you evaluate whether intent data is worth buying?

Run the contract through five questions. Who is responsible — by name — for acting on the data weekly? What specific motion does the signal trigger, in which system, with what cadence? Have you mapped fewer than fifteen tightly-scoped topics? Can you compare surging accounts to a matched control group on pipeline conversion? Have you already surfaced your first-party signals in the same workflow? If you can't answer all five, the platform isn't the problem — your operating model is.

Why do most intent data programs fail?

They fail at the operating-model layer, not the platform layer. Common failure modes: handing surge alerts to BDRs as if they were inbound leads (conversion is awful), selecting too many topics so the feed becomes noise, never building closed-loop measurement against a control group, and letting the vendor's UI become the workflow instead of the CRM. The data shows up, nobody owns what to do with it, and within two quarters the dashboard sits unused.

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