This is the response I occasionally receive when I mention intent data. Sometimes delivered with a bit of a contemptuous sneer, this critique of intent data is a red herring.
A Tesla Doesn't Burn Diesel
So what? Does that mean that a Tesla isn't a valid form of transport?
Does a conversation in a trade show booth mean someone is ready to buy? Could it be just a long-time industry acquaintance saying hello? Or only a serial customer nurturing a support relationship? Or is it a decision maker from a new logo with a well defined requirement and allocated budget that's struggling to find the precise capabilities you can deliver?
Does an online white paper download indicate intent? Or interest? What if someone read it if it was ungated and never submitted a form? Or maybe it is a competitor, or even a student, doing some research?
Of course all of those situations are common - well, all except the decision maker with allocated budget visiting the trade show booth.
That's why marketing and sales exist.
Successful companies create and detect interest - in solving a problem, achieving an outcome, exploring competitive solutions, etc. Then they qualify and nurture that interest until they're able to disqualify a prospect or create an opportunity.
Lead Scoring & Fit
As a prospect travels the interest continuum, when should BDRs get involved? Or Inside Sales jump in? Or an Account Executive join the conversation? Or should they?
Those are deceptively complex questions, and the reason companies score leads and use terms like IQL (information qualified lead), MQL (marketing qualified lead), SQL (sales qualified lead), and as we recommend IDQL (intent data qualified lead.) It's also why companies use tools like ICP (ideal customer profile) and discuss both account and prospect fit.
These are fundamental building blocks of B2B marketing and sales. Not every prospect buys, and those that do, follow their own unique buying journey.
Just Send us SQLs or We Don't Know How to Use Intent Data
So what does someone really mean when they protest that "interest doesn't equal intent"?
In my experience it's one of several things.
The simplest might simply be some form of "Look. We're busy. We're working on a bunch of opportunities and are always excited to work on more, but we don't have time to chase leads." This could be factual, or driven by laziness, but it's based on the sales team's perception of the return on their time. Either way the message is basically, just send us SQLs when they're ready for our sales process.
In other cases, it's someone who was handed a large number of intent data leads and didn't generate results. That may be based on statistical comparison (e.g. they worked 1,000 random leads and 1,000 intent data leads and didn't see higher performance with the intent data group) or anecdotes and gut feeling. That certainly could be a reflection of the data quality, just as it could reflect other variables as well. Maybe the data wasn't tuned to collect the right leads. Perhaps the segmentation was poor and therefore messaging poorly targeted. The messaging itself could have been mediocre. Or maybe the sales person didn't bring passion and enthusiasm and lacked quality enablement content.
And in some cases the real message is "We're really not sure how to use it." There aren't many who say that, but that's the answer you'd get from most marketing operations and sales operations teams who answer honestly. Intent data best practices are still being written, and effective activation tactics are often discovered through experimentation, integration of multiple data sets (e.g. a company's own first-party data along with one or more sets of third-party data), rigorous segmentation and finely tuned multi-touch sequences.
A Non-Binary Approach
Therefore the solution isn't to simply either adopt intent data completely or reject it fully.
The right solution is to test, adjust, learn and test some more. That includes testing data filters, email templates, call scripts, scoring and hand-offs, segmentation and more.
But when I hear someone say "Interest doesn't equal intent" (or it's cousin "Content intent is different than purchase intent") experience tells me that I'm talking to someone who's either looking for a simple, and easy answer to revenue growth or who's never had the opportunity to explore the nuance and potential of contact level intent data fully.
I've learned to skip the first type of conversation, and to relish the second.