This is the TitanX newsletter, where GTM is built on conversations, targeting, and, of course, Phone Intent™ - Read more.
We all want to filter down our market to those we should talk to today.
But how? Is that even possible?
In other words:
What in the world is “intent”?
In this newsletter, we’ll cover:
The big Internet and how B2B intent vendors came to be
Different kinds of intent - what’s worth it, what’s not
What Phone Intent is and how to think about prioritizing your market
Throwback: too much VC money, too much Internet to analyze
10 years ago, I was an industry expert on social listening, writing for eConsultancy, TrustRadius, G2 Crowd (now G2) back when they invested in independent category analysts. At the time, tech startups were paying gobs of cash for access to the Twitter “firehose” API and storing hundreds of millions of websites (news, blogs, media), and using NLP (Natural Language Processing - the thing most data scientists did before LLMs) to analyze all the posts. It was extremely expensive to build; most tools charged $40,000+ for access.
But this experience also kind of broke me - as I slowly saw how detached from the “revenue reality” this data was. It was incredibly interesting data. (I sat with Verizon Wireless marketing leadership and analyzed the difference in sentiment among their support chatter on Twitter vs. the other major telcos. Even color-coded the charts per the big 4 branding.)
One time, I presented dashboards of social listening data I had worked extremely hard to build. It was to a room of HBO execs. No response. Nothing. They just walked out at the end of my presentation.
All that social listening… It just… didn’t really matter.
You can’t take action off of the vague sense of what’s happening at scale on social media, unless maybe you’re a politician. Or a journalist writing about the vague sense of what’s happening at scale on social media.
Then I heard about “buying intent” vendors for B2B.
By that time, I was building ROI models for the now-CMO of Slack. For the first time in my career, attribution to revenue mattered.
One of these intent vendors tried selling us their platform. I asked for a meeting with the data science team. I knew a bit about NLP, web scraping, topical analysis across web datasets, and ID resolution for adtech.
They wouldn’t answer any questions satisfactorily - no explanation for why “data management” is a distinct category from “data governance” and how they split those hairs, and which one indicates more “buying intent.” Which just confirmed my fears.
Intent data is a fiction of venture money injected into adtech and social listening.
The premise “we can tell which companies are interested in buying your software category because someone who works there has been browsing your related topics on the web” is flawed in two key ways:
It’s really hard to draw a line between reading some articles and buying software. I haven’t seen any robust research around it.
It’s really hard to draw a line between which individuals in which part of the company and their real access to buying authority.
It’s no shock to call out the kind of “buying intent” above as problematic. This sort of “topical intent” or “3rd party intent” has been called out before, most recently by Jason Bay. The reason I bring it up is to set the stage for other types of intent.
Why we call TitanX “Phone Intent”
If we say “intent” is “using special datasets to filter your GTM activity into higher-likelihoods of success” then there are a few other categories worth mentioning:
2nd party intent: Review sites like G2 offer a service where they share the companies actively searching for your software. This makes sense. They know the companies from logged-in users, and people go to G2 to shop for tech. Passes the smell check. Mixed results in my experience, but logically sound.
1st party intent / website intent: This is what visitor identification (whether at account or contact level) tools do, and it’s really just a good engagement signal. It definitely should be in your stack, whether via Snitcher or HubSpot’s access to Clearbit or another tool. Accuracy ranges from 60-80% so be careful you don’t bet the house on it. Note: contact-level identification without consent is a legal gray area.
Behavioral intent: this is where “phone intent” lives. A good analogy is “social intent” (which I invented just now but is a common practice) - where if you want to launch a LinkedIn outreach campaign, you filter to LinkedIn profiles that have been active in the last 30 days. Otherwise they probably don’t use LinkedIn for communication very regularly.
Phone intent operates similarly, where we use signals first to eliminate waste, and second to determine if this person is in fact a “picker-upper” - someone who answers cold calls. Note: ensure TCPA compliance from your phone intent vendor (no AI voice on cold calls or AI placing calls that get dropped).
Why people gravitate to Intent: you need results today
By framing the deep, behavioral phone validation TitanX provides as Phone Intent, we’re leaning into the primary reason people buy intent tooling: they want immediate outcomes.
It’s not wrong to want to solve for this quarter’s goals. Often this happens because of major growth needs with new funding or new markets, or because of shortfalls in hitting growth targets.
Great. You can - and should - get those results from Phone Intent:
The long game: eliminating outbound waste
There’s more to Phone Intent than immediate results. You can actually build a powerful system around prioritizing and filtering your market into behavioral buckets
Those who answer the phone
Those who answer email
Those who are active on social
If you could map your TAM by where they spend their time, you’d quickly detach from the assumptions you have - that they’re all on LinkedIn, or all respond to cold email, or are all lurking Reddit - aren’t all true and aren’t all false. It’s a mix.
We believe you should build lists for your outbound efforts that are already filtered by propensity to respond on certain channels.
In short: we’re not here merely to piggyback on “intent” as a term - we’re here to reform it.
The volume playbook is dead. Welcome to the Era of Phone Intent.
Thanks for reading,
Evan Dunn (LinkedIn)