"Intent data is a big giant scam," says Joey Gilkey, CEO of Apex revenue who's founded and sold-off billion dollar businesses. More importantly, he says "there's a difference between propensity and intent."

In response, his CRO colleague, Corey Rich, reports the most unproductive outbound campaigns he's been involved with, "are ones where the lists were built using intent data tools."

Gilkey concurs. "I’ve literally never met a sales team using 6sense that is actually hitting quota or driving any meaningful results. Unless you or someone you know uncovered intent through an interaction you can keep that trash."

What is intent data?

Intent data is commonly defined as a dataset showing what an individual may be interested in -- and what they are likely to do, say or buy next. The theory works like this: When you search for something online or visit a website, you are tacitly expressing an interest in particular topics. Your intention.

These activities are logged. Like it or not. Plus, they're sold. Are these actual "purchase intent signals?" Sometimes yes, more often no. But you know what my hero Bob Hoffman says.

"There's no bigger sucker than a gullible marketer convinced he's missing a trend."

Marketers have, for decades now, rushed in to embrace so-called intent data as a reliable (?) means to become more relevant to customers. They use it to be in the right place, at the right time with customers who are actively seeking to buy now -- or soon.

Where does data come from?

There are a handful of sources data sellers rely on. These are mainly:

1. First party data: Collected from your website, for example... when customers or prospects visit your site, fill out a form, click on emails, attend webinars and more.
2. Third party data: They may source data from large aggregators of data like site traffic, search behavior, content consumption, social media activity, purchase intent signals, etc.
3. Social media data: Intent data providers may pull activity data from social media platforms like LinkedIn -- where mentions, engagements (likes, reactions) and conversations using keyword topics or brand names... all assumed to be buying / purchase intent signals.

Of course, companies selling intent data are asked to adhere to privacy regulations and ethical guidelines when collecting and using consumer data. This includes obtaining consent when necessary, anonymizing and aggregating data to protect individual privacy, and providing transparency about data practices to users.

This is an important fact we'll return to.

Does it truly reflect buying intent?

Should you use it and how?

Is intent data worth investing in -- and applying? If so, how?

Having access to intent data is one thing; knowing how to use it is another. Here's my hot take. Beware: It's negative. I present positive recommendations / experiences in this post too... so you can decide for yourself.

In my experience, buying into the intent data wet dream 🙂 is, most often, an insurance policy on outbound sales failure.

Because believing intent data is a strong signal promotes bad behavior. I'm literally coaching BDRs sending emails like this:

"I saw that someone from [prospect] was looking into our content regarding [topic]. I cannot see exactly who was educating themselves on our solution, but I thought I'd reach out to you as the [title] at your organization."

That's saying the quiet part out loud. How does this look to the customer? Creepy and ignorant.

I'm convinced: Most everyone who sends messages like this knows -- it makes them look like an ignorant stalker. Yet they participate in the belief -- intent data is a strong (enough) signal.

It's not.

Buying intent data is, actually, buying an insurance policy on failure.

"I think the problem is sales teams are basing their entire outreach on intent data -- as opposed to doing primary research and augmenting it with intent data. Big difference between the two," says home made pizza lover, Damien DeHart of Checkmk. 

Monty Folwer, VP of Revenue Strategy at Kintik is a skeptic too.

He says the "big idea" behind intent data is, "meaningful information can be inferred from analyzing what topics a particular audience or persona is actively engaging with online. The value proposition goes something like, 'we can predict future customer behavior, thereby assisting businesses in targeted marketing or sales strategies.'"

Below are challenges Monty says cause his team to doubt the intent data vendors' claims and promises.

• Data Integrity: Poor data quality can undermine the insights generated.
• Limited Scope: A narrow focus can miss crucial cues.
• Bias Risks: Confirmation bias can cloud the insights.
• Transparency: The "black box" nature of algorithms can make it hard to assess their reliability.
• Cost Concerns: There is a mismatch between the cost and the proven value of these services.
  

Is intent data needed?

"Most people don't need inferred intent coming from an algorithm. They need basic insights like... 'which accounts are actually using our trial?' and 'immediate notification of important events to jump on as a sales rep,'" says Sam Arnold, an Enterprise AE at Census. 

"I'm biased because I sell this, but I think the key for most companies is to get key data into sales & marketing platforms from the data warehouse (esp. usage-based data and events) without having to do a bunch of back-and-forth with engineers or SFDC dev work. Shockingly few companies actually do the basics before investing in something like 6sense."

"At the end of the day, it comes down to strategy and building the proper framework BEFORE you buy intent data software," says Courtney Wilbanks who leads sales teams.

"If you have a CRM data mapping problem, and your reps simply are not being taught data integrity, nothing can patch up your outbound. I always tell people: peel back the why."

She also points out how proper account segmentation factors in. "Which is what reps should be taught, not pull a list and fire. Understand your target. It literally boils down to understanding your target and using intent to support NOT fuel."

When can it work well enough?

"I was working with several Fortune 500 clients selling to mature markets to a mix of install-base, cross-sell and new logos," says B2B tech growth strategist Hans Bunes. "We used a combination of third and first party data intent to gauge what could be of interest to these accounts. A couple of observations:

1. Nine out of ten times I told a sales rep to investigate a signal of intent, it was confirmed. Meaning, the account was actively pursuing an area that we saw signals on.
   
2. We saw signals from install-base towards 3rd party, but not 1st party but failed to recognize what the signal was telling us. Namely, that a competitor was taking our client out.
   
3. For months we saw massive spikes in 3rd party signals, but failed to understand them. They were a precursor to a big RFP/RFQ from a local government body.

It's like most things in life. Neither black or white. It depends on the context of the market. 

Again, Joey Gilky's points about the difference in propensity and intent is profound.

Propensity is "an inclination or natural tendency to behave in a particular way." Intent is one's determined purpose.

Joey says, "Big broad search terms do little if any good at all, complicated by the fact you don’t know who was searching for the topic."

Jacob Lauritzen, founder of Unhaze, has studied intent data quite 6sense (and other 3rd party intent providers) customers. Often (but not always) it turns out, "'in-market' accounts close just as often as those not 'in-market,' neither more nor less.

My hypothesis is if you reach out once the prospect is already actively looking for / evaluating competitors ('in-market'), you’re already behind your competition and the prospect has already formed an opinion without your input. 

On the other hand, reaching out to prospects that don’t show intent mean you need to convince them. All in all, across quite a few customers of ours, the win rates are more or less the same."

Intent data does, however, shine in combination with other signals. If a small company shows intent for customer success software and their cs team is growing under a recently hired head of cs that’s a really good signal. If a big company with a stable/stagnant cs teams shows the same intent, it may not help as much."

That said one of our Academy members in the contact center outsourcing space courts the Fortune 1000 and does very well using intent data based mainly on search signals.

What is your experience teaching you? See you in comments!