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A Guide to Intent Data: The Secret to Marketing and Sales Success

Intent data can reveal which companies are ready to buy and what’s driving their interest. Here’s how you can turn these insights into revenue breakthroughs.



Chapter 1


Chapter 2

What Is Intent Data?

Chapter 3

How Intent Data Starts the Sales Engine

Chapter 4

Making Intent Data Matter

Chapter 5

Why Intent Data Matters to Sales and Marketing

Chapter 6

Why Sales Teams Love Intent Data

Chapter 7

Meet Your Next-Gen Metrics

Chapter 8


Table of Contents

Chapter 1


What do we know about the selling and buying cycle today?

  • We know less than 5% of website visitors fill out forms
  • We know that of those form-fills, only 25% become an MQL
  • We know 70% of the buyer’s journey happens before they raise a hand

We also know traditional demand gen doesn’t work. Bombarding prospects who fit your ICP but aren’t in the market for a solution creates noise, not value.

So how can sellers find and support buyers who are ready to connect?

By harnessing the power of intent data.

Chapter 2

What Is Intent Data?

Every time someone uses the internet to search for a keyword, visit a website, use social media, download a whitepaper, or do literally anything online, it creates a data trail. Each action serves as a virtual footprint, and a trail of virtual footprints can be used to track and predict buyer behavior.

This information is called intent data, because it can be interpreted to provide B2B revenue teams with valuable insights like:

  • Who may be interested in their products and services
  • How likely they are to become a customer
  • When they’re most likely to make that decision

Some of that information is known as first-party intent data: information that comes from within your own systems, including your company’s website, your CRM or MAP, and custom analytics.

Other information comes from outside your systems: third-party intent data. Providers collect and aggregate this information from external sources such as blogs, social networks, and industry solution providers.

Assembling this information can help determine everything from where a prospective customer is in the buying process to which competitors they are interested in.

Chapter 3

How Intent Data Starts the Sales Engine

We’re not in the demand-gen Dark Ages anymore. The rise of data-powered artificial intelligence (AI) means new opportunities and a better path to success for buyers and sellers with the smart use of intent data.

Finding prospects to fit a company’s ICP was never the issue. It was finding the overlap in a Venn diagram of the ICP and the in-market ICP (we like to call that the IICP).

Now, instead of waiting around for in-market buyers to reveal themselves, sales teams can use the power of intent data to find potential customers as they launch their search, and meet them at the right time with the right message, guiding their progress and offering the tools they need.

Chapter 4

Making Intent Data Matter

On its own, intent data is usually anonymous, which can be useful information in its own right. Sales teams can use aggregated intent data to track interest in topics and look at trends in competitor research and keywords.

But when intent data is de-anonymized, its benefits to the sales cycle grow exponentially. Account engagement platforms like 6sense use AI to match this intent data to specific companies and personas using internal Customer Data Platforms.

That means now not only does your team know what people are searching for, they also know who is doing the looking. Putting that information together, you can:

  • Prioritize in-market accounts
  • Personalize messaging based on interest
  • Uncover and target buying committee members
  • Offer bespoke and personalized content based on search information

Too many marketers sit on mounds of data without any way to make sense of it. Having an AI trained on B2B sales data that can recognize specific behavior patterns and highlight sales opportunities? That’s a game-changer.

We all leave “footprints in the snow” as we traverse the web to shop, research, socialize, and more. We’re inclined to think of our steps as anonymous. But to the right sleuths, these tracks might be the next big sale.

We refer to this world of anonymous buyer intent data as the Dark Funnel™.  For B2B revenue teams, matching traditionally unidentified Dark Funnel clues to known accounts is the new key to usher buyers through the sales funnel.

Want to learn more about how AI turns these footprints in the snow into actionable data? Check out A Deep Dive Into the Dark Funnel to learn about the wealth of anonymized buyer intent data that wasn’t visible to revenue teams … until now.

Chapter 5

Why Intent Data Matters to Sales and Marketing

Intent data can power your revenue team’s efforts on multiple fronts. It’s not a replacement for the traditional connections created by sales and marketing — it’s a way to augment and support the work your teams already do well.Here’s how it pays off:

For New and Existing Leads

In addition to the generalized market research, anonymous intent data gives us to help organize our approach to the sales funnel, de-anonymized intent data allows revenue teams to orchestrate buyer journeys from behind the curtain.

That means crafting the right marketing and sales materials and making them available to answer questions just in time — or even before.

And it means offering customized website experiences depending on persona or industry, creating targeted off-site advertising, and following the customer journey in order to ensure the messaging matches the buying committee’s process.

Digital display ads have lots of options for targeting and personalization, but intent data makes all the difference. When you use intent data, AI, and predictive analytics, you can serve ads only to the people that are in-market for your product or service.

What’s more, you can personalize those ads depending on where the prospect is in the buying journey, which is a better experience for them and a smarter use of ad spend.

There’s a lot to learn about digital advertising, but don’t worry, we’ve got you covered.  

Events and Webinars

Events and webinars don’t have to be blind or passive experiences, waiting for the right prospect to show up.

Intent data transforms connections before, during, and after the event. A platform that can identify and predict buyer intent will allow you to match your efforts to the attendees instead of a broad, generic experience.

Here’s how you might use intent data to promote an event from beginning to end.

Before the event:’

  • Match attendees to ICP and IICP
  • Identify attendees who are already engaging and researching your brand
  • Target attendees with personalized information and invitations
  • Research and prepare for connection

During the event:

  • Run planned plays when high-intent prospects visit or engage
  • Use research to personalize conversations and connections with IICP attendees
  • Create opportunities for in-depth, personalized interactions with target accounts

After the event:

  • Measure ROI based on account engagement
  • Evaluate additional information from conversations, questions, and interactions
  • Follow up with personalized content based on new data

Uncovering Buying Teams

For years, Forrester’s data has shown that the size of buying teams for large purchases can easily exceed a dozen stakeholders. The larger and more complex the purchase, the larger and more complex the team.

Our own research indicates buying teams can range from six members to up to nineteen.

The size of the buying team changes the work that sales and marketing needs to do. It also changes the information that will help them.

Again, intent data can reveal information about the buying team’s members and goals. This information means selling and marketing teams can:

  • Research specific personas on the team
  • Include personalized information to target multiple team members
  • Determine which teams are truly in-market

And unmasking the people behind anonymous intent data is a game-changer. “The challenge is that businesses don’t buy things. Individuals buy things. So you have to find the committee of individuals that buy things,” says Erik Matlick, Founder and CEO of Bombora.

Most of today’s B2B customers conduct the majority of their buying journey through anonymous online research.

Any account-based platform worth investing in today uses intent data to shine a light on these unknown accounts’ activity. Otherwise, you’re only able to identify the 3% of website visitors who fill in forms and self-identify on your website.

Intent data is a combination of signals that are generated when people search the web, visit your site, and visit third-party sites that share data. In the case of B2B buying groups, this combined data can reveal which companies are in-market for your solution (i.e., considering a purchase).

But is intent data GDPR-compliant?

First-Party Intent Data

First-party intent data is uncovered by activities on your website, or the data you already have in your CRM. To identify the activities of potential customers, your account identification solution will need access to this data.

To remain compliant, as the controller of Personally Identifiable Information (PII), it’s up to you to follow the appropriate steps when sharing this data — including obtaining consent where required.

Third-Party Intent Data

What about the data generated when buyers are conducting research on websites that aren’t yours, such as online trade publications, blogs, forums, and communities?

Uncovering this third-party data is essential to better understand your in-market prospects. But whether or not that data is GDPR-compliant will come down to your account identification solution provider.

If you’re intending on using an account-based approach in Europe, for instance, always check that potential providers have the appropriate safeguards to process PII and source third-party intent data in compliance with GDPR.

Turning Data Into Insights

With the right safeguards in place, providers of intent data will match an intent signal to an account. For example, intent signals might show:

  • Whether “Acme Industries” is conducting research on ABM, for instance
  • What keywords were viewed
  • When the research was conducted

The intent signal doesn’t identify anonymous visitors at the “person” level, but surfaces account-level activity, meaning there are no blurred lines with personal data. 

How Intent Data Can Turn David Into Goliath

One of the great benefits of intent data is the power it has to level the playing field for small businesses.

A small or medium-sized business may have a smaller potential customer base than an enterprise-sized business, as well as a smaller revenue team to go after that base.

Smaller companies should look for data-backed solutions — especially those powered by AI — to target revenue opportunities and achieve their goals.

With an account intelligence platform, the size of the team matters less. Reps can set relevant keywords and receive alerts when a buyer within a target account is actively researching a service your company can provide, allowing SMB teams to focus their outreach.

When you know what your buyers are looking for, it’s much easier to reach out to them — through marketing or direct outreach — with content and offers that are useful and likely to lead to deals.

We’ve mentioned AI a couple of times as being key to intent data.

Here at 6sense, our customers use Intent Scores, a 1 to 100 measure of an account’s readiness to buy. This dynamic number is the culmination of the way multiple members of an account consume and interact with your content and team. For most of our users, this data point serves as the north star guiding their marketing strategy and decisions.

The intent score maps directly with the 6sense platform’s pre-defined buying stages:

Target Stage — For scores less than 20

Awareness Stage — For scores between 20 and 49

Consideration Stage — For scores between 50 and 69

Decision Stage — For scores between 70 and 84

Purchase Stage — For scores 85 and greater

What Makes It Special?

Different account management and marketing automation platforms offer their unique take on lead scoring, but these scores often have two big drawbacks:

Industry Scoring Problem 1: Arbitrary Metrics

Standard platforms require revenue teams to input rules and points according to their best guesses for which actions might be most consequential to a purchase.

The scores prove faulty because the arithmetic was designed by biased, limited humans and based on moment-in-time assumptions that are no longer accurate — or were never accurate in the first place.

Now With AI Power

To create our 6sense Intent Score, we use AI and machine learning to constantly track which transactions and interactions matter most to opportunities as they progress down the funnel. The technology does the hard, never-ending work, calibrating to changes 24/7, eliminating the prospect of human error — and exposing ripe opportunities.

Industry Scoring Problem 2: Anonymity

Most platforms can only score known leads, which means that the throngs of prospects who anonymously consume your content don’t factor into the equation. 

Unmasking Intent Data

6sense’s special ability to expose anonymous intent data fuels the Intent Score. By matching traffic and keywords from unique sources like IP addresses and device IDs to relevant accounts, it draws from a larger reservoir of information to suggest when and how an account is moving closer to a buying decision.

With AI and intent data, there’s no reason for guesswork. Weak numbers can be replaced with dynamic algorithms that constantly process massive datasets and learn based on what matters most to revenue teams: how deals are won. 

Chapter 6

Why Sales Teams Love Intent Data

Intent data can revolutionize the buying cycle and the work of your entire revenue team, with special benefits for your sales reps. Knowing which accounts are in-market and precisely what they are looking for can:

  • Shorten sales cycles
  • Deliver wins
  • Prevent churn, and
  • Offer opportunities for increasing deal value

Let’s take a closer look.

No More Wasted Time

Ernest Owusu, senior director of sales development at 6sense, recently described the experience of coming back from an important trade show at a previous job and being tasked with reaching out to prospects. “We’d get this list of 10, 15, 20,000 people, and were basically told to ‘smile and dial,’” he said.

Understandably, the SDR and BDR teams had to be “bribed with pizza parties” to tackle this monumental task. Without a sense of which of those accounts were in-market for that company’s solution, the representatives faced an exhausting and lengthy grind of rejections and dead ends.

“Within that trade show, there were certain companies that were actually ready to buy our product, and there were certain companies that were not ready to buy our product,” Owusu said. But we treated them very much the same. And the reality is, that’s extremely inefficient.

For too long, that inefficiency was an inevitable part of the sales process. But intent data changes all that, lifting the load of inefficiency and rejection from the sales team.

With intent data, a list of 20,000 leads can be narrowed to match the in-market ideal customer profile, allowing sales reps to target accounts that are ready to buy and interested in hearing from them.

The Right Message at the Right Time

Intent data doesn’t obviate the need for the revenue team’s role in preparing accounts for future pipeline opportunities. Instead, it lays out a much clearer cadence of which accounts are ready for which message at which time.

Knowing where accounts are in the sales funnel and buying stages allows teams to craft and deliver the right message for each revenue moment.

Delivering Quick Wins

“Just because businesses are doing research doesn’t mean they have a propensity to buy anything anytime soon,” Bombora’s Matlick explains.

Given the size of today’s buying committees, sales cycles can be slow. But with intent data allowing marketing and sales insight into the buyer’s journey early on, marketing can warm those leads with personalized experiences and just-in-time content based on the account’s actions.

That means when sales steps in, the account is both ready to buy and well-informed, giving sales the opportunity to claim the win quickly and effectively.

Keeping an Eye on Current Customers

Sales benefits from intent data even after the deal is closed by being able to monitor customer activity. This can help:

  • Prevent churn, by noticing when current customers may be researching competitor solutions
  • Upsell, by understanding when current customers may be looking for solutions your company can offer
  • Cross-sell, by identifying when another location or department in the company is researching for a solution your company provides to another location or department

As one SDR recently told us: Lead follow-up used to be a nightmare — mostly because every lead looked the same.

A list of hundreds of names can be overwhelming: Where do I start? Who should I call first? What is each person interested in? Are they going to be annoyed by my outreach?

I had no idea of who was actually ready to buy and who was just window shopping, so it’s no wonder my script got me so many hang-ups and “not interested” responses.

…and then came Intent data.

Learn more about her experience.

Zendesk, a SaaS company offering customer service software, needed a way to focus its attention on the accounts that would be most receptive to their outreach — and they needed an account-level view as they moved upmarket.

They found their solution in 6sense, which helped spot in-market accounts and their buying stages. BDRs could then focus their attention on high-intent accounts in the Decision or Purchase stages, dramatically increasing the efficiency of their outreach and their ability to close deals and book revenue.

This data also helped Zendesk see which keywords its prospects were searching for and what websites they were visiting. Zendesk’s revenue team used this information to personalize messaging and reach out at the right time. That targeting resonated with potential customers, accelerating the sales process.

With the help of 6sense’s insights, Zendesk gained traction with accounts they had tried to get into for years. Additionally, lighting up the company’s Dark Funnel™ exposed accounts that it never would have considered, giving the company opportunities to engage with customers that previously didn’t show up on their radar.

Because of using 6sense, Zendesk has seen a 10% average increase in opportunity creation globally. 

Chapter 7

Meet Your Next-Gen Metrics

What metrics are your team using to measure success?

If you’re like most companies, you’re focusing on the old reliable standards like MQLs and impressions. And as we mentioned before, aggregate, big-picture statistics like that can be useful … to a point.

However, adding intent data into the mix opens up new ways to look at returns and successes.

Swap your outdated metrics for these more useful — and actionable — upgrades made possible by intent data:

Impressions → Reach

Impressions track how many times an ad or social media post was displayed. But it doesn’t mean it was seen, or if it was seen by the right person at a company within your ideal customer profile (ICP).

Instead, measure reach: the number of unique people in your target audience who are exposed to your campaigns.

Click-Through Rate → View-Through Rate

Click-through rates tell you just that: the percentage of people who saw your ad and clicked on it. What can you do with this information? Not a whole lot.

You’re missing a bunch of other critical details, like:

  • Why they clicked
  • Their other activities online
  • Whether they’re part of the buying team

In fact, this person could be someone totally out of your target audience simply looking for more information about a certain topic. On the other hand, there may be buyers from your target accounts who view the ad but never click on it.

Click-through rates actually bring up more questions than answers.

View-through rates take this engagement a layer deeper, providing insight into how a particular ad or piece of content influences people to take further action. A view-through rate measures how many people convert on your website after viewing an ad, but not necessarily clicking on it.

When you pair view-through information with de-anonymized intent data, you get a detailed picture of how your advertising efforts are influencing the buying journey of target accounts.

Cost Per Click → Cost Per Result

Clicks don’t indicate a person is ready to buy from you, which makes cost per click also a rather arbitrary measurement of success.

A low cost per click may look great on paper, but what does it mean for business outcomes? Did those clicks lead to revenue, or at least deep engagement from target accounts? If the answer is “no,” or “I don’t know,” this value is virtually meaningless.

Cost per result is more specific and flexible, as you can determine the desired “result,” or outcome — which could be activities like:

  • Researching a keyword the contact was targeted with
  • Visiting your website
  • Consuming website content related to a keyword
  • Booking a demo
  • And more

This enables your marketing to be more strategic by allocating resources and budget toward specific actions.

Clicks → Number of Accounts Engaged

Not all clicks are created equal. Some are unintentional. Some come from wildly unqualified leads. And some come from click farms devoted to defrauding advertisers.

Instead of counting clicks, look at engagement. After accounts see your campaigns, how many begin doing research?

Measuring account engagement relies on buyer intent data that can be tied to specific accounts. A complete intent data platform can also track how accounts interact with your various campaigns, your website content, and third-party content.

This enables you to spot when account behavior shifts, and tie together the factors that influenced the buying journey.

MQLs → In-Market Accounts

Marketing-qualified leads, or MQLs, refer to people who have engaged with marketing content and are considered ready to be engaged by sales. The definition of an MQL differs from one organization to the next, and what qualifies someone as an MQL is usually based on hunches rather than data.

The truth is, people engage with content for a number of reasons, like:

  • Looking for statistics
  • Doing preliminary research
  • Trying to contact a company about something irrelevant to sales

So, just because someone downloaded an ebook or clicked on an ad doesn’t mean you should start blasting them with follow-up emails or phone calls.

Whereas MQLs focus on the actions of a single person, measuring at an account level enables you to strategically engage multiple members of the buying team to move a deal forward.

Pipeline Attribution → Conversion of Accounts to Pipeline and Revenue

Digital marketers strive to attribute leads to specific marketing channels. But today’s B2B buying cycles can take months and involve dozens of touchpoints. Trying to attribute a contact to a single marketing channel can be a fool’s errand — and a giant waste of your time.

By understanding how your campaigns are influencing customers throughout their buying journey, you can see which campaigns are nudging them forward along the path toward revenue.

This allows you to maintain a broader picture of which efforts are and aren’t working, rather than attributing most of the success to just the first or final touchpoint.

Page Views → Relevant Content Consumed

Just because a person visits a page on your website doesn’t mean they’re ready to buy — or even hear — from you. They might be starting their research, plan to use information on your site for something else, or simply feeding curiosity.

Without understanding what other activities they’re doing online, it’s not fair to make assumptions and start bombarding them with outreach.

So, look at relevant content consumed instead. Perhaps the buyer viewed a page on your website related to a specific product, then performed a keyword search related to that product, and browsed competitor products.

These behaviors suggest more than a passing interest and tell you that this buyer may be ready for a deeper conversation.

Contacts Reached → Buying Team Engagement

Besides a contact’s email, name, and location, what do you know about them? Do they work for a company on your target account list, or are they a poor fit for your offerings. Are they a key decision maker on the buying team, or an intern?

Account intelligence tools provide clues that uncover buyer personas and help you identify contacts.

Once you know that a target account has a buying persona engaged, you can quickly purchase contact information for other buying team members, then target each person with hyper-relevant content for their role.

Number of Leads Processed → Account Velocity Through Buying Stages

Rather than counting leads, count accounts and watch how closely in-market accounts progress through buying stages. Account velocity is an indicator of pipeline health, and measures how quickly you convert opportunities into revenue.

If moving accounts through the sales process is a slog, and getting them from one stage to the next requires much effort, you may not be finding the right buyers for your solution. Or, it could mean there are steps in the process that are inefficient and leave buyers looking for other solutions.

Faster velocity through the buying journey lets you know that you are delivering a valuable customer experience for accounts that are considering buying from you. The more value you can provide accounts at every stage, the more you’ll win.

Chapter 8


For too long, sellers have been in the dark about the research their buyers are conducting. This has led to annoying forms and bothersome cold calls.

It’s time to exit the Dark Ages and start capturing all of that intent data to give your buyers the experience they deserve — and using it to think differently and boost your company’s revenue.

This is the power of B2B-focused intent data and artificial intelligence. Your team no longer has to make educated guesses. They can instead rely on data, and can confidently allocate resources — time and money — to drive results.

Ready to see 6sense in action?

The 6sense Team

The 6sense Team