A Simple Definition of Intent Data
Intent Data is the collection of behavioral signals that help interpret B2B purchase intent. The term is commonly used to imply observations of anonymous online activity, but intent data is much broader and has been used by B2B marketing and sales teams for years. Traditional examples include body language, event participation, phone calls, direct mail engagement and trade show activities. Contemporary examples include email engagement, social media interactions, content, competitor and thought leader engagement, online chat interactions and breadth of SaaS feature usage.
Each of these can be analyzed and interpreted to help understand where an anonymous or known prospect, or a customer is in their thinking and buying journey.
Sighs, Crossed Arms, Urgent Meetings & Smartphone Distraction
Prospects, leads, buyers and customers send signals all the time. They're leaning in, satisfied and focused, or falling away and distracted by other things. Sales people have been trained to read body language for years. The growth of business travel, even as video alternatives like Zoom have become so easy and effective, is proof positive of the importance of sending and receiving important physical signals.
Few people would invest the resources in travel for the purpose of meeting with various silhouetted, voice disguised and identity protected participants. We travel for the direct personal engagement.
Yet the anonymity of the internet has challenged marketing and sales people to understand who's doing what, where, when, with whom and with what intensity.
Account-Level Intent Data - Firmographic Data Signals
B2B companies have followed "trigger" signals for years. Contractors have watched property transactions, janitorial companies have tracked new leases, website developers follow URL registrations and board recruiters monitor changes in governance.
Account-level buyer intent signals aren't new, nor is their relevance for astute marketing and sales teams who leverage those insights to discover and solicit likely prospects. Hiring activity, key executive transitions, product launches, new office locations and liquidity events are commonly used triggers, which are filtered by geography, company size, industry, job title, etc. to focus the attention of business development resources where they're most likely to be successful.
Because they're typically published and can be easily tracked with simple free tools like Google Alerts in addition to traditional aggregators, they often attract a lot of noise.
Just try registering a new TLD and sit back and watch your inbox flood with offers.
The big change, of course, is that the internet enables anonymous research. The results are well documented:
- Identifying the 3% of potential buyers that are actually active is seemingly impossible
- 93% of B2B purchases start with internet search
- Buyers are more than 70% of the way through their buyer journeys before they're ready to speak to a sales rep
- 74% of B2B buyers ultimately select the vendor that first provided value in their research
- And at the same time, it's getting harder to sell as procurement teams have swelled to an average of 6.8 members and more projects end in no decision than ever. The status quo in busy organizations trumps the hassle and uncertainty of change.
Yet the same ubiquity of information that allows buyers to lurk in the shadows also gives effective business development teams insights. Researching prospects through professional and personal social media profiles provides important contact-level insights just as reviewing press releases and financial filings provides account-level context.
Digital Body Language, Signal Enrichment, Nuanced Insight
Many companies have gone further — implementing marketing automation, website tracking technology, email delivery and engagement tracking, online chat and related tools yields enormously valuable 1st party contact-level intent data.
Knowing who, from which companies, has engaged with your content, how recently and at what velocity powers ad hoc and automated efforts. Great sales people will review and interpret the info and tailor their outreach timing and message, and they'll respond quickly to alerts notifying them of visits to specific high-intent webpages and emails.
Great marketing, enablement and sales teams will develop workflows that adjust lead score and even prompt outreach - complete with coaching notes and suggested questions - based on the observation and interpretation of these 1st party buyer intent signals.
Sadly many companies simply accumulate the data and proceed with their traditional marketing and sales processes, squandering the value of the information they've accumulated.
The Allure of 3rd Party Intent Data
Extrapolating the power of 1st party intent data, and encouraged by the success of 2nd party intent data (identified leads of opted in subscribers from subscriber platforms), many companies have turned to 3rd party intent data with grand hopes.
If only they knew, the thinking goes, that someone was taking action anywhere on the internet which indicated intent, they'd be able contact them at the right time - when the prospects were actively researching the product or service they offer.
Great idea. After all, that's the point of a trade show or a webinar: to figure out who's active now and start a conversation.
This typically breaks down in execution for two reasons. First, account-level data doesn't approach the value of contact-level intent data that's collected 1st party. Nearly all 3rd party intent data is based on anonymous actions observed only at the account level. Often there are contacts appended which are sourced separately and happen to meet the ideal buyer profile, but these are simply convenient guesses.
Second, marketing just blasts them and hopes something falls out the bottom of the funnel.
Of course there's a "market" for it, just as there's a market for unverified lists without opt-in to blast with email.
A Simplistic Definition Yields Simplistic Implementation
Definitions from companies like Everstring (What is Intent Data?), Discover.org (What is Buyer Intent Data?), and Aberdeen (What is Intent Data?) all define intent data as online behaviors. That's shortsighted and it has implications to the use of, and results from, 3rd party intent data.
A meeting with a prospect is just as meaningful today as it was 15 years ago. (Actually one might argue more meaningful as time is scarcer.) Responding to a handwritten note, traveling to an event and concentrating throughout a 30 minute phone call also still convey critical intent and engagement insight.
To limit the scope of intent data collection, analysis and use to "online behaviors" is therefore inadequate for today's complex B2B revenue growth environment.
Best in class companies will build their algorithms and structure streams to satisfy the distinct needs of demand generation, account based marketing (ABM), target account sales, pending opportunities, complex sales, and customer success. That requires weaving together offline and online intent data sources. It requires contact-level insight (vs. account-level signal with arbitrarily associated contacts.) And it demands cross functional collaboration to facilitate hand-offs, build effective automation and playbooks to help each contributor maximize the value of information for their function.
Intent Data Activation: Effective and Responsible Use
Intent data, like most digital tools, has the potential for abuse. Marketers who simply dump masses of data into a nurturing engine will bombard everyone on a list (often based on the opaque criteria and taxonomy of "topics") with the same irrelevant message.
Yet that's the common outcome. Most intent data is sold based on easy to buy and easy to implement propositions, and locked in for extended subscription contracts.
The solution is robust activation of intent data. That's the process of thoughtfully engineering a robust algorithm; planning for the right tempo and method of delivery for different categories of data; working with stakeholders to deliver the insights they need to help achieve their KPIs; collaborating on the creation of playbooks, workflows, and automation to leverage the contact level insights at scale; and measurement and adaptation.
The outcome of rigorous intent data activation is responsible use that truly enables companies to help prospects. That in turn drives down CPL & CAC, reduces churn and boosts CLTV.
Along the way companies realize a welcome byproduct too. Properly activated 3rd party intent data fosters real marketing and sales alignment.