Intent Signals are 2016’s hot topic in business-to-business marketing circles because new technologies can now monitor the digital actions of groups of individuals across the internet to gain an understanding of their company’s purchase intentions. We’re getting immediate insights as companies take their very first steps in the buying journey – it’s a new and very exciting form of intelligence.
My experience with current intent signals data is that it’s used when a prospect is researching a topic – typically a problem they need solved – showing us what is important to their organization. For marketers like me, turning this behavior into guidance for marketing takes a historical understanding of the habit and its roots in consumer activities.
Where Behavioral Data Starts
Historically, we’ve seen behavioral data focus on individuals, even in B2B. We focused on determining what some refer to as each individual’s "digital body language," hoping to interpret the interest level and purchase intent of each individual prospect and extrapolating to the greatest extent possible regarding the corporate purchase situation.
The History of Intent Signals
We’ve seen digital behavioral data evolve from early touch points like email opens and clicks to Google AdWords clickthroughs and then to monitoring visits of pages on our own website. Marketing automation platforms such as Oracle Eloqua, Marketo, and others provide this as standard functionality today.
This is extremely useful information, but it is limited to monitoring of our own interactions with each prospect individual – clicks on our own Google Ads, downloads of our own white papers, visits to our own website.
Several years ago, I saw Business-to-Consumer (B2C) marketers began to find ways to monitor visits by individuals (browsing from home) to websites other than their own. I watched with great interest as B2C marketers gained the ability to recognize when someone in a given household was visiting more web pages related to a certain product type than they typically do, indicating heightened interest in a product.
For example, let's say a I’m running a company who sells canoes - intent signals allow me to see increases in visits to web pages about canoes, serving as a trigger for automated email campaigns or other outreach.
It is only in the past year that we’ve seen this capability made meaningfully available to those of us in B2B marketing, and it is proving to be a revelation.
The B2B Side of Intent
We B2B marketers have long tailored marketing and sales outreach based on personas and job titles, but now we have the capability to adjust marketing based on identification of surges in interest in whatever it is we sell (cloud storage solutions, for example) among individuals at corporate, rather than residential, IP addresses.
When we pair this IP and intent signal data from third-party reviews and sites, I see businesses able to dynamically target prospects based on the type of information the prospect is viewing, indicating the most likely position in the buyer’s journey.
The Intent Future Is Account-Based
Prospects are leaving clearer data trails than ever before, and our ability to collect this intent data at scale is currently changing the B2B landscape. I see these improvements in the capability to both monitor and interpret intent data at scale – meaning we can look at intent from organizations as a whole – as major drivers in the current boom in interest in account-based marketing.
We’re starting to see intent data as an indicator of where an account is in terms of their buying journey, which is crucial to us in deciding on the appropriate next action. There will be situations, especially for practitioners of ABM strategies, in which the appropriate outreach is not a marketing campaign but rather a direct sales call.
Seamless, Actionable Data
We already see that intent signals can effectively be used to automatically trigger campaigns for the potential purchaser immediately, when the prospect is most likely to engage. We already know timely and automatic engagement is vital to marketing and sales efforts.
Next, I hope that intent signal intelligence will be combined with other ABM inputs to add weight based on each individual’s role within a prospect company – this added context will help marketers understand the appropriate form of outreach for each of the relevant prospect individuals at companies with surging interest.
The net result can be surprising to some – by better understanding when a given organization is considering a purchase, B2B marketers can refine their efforts and actually reduce their outreach - less email, fewer unwanted phone calls, less background noise in the market.
Intent Signals intelligence is a win/win, as it allows marketers to provide their prospects with what they want, when they want it. The goal is valet-level service and an end to interruption marketing, and Intent Signals data is the most meaningful step in this direction in more than a decade.
(About the author: Brian Giese is a founder of True Influence, a leader in Software-as-a-Service business intelligence and demand generation services for marketers.)
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