In B2B marketing and advertising, goals are all about identifying the right audience, the right time to engage them, and the right approach to the engagement.
Identifying the right audience is a staggering task unto itself, but intent analysis has evolved and, when executed intelligently, is now a reliable approach to capturing and synthesizing the purchase intent signals emitted by prospective accounts while researching solutions to their organizational pain points.
It’s the targeting and identifying of specific, key decision makers within those flagged accounts that proves as difficult as it is necessary to close on them. With the right data sources, job titles can be mapped from within data sets, but a verified job title does not guarantee a win.
Job titles at B2B organizations are becoming more disparate and meaningless (rather, open to interpretation) every day. For example, the IT Director at a small shop means something very different than an IT Director at an enterprise, just as a Product Manager at a small shop may have different responsibilities and levels of input in business decision making than a Product Manager of an enterprise’s global division.
Unless your target accounts share one work computer, targeting advertisements at the wrong audience within a target account you’ve been trying to convert might be as wasteful as it is demoralizing and pointless.
Segments of Which Audiences?
In a blog post on Demandbase.com, Matt Aaronson explores targeting the right prospects within target accounts in B2B advertising.
In account-based advertising, he says, “if you’re not reaching the key decision makers within your target accounts, your ad dollars might as well be flying out a window.”
Typical segmentation of identity-based audiences captures information about job title, job function, department, seniority, and company, but given the disparate nature of job titles, how actionable are the insights contained within any given set of this information?
To avoid hinging your account-based advertising success on data that might not be the accurate identity-based B2B audiences a data provider promises, Aaronson says, ask any potential intent data providers if their segments are deterministic, modeled, or mixed; where their deterministic data sets come from; and what their methodology for modeled data is.
If you can determine the provider has qualified data, and you’ve developed an intelligent strategy for using that data, you can trust that your investment won’t be for naught.
Each of these questions will help you to vet any providers you may be considering. The provider’s answers are crucial to the efficacy and level of “actionability” in their insights.
For example, deterministic segments use identity data provided by users in registration forms, and modeled / probabilistic segments predict job titles based on anonymized user data and characteristics. Don’t run free with the assumption that deterministic data is always sourced from a co-operative network of B2B publishers, however; prospective providers should always tell you what their data sources are.
According to Aaronson, deterministic segments are more reliable than modeled — but they’re so huge that data providers will usually supplement them with modeled data to expand the audience. Again, it is key to ask a prospective provider where their modeled data is sourced from. Additionally, the provider should be willing to explain which signals are used to map cookies to job titles.
Intent Targeted Ads
Job titles alone are not adequate to verify an audience’s identity, and they are not enough of a green light to score a lead based on a verified job title. Context is required for the data to be actionable and drive value.
As Aaronson says, failing to reach the relevant decision-making audience with a targeted ad (or any marketing efforts that use budget) is akin to pouring your advertising allocation out a window.
Aberdeen offers Intent Targeted Ads programs designed to deliver an optimized return on your digital advertising investment, rather than losing your marketing / ad spend.
Because Aberdeen’s massive intent data sets are qualified, verified, and up to 91% accurate in tests, any engagement in an Intent Targeted Ads program is with a qualified prospect at the moment they are conducting active research. This increased relevancy leads to increases in click-through and view-through rates of 200% and more.
Using verified, qualified data for account based advertising is an option that Marketing and Sales functions don’t have to choose for their operations, but knowing the alternative should make this choice an easy one.
Do you know which specific companies are currently in-market to buy your product?
Wouldn’t it be easier to sell to them if you already knew who they were, what they thought of you, and what they thought of your competitors?
Good news – It is now possible to know this, with up to 91% accuracy. Check out Aberdeen’s comprehensive report Demystifying B2B Purchase Intent Data to learn more.