TL;DR: B2B Intent data is often associated with demand generation. That’s a huge use case, and fully optimizing the capabilities requires the ability to segment different types of leads for different treatment for effective activation. Data sources which support that can then offer substantial value through enterprise-wide orchestration among departments. It starts with contextual data and the ability to (or not) integrate into CRM.
Right Follow Up...Or Not
The premise of intent data is to understand who’s an active prospect and potential buyer and to have enough granular context and situational information to help deliver the right message at the right time to the right person.
But that message has to be delivered — in the right way, or combination of ways. That could include custom audience remarketing, account-based marketing or good old-fashioned outbound sales cadences. Maybe some leads shouldn’t be followed up on, while other signals should be noted/logged for awareness, but don’t merit direct action.
This is common sense, but it’s challenging to implement with many B2B intent data sources.
High volumes of potentially inaccurate information from bidstream data, account-level only signals and “topic-” based data that lacks granular context all complicate or preclude segmentation and tailored follow up.
Often the marketing message that is served up is muddy and broadcast to anyone who might be the right person. It’s not delivered effectively.
Joanna Bittle (@Comm_Creative) discussed the role of nuanced B2B intent data in the targeting of customized display creative in her contribution to the recent DemandGen Report “What’s Working in B2B Advertising.” Unlocking the value of intent data requires thoughtful analysis and specific action.
Detailed, Nuanced Data for Effective Segmentation & Activation
If you heard that some unknown person in one of your target accounts took action with content surrounding a problem your product solves, would you promptly adjust your pipeline to increase the likelihood of close? Or if you heard that some anonymous individual in a customer account interacted with a competitor, would you freak out?
Of course not. In both cases, the situation could be anywhere from completely innocuous to a crisis situation. Depending on job title, number of signals, number of people involved, details of their interaction and more, you’d quickly draw some conclusions.
If it’s the key decision-maker in the buying process undertaking deliberate and extensive research, you’ll react differently than if it’s a low-level employee burning time on unrelated tweets.
Making the required judgment call requires context and the ability to see the related data points in a consolidated view to support analysis.
Unfortunately, most intent data doesn’t deliver. If you only have a topic, behind which lies an opaque taxonomy, you can’t know the detail of the engagement. If you don’t have the actual person’s job title and details, you can’t gauge the import of their actions.
Optimizing the ROI of your B2B intent data requires segmenting it to deliver the right message in the right way.
CRM/Marketing Automation Integration May Not Be Enough
Behavioral intent data activation conversations normally start with discussions of integrating data with CRM and marketing automation platforms. That accelerates the delivery of critical signals to marketing, sales and success team members and reduces the work for the demand gen team that normally coordinates the data.
Workflows and alerts can be created for basic categories including current customers, target accounts and pending deals. But that might not be enough.
For instance, how will you manage audiences for remarketing? To be effective you’ll probably construct different audiences for remarketing by platform (Twitter, Facebook, Google, LinkedIn), by competitor engagement, by job function/title and by problem/outcome focus.
How will you aggregate data for a robust competitive marketing analysis? And how will you filter high priority leads (by stage in buying journey and specific engagement details overlayed on demographic and firmographic details)?
I’ll give you a hint: Once the data is imported into the CRM, it’s lost and forgotten. If it happened to trigger an alert or appeared on someone’s dashboard, it might have resulted in action.
Otherwise, it’s now simply crud in the database — and likely expensive crud since most marketing automation systems exact an insignificant carry cost based on contact counts.
The bottom line is simple: In order to optimize the value of B2B intent data, you have to be able to carve it up into various streams. Some will drive immediate action in your CRM. Some will augment your ABM in your marketing automation. Some will support remarketing. Most will yield high-level insights. And, frankly, some will be noise.
Pushing it all into your CRM will miss critical use cases.
Collaboration for Effective Intent Data Orchestration
At the heart of this question is one of the biggest challenges, and naturally perhaps the corresponding biggest opportunity for intent data implementations.
Each function and each department (e.g. demand gen, ABM, remarketing, and competitive within marketing, sales, success) will have to execute different activation plans. Each of those might involve a different data stream or streams.
But what about the broader organization? What about orchestrating the use of B2B intent data across departments? In other words, not only optimizing it for all marketing functions but also explicitly incorporating it into target account sales, complex sales and pending deals for intelligence. And delivering key insights to success teams to reduce churn and improve and cross-sell opportunities.
Typically one department, even one functional director (often the director of demand generation or ABM) makes the buyer intent data procurement decision. The data model and detail are based on their specific needs and understanding of available options.
What if there was a way for all departments and functions to participate? That means that the right intent data could legitimately replace lots of other costly, underperforming data and lead gen resources with a single source. The resulting savings and efficiencies could be shifted to experiment with other approaches that hadn’t been feasible.
Other department heads and functional leaders might not see the value upfront, but an important byproduct of flexible, multi-stream and format delivery, is the ability to deliver huge value for each group as they discover the potential and ask for more.
The bottom line is that intent data may actually hold the key to the Holy Grail of sales and marketing alignment.
