Tl;dr - Sales pipeline management involves countless assumptions - and it's challenging as a result. Contact level™ intent data can serve as a diagnostic imaging tool to see into the buying team, infer some of the politics and priorities, and help sales and marketing adapt their tactics accordingly. That can help shorten sell cycles, boost close rates and improve forecasting accuracy.
Complex sales is hard...and getting harder. But that doesn't relieve the revenue team of the responsibility to improve sales pipeline management. Many management functions hinge on having an accurate picture of pending deals. Staffing & hiring, cash flow planning, and others depend on accurate forecasting.
Yet it's hard, complex and inconsistent - particularly for big ticket, long sell-cycle, large buying team complex deals.
There are a number of sales and marketing best practices for continuous qualification, sales enablement and account/product fit factors that help.
But many companies overlook the potential for contact level intent data to contribute as well. There are four areas where third-party intent data can help.
Let's dig into each of these.
To simply establish a sales connection for a dialog you've got to speak to an issue that you know is likely pressing for a buyer. Product marketing, market research and a Challenger Sales Approach will help to craft messages to generically speak to the market.
Contact level intent data can help you infer specifically, for each active contact at a company, what they're taking action on - possibly researching as part of a the buying process. Analyzing the key term around which they've taken action (from which you can gain insight into the problem they're trying to solve and the outcome they're trying to achieve) can also help you understand how far along they are in their buying journey and the magnitude of the "value gap" they're focused on resolving.
This can help you target the nurturing or outbound sales more specifically. It also can help to steer the conversation to more quickly confirm and quantify the magnitude of the problem to facilitate qualification. Finally it provides insight into how closely aligned (or not) the buying team may collectively be around these important questions.
Speaking of the buying team, if you're like many companies managing complex sales, you're probably coordinating communications and selling to a team of 10-15 members. They're each individuals with personal preferences and departmental priorities and biases. Some will resent spending time working on a project to buy your product/service since it won't help them personally and might consume resources which preclude their preferred projects.
In any event, you'll rarely know all of the folks involved and almost certainly won't have a chance to connect with them. Even your deal champion might not understand all the dynamics.
Intent data can help by observing the details of the activities of each of the participants who's taking reportable action. Job titles help you begin to plug them into roles that you know are likely part of the buying team, and then to identify gaps - key roles that aren't apparently active - for targeted outreach and nurturing. It also lets you observe those who are active, but might be considering alternative solutions, focused on different problems to solve, or at different stages in their buying journey (which you can often infer from keyterms which are reasonably associated with different stages in the buying journey.)
What's your sales play when your deal champion asks for a quote and agreement for review, but you know other members of the buying team are still in the consideration phase or other earlier sales pipeline stages? Or when a very process focused participant (e.g. IT or engineering) is much more deliberative and weighing more factors than the group that stands to benefit most and wants to implement quickly?
It's often hard to quantify those scenarios even if you, or your champion, sense them.
Intent data can help here as well by observing specific behavior of each participant of the buying team that's taking public action. That helps to understand them individually - and to visualize the aggregate buying journey for the full buying team.
Finally it can be very helpful to observe specific competitive engagement by members of the buying team. Are different departments focused on different vendors? Is a key role (e.g. csuite decision maker) focused on one vendor while the implementation team is more active with another? Are some members still considering vendor options even as your champion indicates the deal is essentially done?
All those are important questions and realistic scenarios. Third-party intent data let's you confirm what you're hearing from the buying team and ask appropriate questions to elicit clarifying answers when your data observations differ from what they're telling you.
Together these capabilities can help revenue growth teams adapt to chaotic complex buying journeys and improve sales pipeline management by overlaying observed intent data signals to reveal possible misunderstandings or gaps in the sales team's understandings.
That has the potential to shorten sales cycles, increase close rates and improve the forecasting reliability of sales pipeline metrics and deal stages.
If this is intriguing, then it's important to understand what data attributes are important to activate these capabilities of intent data for sales.
All of these tactics hinge on knowing WHO the person is that has taken specific action. Only by knowing the job function and seniority is it possible to assess their role on the buying team, and therefore understand whether specific action by a certain person is material to the opportunity or not.
It's not enough to know that there's been a burst of activity - even from a specific office. Today's buying teams not only work remotely, but often collaborate from different corporate locations. And many actions from one person is a different signal than a few actions from many people. It's critical to understand WHO has taken WHAT action.
It's also critical to understand the specific keyterm or competitor with which engagement has occurred. Signals which are merely associated with a "topic" built on an opaque taxonomy won't provide the important details from which one can often infer stage in buying journey, problem to solve, competitor engaged, etc.
Of course there's analysis and subjectivity involved. Data is comprised of signals - marketing and sales intelligence if you will - and can include "content intent" as well as "purchase intent." So this approach will require an open mind to understand important insights, but to avoid concocting imaginary scenarios.
Incorporating contact level intent data into a sophisticated process of sales pipeline management can improve results in creative ways.