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The Evolution of Sales Data - From Verified Database to Intent Data as a Service

Aug 29, 2019 | Author Ed Marsh

TL;DR - Contact-level intent data has changed prospecting, marketing, selling and retaining. Actually, it’s changed what’s possible. Actual operational practices haven’t caught up. It’s tough to implement, so for some companies, a full range of services under an intent data-as-a-service or Intent Data-as-a-Service umbrella might be a practical way to drive results from intent data without internal turmoil.

What is Intent Data-as-a-Service and Why Should You Care?

Remember three years ago when finding sales contacts meant prospecting with a directory or database? Enterprise tech salespeople used to consider access to Rain King as important as their full sales tech stack. And today that seems pretty vanilla.

Sure, companies still buy lists (not sure why...but they do) and DiscoverOrg, ZoomInfo and other databases still command hefty subscription fees.

Flexible tools like LinkedIn Sales Navigator and Seamless.ai fill in gaps and provide prospecting intelligence.

And of course, in the meantime, intent data has really started to come of age.

While the data has fundamentally changed from static databases to real-time insight into who’s active, the playbooks haven’t. Too often sales teams take intent data and work it as though it is a list of contacts from their favorite database tool. And too often, therefore, the results aren’t unlike what they get from hammering on their traditional lists.

It’s time to update the playbooks and sales approaches to reflect the changes in data.

The problem is, of course, that there’s a lot of inertia to overcome and there are data analysis and manipulation requirements that don’t fit easily into traditional marketing or sales buckets.

That’s why intent data-as-a-service is emerging. It’s the solution to help companies manage intent data for efficient and optimized activation.

Large Signal Volume

A properly configured Contact-Level™ Intent Data algorithm will generate a large volume of signal — sometimes thousands of leads per day. Data based on bidstream is sometimes sold based on even higher levels of signal (although accuracy is often suspect).

Some of that is specific interaction with competitors and bottom-of-the-funnel content. Some are noise — for instance, a salesperson hoping to sell their products or services to one of your competitors. Some are simply people staying current in their field. There may be vague or irrelevant social signals and casually related event attendance data.

Much of this is understandably irrelevant to AEs and even BDRs as discrete signals. And companies using marketing automation platforms with contact count billing components are understandably hesitant to import all leads indiscriminately.

When marketing and sales are already “over meetinged” and buried under email and task lists — yet pressured with KPIs — there’s not a lot of time for thoughtful contemplation of daily lists.

Therefore, the first challenge is how to continuously filter for the important signals and prioritize leads for nurturing and outbound sales (or even attention from AEs and the success team).

Intersecting Engagement

Often the critical sales opportunities are identified at the intersection of multiple signals. The fifth engagement over the past month by a single contact might be the indicator of qualification. The third individual from an account taking action might represent critical mass indicative of an organizational focus and project.

Active opportunities in the CRM and first-party intent signals like site visits, intersecting with third-party data, provide valuable clues.

And even complimentary third-party data sets can reveal important signals where they overlap. Sales channel prospect lists, for example, could be monitored for intersections with first-party and third-party data to create value for channel partners and prospects.

Tracking all of this creates challenges. Aside from contact count and cost, there’s noise…until it’s not noise. But when it’s not noise, it’s unfortunately likely that nobody’s watching closely to detect the change.

Of course, you can absolutely do this using spreadsheets and pivot tables. It takes time and is mind-numbing work, but it’s entirely possible to process lots of signals to find what’s important and forward it to the right person.

Possible isn’t the same as practical, however.

Building Playbooks and Workflows

Let’s put aside the contact cost question for a moment. It’s certainly possible to build rules, workflows and sequences in many CRM and marketing automation systems to provide filtering and alerts.

But what should the rules be? What’s an intent data qualified lead? When does an IDQL move from marketing to sales?

Often these are entirely new questions that raise additional questions as the proverbial onion is peeled, and implementation is often shortchanged as a result.

Data is imported, outbound sequences implemented, but the hard and important work of really activating the data for each use case is never fully undertaken.

Elusive Intent Data Activation

As a result, the program never realizes full traction. The value of the data isn’t unlocked and often it's not used across the entire customer lifecycle.

There are companies that manage this entire implementation exquisitely. At the recent B2B Sales & Marketing Exchange, Paul Green, director of marketing technologies at Extreme Networks (@PaulsGreen222) shared his Project Orion experience. Amanda Bohne, VP of marketing at AppNetta (@AmandaBohne) joined John Steinert (@TechTargetCMO) to tell a wonderful story of data integration and marketing and sales alignment.

But those successes are rare and require strong visionary leadership with dedicated resources and a willingness to experiment.

That’s why more companies are opting to have others activate the data for them. Opted-in leads, scheduled meetings, and even event registrations are among the typical goals. Intent data is a powerful tool to inform the paid ads, content syndication, email nurturing and omnichannel outbound sales approaches that drive these KPIs.

Intent data-as-a-service pulls all of these components together for companies that see the opportunity but would rather let someone else manage the mechanics.

One risk is that important intersections are missed — contact-level intent data signals from current customers, contacts involved in open opportunities, and coincidental first- and third-party intent data signals could easily be overlooked even when there’s an effective and robust program for data activation.

We’d love to tell you how we solve that. If you’re interested, contact us or just chat in.

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