Growing Your B2B Pipeline Starts with Good, Robust, and Actionable Data

With the digitization of everything, the imprints of our interactions are everywhere and can be consumed and analyzed by any org or business that crosses our path. But even with the proliferation of all these signals, marketing and sales ops teams still struggle to effectively wrangle them and put them to work efficiently in go-to-market motions on a consistent, day-in, day-out basis.

The question of why this is still such a struggle for sales, marketing and revenue ops teams and what the best data-forward organizations are doing to solve it was the subject of a recent panel discussion held by the data-obsessed executives at Openprise and SalesIntel. In addition to redefining the challenge of “operationalizing data” in a way anyone can understand, the speakers shared the five best practices for making data consistently ‘good’ and ‘usable’ that they deploy at their own organizations.

Make it good. Make it yours. Make is usable.

Not all that long ago, the job of working with data was the responsibility of a select few technical specialists in the organization or outside consults. But even though data work is now more democratized, we still don’t have a common way of describing our challenges with it. As a way forward, Ed King, CEO and founder of Openprise, proposed the framework of “making data operational”, which he further reduced to the simple rubric of “making it [data] good, making it yours, and making it usable.”

For Ed, the framework is really just a simplification of the good basic data practices that every organization should follow. It starts at the bottom, with the foundation of data governance and the processes to clean, de-dupe, verify, and otherwise ensure data quality, which make it ‘good.’ The next layer is making it ‘yours’ or bringing in the first- and third-party data to enrich and add the proper business context. At the top is making it ‘usable,’ which involves providing access and the structure to deploy it.

The other panelist, James Lamberti, CMO of SalesIntel concurred. But for James, the sequence is as important as each of the steps themselves. Speaking from experience, he said, “people often land right away on making it usable, skipping over making it good and making it yours, and so the foundation isn’t properly set.”

Data define your addressable market

For both Ed and James, the framework isn’t just a construct they use to explain abstract concepts or hypotheticals, it’s a tool they deploy every day. The two illustrated this in the first best practice, data defining your addressable market, which can’t be completed without the ‘make your data good, yours, and usable’ rubric.

Every business has a total addressable market (or TAM) and a truly relevant market (TRM). The former is generally easy to determine based on publicly available information, but the latter is far more difficult and typically is the thing that separates a market leader from its competition. TRM is about being efficient and giving your team the targets and tools to be successful, and it starts with having good clean, up-to-date, and accurate data on all your TAM accounts and contacts. From there, you can use first- and third-party data, such as metadata, firmographic and technographic information, to whittle down your accounts, contacts, and leads to the TRM that best fits your ideal customer profile (ICP).

ABX your B2B pipeline generation

Whether inbound or outbound, James and Ed are big proponents of account based experience or ABX strategies and tactics that combine the data-driven engagement of marketing motions with the laser focus and targeting of ABM. For both, ABX motions are all about intent, or as James says, “it’s about adding intent data to expand your ability to reach a particular target and make your sales and marketing motions orders of magnitude more efficient.” For Ed, ABX also has to consider the buyer’s journey and “be very focused, very targeted, and include hunting-like tactics.” But even more importantly, the data needs to be operational, or easily consumable. The account hierarchy, for example, has to match the go-to-market strategy. Agility and the ability to self-serve are also key. Marketing, for example, needs to be able to run a campaign using difficult-to-acquire data, such as cell phone records, without IT or ops intervention. And sales should be able to do a data exploration without wondering if the contact’s history is correct.

Maintain good data hygiene

Sustaining good hygiene, for both James and Ed, is the most difficult part of the whole puzzle. As Ed noted, “it’s still shocking how many people think this is just a one-time thing. Data deteriorates at a rate of 25% per year, so maintaining good data hygiene is a continuous effort.” Contacts, especially in marketing, frequently move jobs. Companies change their technology almost as frequently. At SalesIntel, they have 2000 on-demand researchers to support the management of its data quality, but, of course, that isn’t scalable for most companies. For Ed, maintaining data quality has to involve some kind of process automation, but he conceded it’s not just the job of machines and needs the cross-functional involvement of multiple people throughout the organization. The orgs that succeed eventually find their sweet spot somewhere in the middle between distributed and centralized access, with AI doing the heavy lifting and human control delegated to a few individuals across the respective teams.

Movers data matters

The importance of being able to track contacts as they move and especially those that know, champion and love your brand or solution cannot be overstated. This typically involves multiple moving parts, but at its root, you need to be able to detect the move signal immediately, check the contact’s new information against what you have for them in your CRM, create a new record if need be, AND make sure that their historical connection to your company is retained. That’s just the table stakes. What’s absolutely critical is being able just as quickly to deploy a sales or marketing motion using this new information. This is where the importance of real-time, on-demand research capability comes in. To Ed, “True data operationalization in this case means finding where the contact moved and notifying the new account owner, so they can take immediate action.”

Align around the demand center

In simplest terms, this means getting the entire organization, from marketing and sales to revops, all aligned around the motions that are working best and most efficiently. Or as James put it, “this is about being efficient as a team. If marketing’s getting efficient inbound, great, spend more money on marketing. If you’re doing better with ABM, then do that.” On the operation side, Ed sees a growing role for revops as the independent arbiter and trusted reporter for the C-suite. For him, “a big part of operationalizing your data is that you actually now have the ability to measure how you’re doing and get the feedback loop going,” but that’s only possible if you’ve done the work to put the good data and structures in place.

Getting started

For those interested in learning more about your B2B pipeline and how to operationalize your B2B sales data and begin to put in place the best practices summarized in this post, James and Ed’s talk is now available on demand.