I’ve spent the last 25 years in and around marketing and sales. For the past 15, my focus has been working with operations — marketing operations (MOps), sales operations (SOps), and now, revenue operations (RevOps). The department label doesn’t matter as much as this: the same problem that plagued those teams in 2008 is plaguing them today, and that’s a lack of actionable data.
Oh, the teams have data. Simply ask them or, better yet, ask the software-as-a-service (SaaS) companies that charge them monthly for the terabytes of data managed within their platforms. But do they have actionable data? Chances are, that answer is “no.”
What Is Actionable Data?
So, what the heck is “actionable data?” It’s the data that front-line marketing and sales teams need to drive revenue and deliver actionable intelligence to the business. Actionable data encompasses master data related to people and companies, but it can also include specific transactional data, industry data, product data, and more. Actionable data is:
- Validated: Contacts in databases and their critical data attributes (email address, phone number, etc.) are current and properly formatted. The companies in databases must be active companies (don’t laugh; I’ve seen contacts from long-defunct companies in active campaigns!).
- Enriched: Data is complete or contains at least “minimally acceptable attributes” (MAA). To accomplish this, work with front-line teams to determine what attributes are needed for contacts and companies to be properly segmented and reported on. Establishing MAA for your master data provides a baseline metric for measuring the quality of your data – integrality.
- Standardized: If you have worked in a customer relationship management (CRM), marketing automation platform (MAP), or enterprise resource planning (ERP) system, you know how a lack of standardization can impact operations. It can render a report useless, cause erosion of trust at the executive level, and wreak havoc on product development.
Now let’s talk about use cases and why clean, actionable data is so important.
Your GTM Strategy Depends on Clean Data
Clean data is the starting point of this journey. Data health is an important determining factor for the amount and type of actionable intelligence a company can glean from its data. The resulting actionable intelligence will be impacted if the data is dirty, incomplete, or otherwise unreliable.
Once you have clean data, you can look at an impactful marketing strategy. Such a strategy requires a customized approach. For over a decade, this has translated into “personalization.” But that’s only a tiny part of the equation. Just plopping in “Dear John” or referencing someone’s title in the body of an email isn’t going to do much to drive that click to get the recipient to “lean into” the conversation.
Surprisingly, many companies still struggle with executing this simple tactic. Determining how to send the right message at the right time requires knowledge of who the person is, where they fit into the buying committee, and where they are in the buying cycle. Those signals can only be identified if the data about that person is clean.
Imagine a scenario where you want to deliver a customized sequence to a decision-maker, but they have four unique records across your technology architecture. Here is what that may look like:
|firstname.lastname@example.org||VP of IT Services||ACME Company||United States|
|John Doeemail@example.com||Chief Technical Officer||ACME USA|
|Johnfirstname.lastname@example.org||United States of America|
This scenario raises a few questions:
- Which record is the “primary?” Is “acmeinc.com” or “acmeco.com” the proper URL?
- Are all the email addresses valid?
- Is John VP level or C-level? If C-level, was this a recent promotion? If VP, is there another senior leader who makes the decisions?
But there are also not-so-obvious challenges:
- Has John opted out of communications for any of the addresses? And if the answer is yes, does John expect that opt-out to apply to all addresses?
- What types of activities did John do to generate that many records? Would that be helpful for building more context in a message?
These can be mitigated by validating, enriching, and standardizing the records. Ideally, John Doe from ACME should have one record in the database that is delivered to all systems that may need it. That record would have four email addresses associated with it, along with all the engagement activity John has generated since he first became known.
Which companies are the most important vendors in data? Check out the Acceleration Economy Data Modernization Top 10 Shortlist.
Is Your Leadership Aligned?
Earlier this year, Scott Vaughan, a leading GTM strategist and Acceleration Economy practitioner analyst, highlighted the importance of actionable data — framed as unified data — during a conversation with Mike Weir at G2, where he discussed a unified data approach as a basis for aligning teams and creating a data-driven culture. Then, in his analysis on turning data into actionable intelligence, he highlighted two key concepts:
- Modernizing your data management standards and framework
- Adopting clear governance strategy and policies to ensure data quality
I would consider this baseline guidance from someone who has experienced the effects of both good and bad data, but what happens when your leadership is not aligned?
A significant data project failure point is a lack of alignment with the executive leadership. Even in cases when the initiative(s) are being sponsored or led by a Chief Data Officer, there are never any guarantees that the project will succeed or even get fully off the ground unless the company has a data-driven culture.
That’s why Scott’s suggestions regarding the implementation of an updated data framework and governance strategy are essential, either as an integral part of the project or as prerequisites before initiating the project.