Kelly Owen Grover is the Vice President of Marketing for Cloverly, a technology platform for high-quality carbon credits.
getty
When you hear successful GTM (go to market) leaders exalting their triumphs at a conference or sharing best practices on a podcast, they are almost always sharing the highly visible, super-sexy stories: a shiny rebrand, exploiting a ripe market opportunity or implementing a new GTM strategy like ABM (account-based marketing) or PLG (product-led growth). To be clear, these are incredibly powerful and indeed very sexy strategic ventures. However, career-making activities like the above can steal the stage from key foundational work that is often orphaned, overlooked or ignored. A robust data governance plan can be the antidote to this all-too-common corporate ailment.
What Is Data Governance?
For the purposes of this article, we can define data governance as a shared definition of all terms, processes and metrics that are consistent across teams, documents and systems. This article is the first of a two-part series focusing first on the necessary inputs and then on the process. The data discussed is that of the core GTM teams: sales, marketing, product and customer service. These metrics will bridge the performance of the various levels of the GTM funnel (leads, opportunities, closed/won business, expansion, etc.) with that performance’s contribution and ROI to the organization’s objectives (customer acquisition cost, or CAC; lifetime value, or LTV; and so on).
The Basic Inputs
1. A common language: Even basic communication requires the participants to understand the words the other person is saying. Strategic GTM planning is no different. However, all too often there is no set definition for the most common and fundamental terms, and thus, teams unknowingly speak past each other. The quintessential example of this is the word “lead.” Ask any GTM team members how they define a lead and, often, you can get disparate answers. Consider one of the most common debates among GTM teams: “Do we have enough leads?” With no shared definition, this is like discussing whether you have enough money without knowing the value of your currency. Now, imagine this same conversation if there is a shared definition of the role of lead. They could do a reverse waterfall exercise by working their way backward from revenue goals and applying average conversion rates to calculate exactly how many leads they need to reach financial targets. A data governance team can create a glossary of key terminology, ensure buy-in for the definitions by all GTM stakeholders, and uphold their proper use.
2. Shared reports: Now that all GTM stakeholders have clear definitions for key terms like lead, prospect, customer, opportunity, conversion, velocity, closed business and so on, a data governance team can progress to leveraging those terms to create shared reports. Often, different GTM department leaders leverage different funnel data sets to manage their teams and for presenting performance information. This siloed data strategy can lead to siloed decision-making, all at the expense of corporate performance. There is only one funnel. If the team can align around a single source of truth for each data set, they can cut through any blind spots. Not only does this break down silos, but it also speeds up decision-making. Reports require an understanding of context, nuances, format and so on. Each time a stakeholder looks at a report for the first time, they will spend most of their effort on understanding the information and not taking action on the data. If all teams leverage the same reports, they can understand them more easily, and their focus can shift to GTM collaboration. To return to the earlier debate around the term “lead”: with a shared waterfall, a team might see that it has more than enough leads but is struggling to convert them. This requires a totally different focus than the marketing team’s. Without cross-GTM alignment, the marketing team may be reticent to take their foot off the lead pedal because that is how their success is typically measured. A single funnel view will make it clear that it would be better to deploy resources mid-funnel. This would allow marketing to divert their attention without penalization and sales to get critical conversion assets like case studies and product demos. The entire GTM function could set shared SMART goals around raising conversions to sustain this focus and then celebrate their success together as well. A data governance team can create the core source reports for each of the shared metrics, save them to a common dashboard, and train GTM stakeholders on how to leverage the data to meet their specific needs.
3. Standard operating procedures: Systems in a GTM tech stack are simply databases at the mercy of the quality of the data that goes into them and the humans who manipulate that data. The phrase “garbage in, garbage out” has no truer application than a tech stack. This may be the most insidious portion of data governance because teams don’t know what they don’t know. That same team that is laser-focused on conversion might be scrutinizing its performance without clear definitions for why opportunities are either lost or won. Often, CRMs default to fields that do not have enough specificity to drive insight. For example, if an opportunity is lost, one of the reasons provided might be “lost to competitor.” What does this mean? What competitor? Did the company lose the opportunity due to price, product specs, service or something else? Their concentrated efforts are being guided by a report that is largely useless. In the best cases, bad data can skew the true measure by a few degrees but be directionally correct. In the worst cases, bad data can lead teams in the opposite direction of where they need to be. Companies that do not understand buying behavior risk diluting their value proposition by competing on price, cutting their margins and veering from their business model. A data governance team can create SOPs for all data manipulation within the tech stacks and harmonize this across all users so that it is consistently applied and thus consistently understood.
With these three basic inputs, a data governance team can immediately provide immense value. Part two of this article will provide an itemized plan for the processes involved in bringing context to the plan. Together, they will lay the foundation for an evergreen data governance strategy that can support sexy growth.
Forbes Communications Council is an invitation-only community for executives in successful public relations, media strategy, creative and advertising agencies. Do I qualify?
