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How Successful CMOs Build a Data-Strategy and Avoid the Hot Seat

Alex Poulos

CMO tenure is at an all-time low.

According to a recent survey, CMO tenure dipped to the lowest it has been since 2009.

If you aren't obsessing over data as a CMO, you might not be a CMO much longer. The rise of the modern data stack has unlocked huge amounts of data sources and data points. As a result, marketing has shifted away from the brand-centric Mad Men era to a focus on driving operational success. Today's CMOs, or at least the successful ones, are truly data-driven. 

We recently spoke with CMOs in the space during a live panel event and asked them how the CMO role is changing. Unsurprisingly, data and operations came up in multiple responses.

“The biggest thing that has changed for marketing leaders in the last 12 months is the need to be able to move a metric in a really short amount of time,” Sheridan Gaenger, Head of Revenue Marketing at Honeycomb.io, shared. She elaborated that marketing leaders today must be clear about the metrics that matter most to the business and how they can use data to move those metrics.

“The biggest change we’ve seen is the continuing proliferation of customer touchpoints and channels,” Kevin Tate, CRO at Clearbit, discussed. More tools and tech than ever before means more customer data to operationalize. 

The role of the CMO today is to make sense of an abundance of data and drive the business forward. So, what should CMOs be thinking about when creating a data strategy and building a data-driven culture

Here are three key insights from leaders in the space. 

1. The MQL is a dying metric

For a long time, CMOs and marketing leaders focused on the MQL as the north star metric. It’s necessary to step back and dive into the data to evaluate what is most important for your organization. Data shows us what is most important to our customers and prospects. We can use that information to have to accelerate deals and make revenue teams more effective. 

Enter the MQA (marketing qualified account).

“So long, MQL. Hello, MQA.”

Sheridan shared an interesting result she found from digging into Honeycomb’s data. After analyzing a recent paid campaign, she and her team noticed they were driving a ton of impressions to the landing page, but people were bouncing. Conversions weren’t happening. She and her team learned from these insights that the content was interesting, but people didn’t want to fill out a form. Knowing her ICP, developers tend to be more cautious with their personal information online; it made sense that they wouldn’t want to fill out a form. 

These findings shifted their approach. They removed the forms and decided to focus on creating educational content. A good reminder here and point that Chris Walker, CEO at Refine Labs, discusses around creating valuable content for your audience, regardless of whether they are a customer or not. 

They also realized it was more important to get multiple practitioners to consume the content than one individual. These changes led them to move away from an MQL to an MQA goal, ensuring a focus on engagement across the account and signals that are more indicative of readiness to buy. 

Have you checked what your data is telling you recently? It might just shift how you approach defining measurement and success. 

Let’s talk PQLs.

Product data is critical in understanding user behavior and interest. In a PLG organization, it is essential to understand key milestones and activities to get users to interact in a way that will lead to conversions. 

No longer do the same MQL rules apply.

PLG organizations are looking at PQLs (product qualified leads) instead of MQLs. Sara Strope, CMO at TaxJar shared the importance of understanding PQLs to identify who, when, and how to interact from a sales and marketing perspective. She also shares how dissecting the data helped uncover an opportunity for marketing to engage with users in a more meaningful way and reduced support tickets by 30%.

2. There’s a shift to data centralization.

Having data easily visible in one place allows the marketing team to understand their impact metric regardless of their department. 

Sheridan discussed how she and her team brought in a modern Business Intelligence (BI) tool to lead the data centralization charge. By having a BI tool, all teams at the company can see the same information, and everyone is enabled to be their own data engineer, accessing critical information to make informed decisions. Many organizations may think they have their data centralized, but is it actionable? For data centralization to be a success, relevant teams like sales and marketing need to get immediate insights to drive their business area forward.

“Finding how to measure that (impact) metric is extremely challenging,” said Sheridan. It can be coming from multiple sources. A solution like Mode enables marketing to make informed decisions to drive the business forward.

Regardless of the specific tool, CMOs today should be thinking about data centralization and how to make data more accessible and usable for their teams.

3. CMOs need strong relationships with other technical teams.

While tools and tech can help CMOs drive a data strategy, a key piece of the puzzle is having relationships with other important stakeholders. 

Raj Sarkar, CMO at 1Password, and Sara shared how they partner with technical teams across the org to drive a smart and successful data strategy. 

Most marketing teams now have their own analysts and data engineers. 

Raj shared how his team structure at 1Password has enabled his team to build a data-centric strategy. 

While there is a centralized data organization within the company, he also has analysts and data engineers that sit directly on his marketing team who prioritize and contextualize the metrics that matter most to his strategy. They also help communicate with data teams within other orgs, so the company as a whole is well briefed on what is driving their bottom line. Raj noted that, though this was not the case 15 or 20 years ago, the trend of having data engineers embedded in the marketing team is becoming more commonplace.“There is a transformation happening in the marketing function” and how they interact with technical resources.

Kevin also shared that at Clearbit, the data ops team lives within the marketing team, enabling marketers to be close to the data and make informed data-driven decisions. 

CMOs must build relationships with data leaders. 

At TaxJar, they introduced a new role, a Data and Ops Leader. 

“The data and operations leader became one of my new best friends,” said Sara.

This role works closely with marketing to help roll out new tools like Segment and Amplitude and ensure the team gets the most out of these tools. Having this as an independent function also helps to broker the needs across the organization. 

As a CMO in this data-driven world, creating those strong cross-functional relationships with data and engineering leaders is essential. 

For more data-driven insights from marketing leaders, check out the recent panel event.  

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