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Context is Key to Cementing the Value of Data Within a Company

Data Data, Data Strategy & Advisory, Data maturity 5 min read
Profile picture for user Juliana.Jackson

Written by
Iuliana Jackson
Senior Data & Optimization Strategist

A laptop and an analytics print out showing data tables and graphs

Ten years ago, my career looked totally different—I was in sales and didn’t know the first thing about data. Fast-forward to today, I have moved to a tech-first role and I’m loving every bit and bob of it. Interestingly enough, it is through my non-tech background that I’m able to thrive in my current role. Why? Because as a digital analyst, it’s important to understand business principles and how they influence your work—something that salespeople are experts in. Digital analysts must understand human behavior, the business landscape, and how their company and clients make money. This will enable them to make informed decisions and be truly impactful in their roles.

“It’s so much more powerful being a part of a team that’s full of mixed backgrounds and experiences,” says Doug Hall, VP of Data Services and Technology. “Tech isn’t just for computer science graduates. If we didn’t have a rich tapestry of skills and experiences woven into the team fabric, we’d have a homogeneous glom of great skills, but we’d be more likely to do the same things this week as we did last, and in the same way.”

My move from non-tech to tech-first taught me that many things surrounding data are isolated from business needs and outcomes, even though you don’t want this to happen. When teams operate in silos and data works in isolation, so does experimentation. This inevitably leads to random acts of marketing and chaotic reporting. Rather than siloing teams, data should unify them—even if they have totally different KPIs. For instance, marketing teams look at lead generation, engagement and visibility, while product teams focus on retention and acquisition. In short, if everyone has a separate way of tracking and collecting data, this also means that everyone is looking at different things. 

Viewing the full picture is pivotal to success. 

The bottom line is that all of this information is data, and everyone should be aligned on what type of data will actually help the company move forward. Companies may invest in tools that serve one or more departments—GA4, for one, can support marketing and product teams—but the way each team or department collects data should be a company-wide decision. In turn, this means that a company’s data collection mechanism needs to be strong and reliable to be able to support every team and department in a business and help spur progress. The goal is to unite, not separate. That’s why it’s critical to align what matters in terms of data collection and measurement with the company’s business needs. 

The operative word is context—whatever we do, we must keep this in mind. Getting your company or clients to believe in the data at hand starts with analysts and measurement marketers understanding where the business is right now and where it can go. By actively participating in the inner workings of a business—with a focus on resource allocation and the processes that generate money—and analyzing relevant and purposefully collected data, you can help steer your company or clients towards profit. 

As such, I recommend every digital analyst to get familiar with a business’ internal processes. You can use this knowledge to implement tracking and analytics systems that align with the company’s procedures. A good example of this is how we helped the multinational alcoholic beverage company Diageo deploy GA4 across its 150 brand websites. As Hall explains, “Due to alcohol regulations around the world, most countries require an age verification gateway, which is a major conversion blocker that goes above and beyond consent management. This means that measurement and optimization are crucial for Diageo—and that’s how we knew that deploying consistent measurement across all brand sites was the best solution.”

Monk Thoughts The deployment of consistent measurement was automated. Consistency comes not only from mirroring the tagging, but also from doing so across each site in the exact same way—perfect for automation to solve at scale. Ultimately, this increases efficiency and reliability.
Julien Coquet headshot

In short, every digital analyst should come to understand the business context and goals to make sure the tag management and analytics tools are both implemented effectively and in line with the needs of the business. The secret sauce here is to closely collaborate with business-focused team members like marketers, consultants and account managers, who can provide guidance on what data is needed and how it will be used. Sure, we can rely on our experience and heuristics, but that doesn't mean any of our assumptions can be valued as truth. Once you’ve actually combed through a specific business context, you can start to define the right strategy for your business—and even then, it’s a matter of seeing how things play out before you can confirm or reject your hypothesis. Experiment, experiment, experiment!  

Become data mature to make your cash flow. 

Ultimately, this all feeds into a company’s data maturity, which Forbes defines as “a measure of an organization's ability to use data, along with how well the organization leverages those capabilities.” It’s not just about making data-driven decisions, but also about making sure data resources are accessible across an organization. The more data mature you become, the more you can scale—a topic that Coquet will discuss in more detail during the upcoming SUPERWEEK conference.  

With scale comes growth, which, in turn, can lead to new opportunities—and let’s be honest, this is an outcome that every business is after in their search for better tools, better consultants, and better digital marketing partners. When it comes to collecting data and tracking user behaviors (with consent, but this goes without saying), businesses do not want to miss out on any opportunity to get new customers, while staying relevant to their existing ones so that they continue to trust and purchase from them. More happy customers equals more cash flow. In the end, profit is the ultimate validation of growth (and that you’re doing a good job), both from a product and a customer experience perspective. 

Three takeaways to make your data take off. 

While it may take some time to find the most advanced tech stack or the best digital marketing partner—one that truly understands your business and all its needs—there are some changes you can make today. Trust me when I say that these actions will pay off in the end and help your cash flow grow. 

First of all, start by defining the problems you are aiming to solve and the questions you are seeking to answer with your data before you implement anything. This will help fine-tune your efforts and ensure that you are using the right tools and approaches to address the specific challenges you face. 

Second, consider (and research) the possibility of teaming up with a data consultant or specialist, who is able to provide expert advice and guidance on what tools and approaches are best for your specific problems and questions. This is particularly helpful if you are working on a complex or unique challenge that requires specialized knowledge and skills.

Third, teamwork always makes the data dream work. It’s crucial to collaborate with your team members and exchange your knowledge and experience—as Doug said, the more mixed the expertise, the better. By closely working together and sharing what you know, you can pool your collective knowledge and experience in setting up your measurement strategy. Keep in mind that within a business context, every team has its own problems and questions. As a leader, it's important to begin by having them define these, which, in turn, will reveal how aligned your team is around the company’s needs.

The main lesson that you should learn from this article is that context is key. At the end of the day, understanding human behavior, the business landscape, and how a company and its clients bring in money is what makes a successful digital analyst. I didn’t know this ten years ago, but I do now and I’m very happy to share these insights with you—find Julien, Doug, me and many other Data.Monks at SUPERWEEK 2023 and learn more about what really matters in managing your data.


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The website has been translated to English with the help of Humans and AI