For Wambui, choosing 33 Sticks wasn't just about fulfilling an internship requirement, it was about finding the right environment for meaningful growth. With her experience, she sought a boutique agency with specialized offerings and a reputation for excellence.

"At this stage in my career, joining a boutique agency felt essential, somewhere with a tailored service offering and a reputation for excellence. I wanted more than just 'checking the box' for my master's internship, I wanted an enriching, really focused experience that truly aligned with my goals."

Perhaps most importantly, she was drawn to our people-first philosophy. "Success to me, is about building with integrity and people at the center. That people-first approach made me confident this is the right place to grow and receive invaluable mentorship."

Disinformation is not confined to politics or public health, it lives wherever data can be bent to serve an agenda. Analysts hold a unique responsibility as translators of data into action.

When we strip away context or selectively frame numbers, we risk becoming part of the same machinery that erodes public trust.

At 33 Sticks, we believe ethics cannot be optional. Our manifesto commits us to objectivity, transparency, and context because without objectivity, the true value of data is lost.

For the past fifteen years, i’ve worked with data practitioners across industries, retail, healthcare, tech, finance, entertainment. Different businesses, same story. Teams feel frustrated and underappreciated. They’re buried in requests for reports and dashboards, treated as service providers, and excluded from strategic conversations.

The complaints are familiar:

• “We don’t have a seat at the table.”

• “The business doesn’t respect us.”

• “Leadership ignores our insights.”

Yet beneath the frustration lies a paradox. The very behaviors and beliefs that define how most data teams work are the same ones sabotaging their influence. We want respect but avoid accountability. We want to be strategic, but we refuse to step into the role.

Earlier this month, Cracker Barrel unveiled a new brand identity. The familiar imagery of a man leaning on a barrel disappeared. Within hours, social media lit up and headlines followed:

• “Board member under fire for DEI background after restaurant ditches traditional logo”

• “Conservative activist slams Cracker Barrel; company left reeling after logo redesign”

• “Marketing fiasco shows investors are making ‘woke’ a massive risk factor”

The narrative was clear, the redesign wasn’t about business strategy, it was about politics.

At 33 Sticks, we believe the most fascinating insights often emerge when we apply analytical rigor to unexpected datasets. Recently, we discovered a treasure trove of human behavior patterns hiding in plain sight: LinkedIn professional responses to a policy analysis scenario.

Until we bridge the gap between data and felt experience, our dashboards will remain beautiful, sophisticated, and ultimately ineffective displays of information that change nothing.

The digital analytics industry stands at an inflection point. As generative AI and automation sweep through organizations, promising to handle everything from data collection to basic analysis, we face a fundamental question: What becomes of the digital analyst?

The answer isn't found in fighting the tide of automation or doubling down on technical skills. Instead, it requires us to acknowledge an uncomfortable truth that digital analytics, as we've known it, is already obsolete. Not because the work doesn't matter, but because the name itself has become too small for what we must now become.

What emerges from this disruption isn't the death of a profession but its radical evolution from mechanical data workers to what we call "organizational anthropologists," practitioners of Human-Centered Analytics who help businesses see the humans behind the data.

There’s a moment in every analyst’s career when they stop just reading data and start questioning it.

We’re not talking about being cynical or skeptical for the sake of it. We’re talking about curiosity-driven, clarity-seeking, insight-focused critical thinking.

Take U-Haul’s 2024 “Growth States Report.” It ranks U.S. states based on one-way U-Haul rentals, suggesting where people are moving to and from. At a glance, it’s a tidy list with intuitive appeal. But scratch the surface, and it becomes a perfect teaching tool, not because the data is “bad,” but because it invites better questions.

So let’s use this dataset not as something to critique but as something to practice on.

Ad agencies are buzzing about Meta’s new Incremental Attribution model with some calling it a breakthrough in “real” measurement and the end of vanity metrics.

But here’s what we’re not seeing: Critical discussion from a data perspective.

The rapid rise of Generative AI has raised serious questions about the future of digital analytics. Tools that were once positioned as analyst accelerators now appear to be replacing the need for analysts altogether. With platforms like Amplitude, Adobe Analytics, and GA4 embedding natural language querying, anomaly detection, and AI-generated insights directly into their workflows, some enterprise leaders have begun to ask an uncomfortable question: Do we still need analysts at all?

A friend once remarked to me that "unintentional evil is still evil," referencing how social media platforms might not have been designed with malicious intent, yet their engagement-obsessed algorithms often create harmful outcomes. Sometimes it's not evil but simply unethical, disrespecting humans, breaking trust, or manipulating behavior.

In both espresso-making and data analysis, the magic happens not when we automate away complexity, but when we master it. The perfect shot, like the perfect analysis, comes from understanding each variable, each step, each potential pitfall in the process.

The organizational positioning of analytics teams represents one of the most consequential yet frequently overlooked strategic decisions in modern enterprise structure.

Critical thinking and skepticism are not just optional tools for data analysts—they are essential. Without them, we risk allowing flawed, biased, or incomplete data to influence important decisions. In a world where data is used to shape narratives and drive opinions, our responsibility is to approach it with a healthy dose of doubt and a commitment to uncovering the full story.

Popups. Sliders. Takeovers. We all hate them. Right?

Everyone says popups suck yet sites that use popups consistently outperform sites without them.

If this is true, then why do so many sites choose not to deploy a well designed and targeted popup strategy?

As a data practitioner, it's hard not to be curious and perhaps concerned about how Generative AI (GenAI) will impact your profession. The reality is, we’re already in the middle of a major shift, one that's unfolding in distinct phases. For those responsible for making decisions about the future of data teams, including budget holders, analytics executives, and practitioners themselves, understanding these phases is critical to staying ahead.

• Revenue Alignment Isn't Everything: While important, focusing solely on revenue can overlook other critical factors stakeholders value.

• Stakeholder Engagement Is Crucial: Regular communication and understanding stakeholder priorities enhance alignment and recognition.

• Multidimensional Value Matters: Demonstrating value across various dimensions strengthens the case for the analytics team's contributions.

For those data professionals, of which there are MANY, whose primary outputs are things like data collection, reporting, PowerPoint presentations, writing code, and deploying data tools, if these activities are seen as the core of their work rather than as means to deliver real, tangible value, they are on a dangerous path.

We would like to argue that data-driven test ideas are some of the most impactful test ideas to drive results and help your senior leaders achieve their goals. Testing an idea that has the potential to address checkout funnel fallout and decrease that rate is impactful. That being said, how much time does your data team spend developing and providing these insights?

33 Sticks Co-Founder and Principal Analyst, Hila Dahan, presented an extremely popular session at Adobe Summit 2019 in Las Vegas on leveraging Adobe Analytics Advanced Calculated Metrics. Hila's session focused on using advanced Calculated Metrics to drive deeper insight into consumer behavior.