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.

Analytics teams will always be understaffed, that's not a problem to solve, but a reality to work with. This article explores how analytics leaders can build powerful virtual teams through evangelism and relationship building rather than waiting for budget approvals.

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.

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.

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.

At 33 Sticks, we're proud to be the artisanal option – crafting unique, high-quality solutions for clients who value a more personalized approach to analytics consulting.

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

The digital analytics industry is facing significant issues as major platforms like Google and Adobe push for migrations to GA4 and Customer Journey Analytics (CJA). These migrations have been plagued by poor implementation, largely due to over-reliance on large consulting firms and subcontractors lacking expertise. This has resulted in frustrated clients, failed projects, and a tarnished industry reputation. However, smaller agencies have an opportunity to step up by focusing on quality, transparency, and client education. The industry must realign incentives, demand transparency, and foster innovation to create a client-first ecosystem that prioritizes genuine customer success over vendor-driven sales goals. This is a call to action to reclaim the industry from monopolistic practices and build a better future for digital analytics.

From an early age, children are naturally curious, asking questions, observing patterns, and trying to make sense of the world around them. In our modern, data-driven society, this innate curiosity can be nurtured through tools that teach them how to think critically, analyze information, and draw meaningful conclusions. This is why we created A is for Analytics—to make the world of data accessible to kids in a fun and engaging way.

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.

A scoring framework for helping select the best A/B testing partner for YOU.