Dashboards were designed for monitoring, not exploration. Analytics is dynamic. It is a process of asking questions, interpreting information, and uncovering meaning. Yet most analytics still rely on static, outdated interfaces. It is time for a better experience, and we believe that experience should feel like a natural conversation. Read More.
The Interface Problem
In our first article (link), we explored the difference between Reporting and Analytics. Reporting looks backwards. Analytics help you reason, explore, and decide. Unfortunately, dashboards (today’s default data tool) don’t serve analytics well.
Dashboards are built for reporting. They’re great at showing what happened. But when the question becomes why, they fall short.
To answer why, you need more than a chart. You need context. You need a back-and-forth. You need to question, reason, and iterate.
You need a conversation.
The Reality of Analytics (Pre-AI)
For years, the default interface of Analytics wasn’t dashboards, it was people. Specifically, someone on the data team with the technical skills and time to explore your questions (data analysts)
When someone wanted to make sense of data, they didn’t open a dashboard. They pinged their data coworker and started a conversation. “Hey, can you help me understand why signups dropped last week?”
That simple exchange would often lead to a series of follow-ups, a handful of SQL queries, and a real explanation: iOS conversions from paid traffic dropped by 30%, so you decide to A/B a new landing page.
This process is a feature, not a bug. It’s how humans solve problems. Through iteration, language, and understanding.
What AI changes, and what it doesn’t
What AI does not change is the nature of analytics. It is still about asking the right questions, reasoning, and iterating.
What does it change? Who gets to participate, and how fast they get answers.
Until now, meaningful analytics was constrained to those with SQL skills, context, and time.
Now, with natural language models and governed data layers, the same human-like conversation can happen faster, at scale.
You still ask the question. You still get follow-ups. You still explore nuance.
But the coworker will is AI. And the AI brings speed, consistency, and context-awareness to every conversation.
Why we built Zoe around conversation
When we started Zenlytic, we didn’t set out to replace dashboards. We just paid attention to how Analytics really happened.
Saw saw the most valuable insights don’t come from a chart. They come from a conversation about that chart.
So what if we could scale that conversation? What if the conversation was the product?
That’s why we leaned into Zoe, our AI data coworker, as the default interface. Not because AI-based chat is trendy, but because it’s natural for the Analytics workflow.
When Dashboards & Charts charts still matter
To be clear: Dashboards aren't dead. They still have a role, and remain the best tool for reporting and monitoring.
We’re also not saying dashboards and charts don’t support Analytics. Often, a conversation with Zoe results in a narrative supported by a handful of visualizations. Charts remain a powerful way to interpret and communicate findings.
But for most users, conversation is the best into the Analytics workflow. Rather than staring at a Dashboard and fiddling with filters, why not just ask?
The future of Analytics UX is human
We’re not trying to reinvent the Analytics conversation, it already exists. Our goal is to make it accessible, more often, and with less friction.
We’re moving from tools designed for data teams to interfaces designed for decision-makers. From static dashboards to a dynamic dialogue.
The future of Analytics UX is still human, and still feels natural. We’re just making it more accessible.
In a world where data is everywhere, the advantage won’t go to the companies with the most charts. it’ll go to the ones with the best understanding. And understanding starts with a better question. Just ask.
