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Top-down guidance

Where we're going in 2025 🚀.

Ella Thompson

Hey team, I've spent the last month diving deep into customer conversations, market trends, and our product capabilities. I'm excited to share where we're heading - because the opportunity in front of us is massive. While we've built something great, we're just scratching the surface of what's possible. Our customers are hungry for more, and we're perfectly positioned to deliver it.

Here’s a quick Loom walking through why I’m so excited about 2025.

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Where we are today

Let's be real - our platform is solid. Our dashboards rock, our reports are reliable, and customers trust us with their critical data. That's huge. But in our recent customer conversations, we're hearing a clear message: they want us to dream bigger. There are two big gaps in our product:

Our enterprise customers are juggling a dozen different tools and begging for better integration.

Mid-market teams love our advanced features but find them too complex to use daily.

The message is clear - they believe in our vision but need us to take it further.

The 3 shifts that change everything

Here's what has me fired up: we're seeing three massive shifts in how companies use data, and they're all playing to our strengths. First, teams are drowning in data but starving for actual insights - they need tools that don't just show charts but tell them what matters. Second, everyone's becoming a data person now - from marketing to sales to customer success. The days of analytics being just for analysts are over. Third, companies don't just want to know what happened - they want to know what's going to happen. This is our moment to step up and solve these challenges in a way no one else can.

See

Example: Miro vision board⁠

for a deeper dive on these shifts.

Our objectives for 2025

1. Enhance user experience in core platforms

2. Drive revenue growth, with a focus on retention

3. Strengthen product stability and scalability in 2025

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Where we’ll be at the end of the quarter.

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What we need

To make this happen, we're going all in:

Growing our AI team significantly (hiring now!)

Leveling up our infrastructure

Building deeper partnerships with the tools our customers love

Expanding our customer success team to support these new capabilities

How we'll know we're winning

We're setting ambitious targets:

30% more people using our platform daily

Getting to insights 25% faster

40% more automated discoveries

NPS jumping from 45 to 60

Data integration time cut in half

The opportunity in front of us

Taking a step back: we're not just building features - we're fundamentally changing how organizations extract value from their data. This is about giving companies superpowers. It's about turning data from a headache into an advantage. And we're the team that gets to make it happen.

The market is ready. Our customers are ready. Our team is ready. 2025 is our year to make the leap from analytics platform to indispensable business partner.

Let's do this.

—Ella

P.S. I'll be hosting open office hours every Thursday to discuss these initiatives and hear your ideas. First session is next week - calendar invite coming shortly!

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Can you break down the 40% AI/ML team expansion - what specific roles are we prioritizing and how does this align with our current technical capabilities?

You mentioned partnering with key enterprise software providers - do we have any specific companies in mind, and have we started those conversations?

The natural language interface sounds ambitious - what level of query complexity are we aiming to support in the first release?

What's our strategy for maintaining backwards compatibility with existing integrations while building out the new data integration platform?

What's our backup plan if we can't hit the Q1 timeline for the first AI features? How are we prioritizing which capabilities to release first?

How are we planning to handle data privacy and security concerns with the new AI features, especially for our customers in regulated industries?

Could you share more details about the unified data governance framework? How will this impact our existing enterprise customers' workflows?

Are we planning to adjust our pricing model to account for these new AI capabilities? How will this affect our current enterprise contracts?

The 25% reduction in time-to-insight metric is interesting - how exactly are we measuring this, and what's our baseline?

The memo mentions 'automated insight generation' - could you share some concrete examples of what this might look like for our customers?

Can you elaborate on the 'role-based experiences' concept? How granular are we thinking about different user personas?

How are we thinking about balancing resources between these new initiatives and ongoing maintenance/support of our core features?

What changes should our customer success team expect in terms of training and support requirements for these new features?

How are we planning to maintain system performance and reliability while implementing these major new features? What's our infrastructure scaling strategy?

The memo mentions 'guided analytics pathways' - could you give some examples of the common use cases we're planning to support first?

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