Leaving Product Analytics ft. Timo Dechau

What Got Us Here Won't Get Us There

Let's look back at the past year:

• Amplitude went seat-based and re-platformed on Snowflake.
• Heap was acquired by Contentsquare.
• Amplitude, Mixpanel are still vying for a slice of the marketing budget.
• PostHog "decided to make less money" and slash down their prices.
• Houseware is now giving access to product analytics for FREE

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And, of course, AI has taken the world by storm, powering a lot of new use cases [along with flashy ones that don’t deliver value]. 

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Phew, what a year it’s been for Product Analytics… but has it? 

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One thing is clear: what got these companies here will not get them there. As these products scramble to expand their offerings, pursue acquisitions, or do more, one has to wonder—are these moves signs of innovation, or are they symptoms of an industry struggling to redefine itself?

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We invited Timo Dechau to discuss precisely this.

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Timo's Journey: From Executor to Creator

Before we get into it, here is a little about Timo and exactly why he is the perfect person to discuss this with. 

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With 8 years of product experience, Timo discovered data early in his career. Why and how exactly? Working in a conservative environment where it was tough to influence the product backlog, Timo found that one of the only ways to get himself to be not only the “executor” but also the “creator” of the backlog was to use analytics—back when people were still using Google Analytics Classic. 

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So, he dove into the data and started using it. Simple! Check out Timo’s profile and what he has been up to since then here.

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The Inspiration: "Leaving Product Analytics"

Our discussion with Timo was inspired by his compelling blog post, "Leaving Product Analytics," written a year ago. This article not only captured the state of the industry at that time but also traced the evolution that had led to that point. Timo's insights into the challenges and potential future directions of product analytics set the stage for our conversation. If you haven't read it yet, we highly recommend giving it a read.

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So, let’s get into it!

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The Product Analytics Landscape: A Forest of Possibilities

For almost 4-5 years, the product analytics field remained relatively static, with major players like Amplitude and Mixpanel merely adding features without fundamentally changing the game. However, about a year ago, the industry began to shift:

1. Amplitude, Mixpanel started incorporating marketing analytics features, trying to address the long-standing need for integrated product and marketing insights [while also going after the function with the bigger budgets: Marketing]
2. Houseware, Kubit, and Netspring emerged, leveraging a warehouse-native architecture to offer fresh approaches to product analytics.
3. The potential for richer insights by combining product data with extensive contextual information from data warehouses became a realisable solution! 

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But did this movement cause much change? 

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Timo aptly described the difference between marketing and product analytics: "Marketing analytics is like a straight road, but product analytics is like wandering through a forest, searching for valuable patterns hidden among the trees." This complexity often makes it challenging for busy product teams to extract actionable insights from their data. 

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Iteration, Not Innovation, in Product Analytics

Over the past year, product analytics has been more about tweaking existing processes than making any big leaps forward. As Timo pointed out, "When you ask product analysts, there is no clear blueprint for how you approach a data setup for product development." Unlike marketing analytics, where the steps are more defined, product analytics still lacks that kind of standardization.

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Even with tools like Amplitude making bold moves—like re-platforming on Snowflake and switching to a seat-based pricing model—it doesn’t really change the game. Timo highlighted how challenging product analytics is and how small the community working on it remains: "It's quite fascinating that this space has been around for 10, 15 years, and we haven't made much progress in standardizing things." Until a solid, widely accepted approach is developed, real innovation in product analytics is still out of reach.

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The Wait for Real Innovation

The anticipated major shakeup in the product analytics landscape hasn't happened yet. AI “Party tricks” have been rolled out, such as talking to your data to get your charts, but as of now they definitely fall short of the 100x value that AI could bring about. 

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It’s about time we got the AI Co-pilots we were promised. 

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AI Agents: The Future of Connecting the Dots in Digital Analytics

AI agents could be the real game changers, especially when connecting the dots between different data sources. 

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These agents mimic human behavior to perform tasks autonomously across various tools—like Hubspot, Salesforce, Amplitude, CRM systems, and more. Imagine having an AI that can manage all these connections, pulling insights together in a way that a human just doesn't have the bandwidth for.

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Timo pointed out how his work in product analytics is all about "connecting a lot of dots." It's not just about analyzing a single data point but pulling together insights from different teams like sales, customer success, and support. AI agents could take this to the next level. With their ability to process vast amounts of data, they could connect "1,000 dots a week" and prioritize the most critical insights for you. This would be a game-changer, especially in spotting potential issues or opportunities that take time to be obvious. This isn't just about improving product development—it's about enhancing the entire customer journey, from initial contact to long-term retention!

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Visualizing the Impact

Divyansh brought up a cool visual to show where AI agents can make the biggest impact [check it out below]. The graphic below highlights how today's tools handle the easy stuff—data that's both accessible and easy to analyze. But the real gold lies in the complex, less accessible data that often gets ignored. AI agents could dig into these "dark insights," Timo also calls them, and uncover valuable patterns that might otherwise be missed.

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This could be huge for big companies where different teams sometimes communicate poorly. By linking marketing analytics with product analytics, AI agents could help answer critical questions, like which marketing campaigns bring in the most valuable users who quickly become engaged. This not only helps optimize marketing budgets but also ensures that product development is focused on what matters most.

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Timo summed it perfectly: "If we come to this point, I'd be super happy because then I scale myself up by the factor of 100." AI agents could take on the heavy lifting of data analysis, allowing human analysts to focus on the big picture and make smarter, faster decisions!

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Catch the entire recording of our discussion with Timo here.

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Join us as we simplify Digital Experience! 

We at Houseware are tackling the digital challenge head-on by creating AI agents that deliver a seamless, unified experience. Our AI agents don't just connect the dots—they transform how businesses handle data, making insights easy to access and act on. We're here to help companies move faster, work smarter, and make better daily decisions. If you're ready to elevate your digital experience, contact us, and let's make it happen!

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