Donux

📊 We just published a practical guide on how to start product analytics the right way, by defining business goals first. This is part one of our 3-part product analytics series, covering goals, tracking plans, and getting real insights from your data. --- Here's what the guide covers: ⚫ Why product analytics is not the same as marketing analytics, and why the distinction matters ⚫ A 4-step framework to define goals before you touch any tool ⚫ How to use the AARRR model to map analytics goals across the full funnel ⚫ Specific, measurable goal examples you can steal (onboarding completion, time-to-value, retention, churn) ⚫ How many goals to track based on your stage: pre-PMF, early growth, and scale ⚫ A comparison of Mixpanel, Amplitude, PostHog, and Heap A Product-Led Alliance report found that 66.9% of product managers said product analytics helped them achieve their goals, but only when analytics was tied to specific business objectives. --- 📜 Full breakdown here: donux(.)com/blog/how-to-start-product-analytics-business-goals Need help setting up product analytics that actually drives decisions? Get a free expert review from the Donux team: donux(.)com/free-expert-review

What's moving in tech this week for product teams 👇 (This is one of the stories from the Donux News Digest, a 5-minute newsletter where we break down the most relevant tech and SaaS news for product teams) --- 🟡 Your next buyer might be an AI agent. Is your product ready? Matt Williamson makes the case that AI agents are becoming product decision-makers. When developers use AI tools to build apps, the AI picks which third-party services to use, Stripe for payments, Resend for email, Firecrawl for scraping, without the human ever doing a comparison. The products that win share four traits: clear APIs, documentation optimized for AI consumption (not just human scanning), structured credibility like GitHub stars and changelogs, and early partnerships with the interface layers that make decisions. If your product doesn't have an API surface that plays nicely with agents, you're about to become the tool that gets routed around. --- 🔗 All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you. Subscribe to get everything into your inbox -> donux(.)com/saas-resources/newsletter Or read directly on LinkedIn -> click below

We just updated our free reference library: ⭐️ Top 25 SaaS Homepage Analysis. --- 🔵 What's inside We picked some of the best SaaS homepages and broke each one down across three layers: - Company context: quick snapshot of the company and product - Conversion structure: how content blocks guide users toward actions and CTAs - Positioning & GTM strategy: Positioning, target audience, differentiators, and adoption approach (PLG, enterprise, etc). On top of that, our design team added short notes on layout, color, typography, motion, and hierarchy. 🔵 Why we made this We believe good design starts with good references. Now, instead of looking at a messy folder full of screenshots collected here and there, you have a structured Figma file. 🔵 This is a living file Over time, we'll continue to add new homepages and fresh comments. Bookmark the file and check back whenever you're looking for inspiration! 👉 Explore the collection: https://lnkd.in/e2kbQEpU ––– ––– ––– 🔵 Who we are Donux is a product design agency for B2B SaaS. We have worked with 80+ SaaS companies, from early stage startups to scaleups. Our team plugs into your product workflow, combining research, design, and data to drive measurable product improvements.

What's moving in tech this week for product teams 👇 (This is one of the stories from the Donux News Digest, a 5-minute newsletter where we break down the most relevant tech and SaaS news for product teams) --- 🟡 The rebundling era means your "one thing" might not be enough. AI companies are skipping the focused single-workflow phase entirely and expanding into adjacent categories on day one because build costs are near zero. Buyers are starting to prefer one platform for three to five years over stitching together best of breed. If you're a B2B SaaS product that owns one workflow really well, the moat isn't the feature anymore. It's the data, the integrations, and how painful you are to rip out. --- All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you. Subscribe to get everything into your inbox -> donux(.)com/saas-resources/newsletter Or read directly on LinkedIn -> click below

What's moving in tech this week for product teams 👇 (This is one of the stories from the Donux News Digest, a 5-minute newsletter where we break down the most relevant tech and SaaS news for product teams) 🟡 OpenAI killed Sora. The product lesson is louder than the news. OpenAI shut down its AI video app Sora and walked away from a $1 billion Disney deal, pivoting toward robotics and agentic AI. Sora made $1.4 million against ChatGPT's $1.9 billion. For product builders: if a feature isn't pulling its weight relative to your core, cutting it early is a strategy, not a failure. --- All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you. Subscribe to get everything in your inbox 👉 https://lnkd.in/g8QpiJUg Or read directly on LinkedIn 👉 click below

From broad vision to focused MVP 🎯 We worked with Sinapto on a management platform with integrated carbon accounting. We took it from a broad product vision to a focused MVP in 5 key phases: 🟠 Analyzed the competitive landscape and decided to position the product around ESG reporting 🟠 Defined user profiles and value propositions to scope the MVP 🟠 Built a modern visual identity, design system, and component library 🟠 Designed the full platform UI 🟠 Created a carbon accounting dashboard with accessible data visualization The result: a clear product direction, a defined MVP scope, and a design system ready for development. Take a look at the entire case study: donux(.)com/case-studies/sinapto --- P.S. Have a broad product vision but need to find the right MVP focus and a clear positioning? We can help you get there -> Get a free expert review from the Donux team: donux(.)com/free-expert-review

What's moving in tech these days 👇 (This is from the Donux News Digest, a 5-minute newsletter where we break down the most relevant tech and SaaS news for product teams) 🟡 Your AI feature might be making users dumber, and that's a design problem. A Wharton study of 1,372 people found that after just a few weeks of using AI, people stop critically evaluating its output entirely. They call it "cognitive surrender." If you're shipping AI features without designing for user judgment, you're building a product that quietly degrades the people using it. 🟡 Clay bet that simpler pricing would cost them 10% of revenue. That's the point. Clay rebuilt its pricing model from scratch, dropping from five tiers to four and adding an "actions" metric alongside data credits. They expect a short-term revenue hit of about 10%. Worth studying: they spent a year testing with real customer segments before shipping, which is more rigor than most teams put into their most revenue-sensitive surface. 🟡 Anthropic's computer use feature is the AI agent story worth actually watching. Anthropic launched a research preview that lets Claude control your Mac: navigating browsers, opening files, using connectors like Google Calendar and Slack. This isn't chatbot territory anymore. If your product relies on users toggling between tools to get work done, the assumption that they'll keep doing that manually has an expiration date. 🟡 Product design is changing in the world of AI and agentic tools. AI has made execution faster than ever, which means the constraint has shifted to judgment. Designers who only know how to push pixels are going to struggle. The ones who combine technical fluency with strategic thinking will become the most valuable people on a product team. ❓ Today's question: When was the last time you tested your pricing with the same rigor you test your product? --- Subscribe here -> https://lnkd.in/g8QpiJUg All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you.

🆕 Product-led growth: implementation checklist A practical month-by-month checklist for SaaS founders implementing product-led growth. We wrote the full guide on the Donux blog. The carousel below covers the highlights. We briefly talk about: - Foundation - Onboarding optimization - Growth "quick wins" - How to define product-qualified leads - The PLG flywheel - 5 PLG mistakes that kill growth: --- --- --- 📜 Read the full blog post: donux(.)com/blog/plg-implementation-checklist 💬 Get a free expert review from the Donux team: donux(.)com/free-expert-review

What's moving in tech these days 👇 (All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you -> donux(.)com/saas-resources/newsletter) --- 🟡 Sketching your way into an AI prompt changes the input game for product teams. Anthropic is reportedly building a Sketch tool for Claude that lets users draw quick visuals instead of typing out descriptions. If this ships, it collapses the gap between what a product person sees in their head and what they can communicate to an AI. For anyone designing interfaces, flows, or layouts with AI assistance, this could make the feedback loop dramatically faster. 🟡 Synthetic customer research just hit 88% accuracy. That changes the discovery timeline. Evidenza runs market research on AI-generated replicas of your target customers, compressing what used to be a 6-month survey into about 6 hours. For B2B teams trying to validate with hard-to-reach buyers like CIOs or procurement leads, this removes the biggest bottleneck in discovery: actually getting time with the people you're building for. 🟡 The fastest way to convert more free users isn't changing your product. It's changing who signs up. ChartMogul analyzed 30 real experiments across 200 B2B software products and found that a 1 percentage point lift in free-to-paid conversion equals roughly 15% more revenue per trial. The biggest lever? Attracting the right users in the first place. Product teams obsess over onboarding flows and activation metrics, but the data says your acquisition filter matters more than your conversion funnel. 🟡 OpenAI doubling its headcount means the AI tooling treadmill is about to speed up again. OpenAI plans to grow from 4,000 to 8,000 employees by year end, with hires spanning product development, engineering, research, and sales. More people shipping means faster releases, more capabilities, and more breaking changes for every product team building on top of their APIs. If your roadmap depends on OpenAI's platform staying stable, budget more time for keeping up. --- ❓ Today's question: If you could only improve one thing, would you rather make your product 10% better for current users or make sure 10% more of the right people find it?

What's moving in tech these days: 🟡 The real product skill now is knowing what not to build. Speed keeps getting cheaper. AI tools, better infra, faster deploys. But shipping more doesn't mean shipping better. Product leaders who treat velocity as the goal end up with bloated products and eroded trust. The new discipline is protecting direction and saying no faster than you say yes. 🟡 OpenAI is collapsing its tools into one app. Your users probably want the same thing. OpenAI is merging ChatGPT, Codex, and Atlas into a single desktop superapp. If even OpenAI thinks separate AI apps are a dead end, product teams bolting on standalone AI features should take note. The pattern is clear: users don't want another tab, they want capability baked into the thing they already use. 🟡 Your free trial length should be tied to your aha moment, not your competitor's pricing page. New research reinforces that optimal trial length depends on how fast users hit real value and form habits. Most teams copy industry defaults and optimize for conversion rate, when they should be optimizing for long-term retention. If users aren't activating during your trial, the trial isn't too short. Your onboarding is too slow. 🟡 Guillermo Rauch on why choosing what to ignore is a competitive advantage. The Vercel CEO shared five lessons for building in the AI era. The one that hits hardest: open source stress tests product-market fit because people won't pay for something they won't even use for free. In a world where AI makes building easier, the founders who win will be the ones who are ruthless about which problems actually deserve their attention. --- ❓ Today's question: Do you actually know how many days it takes your average user to hit real value? --- All the stories come with links in the newsletter, so you can go deeper on the ones that matter to you. Full digest here -> donux(.)com/saas-resources/newsletter