Should we build our own analytics stack or use an off-the-shelf tool?
For most product teams, a dedicated product analytics tool — such as Mixpanel, Amplitude, or PostHog — delivers faster time to insight than a custom-built stack. Building your own means maintaining infrastructure, not analysing behaviour. We help you choose the right tool for your data volume, team size, and privacy requirements, then instrument it properly so you're not rebuilding in six months.
Which metrics framework should we use?
The right framework depends on your product's growth model. The AARRR framework (Acquisition, Activation, Retention, Revenue, Referral) works well for most SaaS products because it maps analytics to the full user lifecycle. We also use north star metric frameworks for teams that need a single shared focus. We assess your model first, then recommend the structure that fits — rather than applying a template regardless of context.
How long does it take to set up product analytics properly?
A full engagement — audit, instrumentation, metrics framework, and initial dashboards — typically takes four to eight weeks, depending on the complexity of your product and the state of your existing tracking. If you have no prior instrumentation, expect the higher end. If you have partial tracking that needs cleaning and extending, we can often move faster. We scope this precisely after the audit.
Which tools does Netguru work with?
We work across the main product analytics platforms, including Mixpanel, Amplitude, PostHog, and Heap. For data pipelines, we work with Segment and RudderStack. We're tool-agnostic in our recommendations — we start from your requirements, not a preferred vendor. If you already have a tool in place, we work within it; if you're choosing from scratch, we help you evaluate options before committing.
What makes a dashboard trustworthy?
A trustworthy dashboard has three properties: it answers a specific question, it draws from a single, well-documented data source, and it has a named owner who keeps it current. Most dashboards fail on all three — they show everything, pull from inconsistent sources, and belong to nobody. We build dashboards around decisions, not data availability, and we document the event logic behind every metric so your team can verify what they're looking at.
What is the difference between auto-capture and manual event tracking?
Auto-capture records every user interaction automatically — clicks, page views, form inputs — without requiring code changes. It's fast to set up but produces noisy, hard-to-query data. Manual tracking requires a developer to instrument specific events, but gives you clean, intentional data with consistent naming and properties. We typically recommend a hybrid approach: auto-capture for discovery, manual tracking for the events that drive decisions.