Many teams run two analytics tools without planning to. Marketing installed one to see where traffic comes from. Product installed another to see what people do after they sign up. Two years later, the two disagree about how many users you have, and nobody is sure which to trust.
The split made sense once. It makes less sense now.
Web analytics: how people found you
Web analytics answers questions about traffic. How many people came this week? Which channel sent them? Which pages did they land on, and which did they leave from? Which campaign worked?
Its unit is the visit. Its home is the marketing site. Google Analytics, Plausible and Fathom are web analytics tools at heart.
Product analytics: what they did next
Product analytics answers questions about behaviour. Where do people drop out of signup? Do the people who signed up in March still come back? What did this one customer do before they upgraded?
Its unit is the person, followed over weeks. Its home is the app. Mixpanel and Amplitude started here.
Why the line blurs
A customer's path crosses both. They read a blog post, come back from a newsletter, start a trial, use the product for a month, then pay. If the first half lives in one tool and the second half in another, the most useful questions fall in the gap between them:
- Which channel brings in customers who stay, rather than visitors who leave?
- Do people from search convert to paid better than people from social?
- Which landing page leads to the most revenue, not the most signups?
Each of those needs the traffic source and the later behaviour in one place, joined by the same person.
When two tools still make sense
If your product needs feature flags or experiments, a product tool like PostHog, Mixpanel or Amplitude does that, and Spreelytics does not. Many teams keep one of them for that work and use a lighter tool for traffic.
If you only run a content site with no signup, product analytics has little to measure. A web analytics tool is enough.
How Spreelytics handles both
Spreelytics reads one stream of events for everything. The same pageview that counts toward your traffic numbers also feeds funnels, retention and person timelines. So a filter you set on the overview, such as "visitors from LinkedIn", carries through to the funnel and down to one person.
The web side covers channels, sources, campaigns, pages and Search Console data. The product side covers goals, funnels, journeys, segments, retention and person timelines. Revenue from Stripe, Paddle, Polar or Lemon Squeezy is credited back to the channel that earned it.
There is no separate bill for each side. Every feature is on every plan except session replay and the in-app AI assistant, which are kept for Growth.
A quick way to decide
Write down the three questions you most want answered this quarter. If they are all about traffic, a web analytics tool will do. If they are all about in-app behaviour and you need flags or experiments, pick a product tool. If they connect the two, such as "which channel brings in customers who pay", you want one tool that holds both.
For the product tools side by side, see the best product analytics tools.