Half the analytics frustration I meet in SaaS companies is not a broken setup. It is a correct setup of the wrong kind. GA4 configured beautifully, reporting sessions and sources with confidence, while the questions the business actually argues about (activation, retention, which feature earns the renewal) go unanswered, because nothing was ever built to answer them.
So before comparing tools, compare the questions.
Two kinds of questions
Web analytics is built around the visit. Where did it come from, what campaign, which landing page, did it convert. It exists to answer one master question: is the acquisition machine working? For an e-commerce store, where the visit and the purchase live in the same session most of the time, this is close to the whole game.
Product analytics is built around the person over time. What did this user do in week one, did they come back in week two, which behaviors precede an upgrade or a cancellation. Its master question: is the product keeping the promises marketing made? For a subscription business, this is where the money actually lives, because revenue is not won at the conversion, it is won at every renewal after it.
The confusion happens because both tools show events and funnels. The difference is the spine: sessions versus identified users across months. You cannot compute a retention curve from session-shaped data, and no amount of GA4 configuration changes that shape.
Which one you need first
Be honest about where your revenue decision pressure is:
- E-commerce, lead-gen, content: web analytics first. Your leverage is traffic quality and conversion rate. Product analytics concepts apply loosely at best.
- SaaS, apps, anything subscription: you need both jobs done, but the product side is usually the starving one. Companies default to installing GA4 because it is free and familiar, then wonder why churn is a mystery. If trials sign up but do not convert, or customers cancel and you learn about it from the invoice, your missing instrument is product analytics.
- Marketplaces and products with a long sales cycle: the deciding factor is the handoff. Your funnel spans anonymous visitor to known account, and the tool question matters less than whether the identity join survives that crossing.
The signs you are running the wrong kind
You are running web analytics where you need product analytics if: nobody can say what activation is, retention is computed quarterly in a spreadsheet by someone who sighs, and "engagement" in your reports means session duration rather than anything a PM could act on.
You are running product analytics where you need web analytics if: you know exactly which features power users touch but cannot say which channel produces customers who stay, and your acquisition reporting is whatever the ad platforms claim about themselves. (The platforms grade their own homework; that failure mode has its own write-up.)
Do you need two tools?
Eventually, often. On day one, rarely. The pragmatic paths I recommend:
- Subscription product, early stage: one product analytics tool (PostHog and friends will also cover basic web questions acceptably), and resist the urge to run a second stack. My detailed comparison of the two philosophies is in GA4 vs PostHog.
- E-commerce: GA4 or a privacy-focused alternative for the web side. You likely never need a product analytics tool in the strict sense.
- SaaS at scale: both, with a deliberate identity bridge: the anonymous marketing visitor becomes user 4711 at signup, and that join is instrumented and tested, not assumed. This bridge is where most two-tool setups quietly fail, and it is the reason funnel numbers stop at the signup wall.
The part that matters more than the choice
Whichever kind you need, the tool is the cheap part. The expensive part is deciding what activation means for your product, which events define the funnel, and how identity flows from first visit to paying account. That thinking is portable across every tool; skipping it is not survivable in any of them. I wrote up the funnel side, including how to find a real activation metric, in how to track a SaaS funnel that predicts revenue.
And if you already have both tools installed and they disagree with each other and with the database, that is not a reason to buy a third tool. That is an instrumentation audit, one week of tracing numbers to their sources, and it ends the argument for good.