What is digital analytics?
Digital analytics is the measurement and analysis of customer behaviour across every digital channel a business operates: website, mobile app, email, advertising platforms, support and in-product usage. It is broader than web analytics, which covers a single website, and its central difficulty is joining those channels into one coherent picture.
Compared
Three overlapping disciplines The labels are used loosely and the distinction is one of scope rather than of technique. Knowing which one someone means saves a lot of confused meetings.
| Feature | Web analytics | Product analytics | Digital analytics |
|---|---|---|---|
| Scope | One website | One product, usually behind a login | Every digital channel |
| Primary question | Where does traffic come from and what does it do? | What do users do inside the product, and do they stay? | How does the whole journey perform end to end? |
| Core unit | The session | The user | The customer across channels |
| Typical owner | Marketing | Product | Analytics or data team |
| Hardest part | Blocking and attribution gaps | Defining activation honestly | Identity resolution across channels |
What it covers beyond the website
Digital analytics takes in every place a customer meets you digitally, and each source has its own shape and its own failure modes.
- The website: traffic, campaigns, conversions.
- Mobile apps: installs, sessions, in-app events, which are measured through a completely different SDK model.
- Email: sends, clicks, and open rates that are now unreliable because mail proxies pre-fetch tracking pixels.
- Advertising platforms: impressions, spend and platform-reported conversions, which almost never match your own numbers.
- In-product usage, support tickets, and revenue systems.
The value is in the joins, and the joins are the hard part. Without a shared identifier, each channel is a separate report and the customer journey stays hypothetical.
Live demo
See it on real data. The live demo is a fully populated dashboard on demo traffic, with no signup and no card.
Open the live demoWhere digital analytics programmes fail
No shared identity
Without a common key, usually an account id or a hashed email, five channels produce five disconnected reports and no journey. This is the single biggest cause of failure.
Platform numbers taken at face value
Ad platforms report conversions using their own attribution and their own windows, and they always report more than your analytics. Both are internally consistent and neither is the truth.
Metrics that mean different things per channel
A session in a mobile SDK, a session in web analytics and a session in an email tool are three different constructs. Adding them produces a number with no meaning.
Modelling before measuring
Teams build a unified data model before any single channel is instrumented correctly. Get one channel honest first, then join.
A realistic starting point
Most companies under a hundred people do not need a warehouse and an identity graph. They need three things done properly.
- Consistent campaign tagging, so every channel that can carry a UTM does.
- One place where conversions and revenue are recorded, so the outcome layer is not split across tools.
- A self-reported source field at signup, which catches the channels no instrumentation sees.
mrkr covers the web and product side of that: pageviews, campaigns, custom events and revenue in one place, with an HTTP API so backend and app events land in the same stream. It is one input to a digital analytics practice, not the whole of it, and pretending otherwise would not help you.
FAQ
Is digital analytics the same as web analytics?
No. Web analytics measures a website. Digital analytics covers every digital channel including apps, email and advertising, and its defining work is joining those channels into one view of the customer. Web analytics is one component of it.
What tools do you need for digital analytics?
At minimum, web analytics, an app SDK if you have an app, your email platform, your ad platforms, and somewhere to join them, which is often a warehouse. The joining layer is what distinguishes a digital analytics practice from a collection of dashboards.
Why do ad platform conversions never match my analytics?
Different attribution models, different lookback windows, and the platform crediting view-through conversions your analytics never sees. Platforms consistently report more. Use your own analytics for cross-channel comparison and platform numbers for optimising within that platform.
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