The basic concepts

Overview of the basic functions: Tracking, User Profiles, Events, User Properties, Opt-In, Custom Reports, Metrics and Funnels

This article explains what MarvelMetrics is and how it works. It explains what kind of data you can import or track and which reports you can create. The document is an overview - you find details on each topic in other articles.

MarvelMetrix - your analytics platform

MarvelMetrix is an analytics platform: It gives you the tools to create reports from data collected from different sources. The platform itself is data agnostic — it does not care where the data comes from nor what data you send.

You can adapt it precisely to your needs:

  • Web pages
  • Email campaigns
  • iOS or Android apps
  • Desktop applications
  • Games
  • IoT devices

The basic idea of MarvelMetrics is to collect data about the users of your web page, app or game to build user profiles. These profiles consist of events — actions a user performed — and user properties.

MarvelMetrics calculates the analytics reports based on these user profiles. They tell you how well a specific group of users converts, how much time and money they spend on your web page, which products they download, and what they put into their cart.

MarvelMetrix always calculates the reports on the full set of data. It does not interpolate or sample data. You can create reports retroactively from all data that is available in the tracking project.

The calculations are swift - it usually takes less than 1 second to get the reports.

Collecting data

User profiles

MarvelMetrix collects data in user profiles. A user profile consists of two types of data:

  • Events
  • User properties

You collect these events and properties from your web page, app or game using an SDK that we provide. The SDK sends the data to our tracking server where it’s collected and processed.

We also offer an API that you can use in case we can’t provide an SDK for your specific needs.

Lawfulness of the processing

Data that you send to us is processed and collected on your behalf within the scope of the GDPR. Please note that you either need the consent of the users (opt-in) or collect the data based on legitimate interest.

Please remember Art. 9 GDPR:

Processing of personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person’s sex life or sexual orientation shall be prohibited.

MarvelMetrix also does not permit you to track any security-related or sensitive data such as credit card data, bank accounts, social security number, identity card numbers, passwords.

User IDs

MarvelMetrix assigns a unique ID to each tracked user. The user ID is the link that ties the events and properties together into a user profile.

The ID can be anonymous (a random number/letter combination) — or an ID that you provide from another source like your customer database (e.g. customer number, email address).

User properties

User properties are values that describe a user, but there is no temporal interest in the values.

Examples for user properties are:

  • returning visitor: yes/no
  • customer: existing/new
  • operating system: Windows, macOS, Linux
  • country
  • year of birth
  • shoe size
  • ad campaigns

All these values are possible user properties you can track with MarvelMetrix.

Of course, not all of them are relevant for your specific setup. E.g. if you sell software, the operating system might be relevant to you. If you have an online store that sells shoes, the shoe size is what matters.

It is tempting to collect all the data you can get, but please restrict the collection to the minimum of information that is relevant to your business.

It’s up to you which values you want to track to create a valuable user profile that helps you understand your customers.

You use these values to segment the users in the reports to answer questions like:

  • How many Mac users downloaded my product?
  • From where do most of the buyers come?
  • Which ad campaign works best?


Events — in contrast to user properties — happen at a specific point in time. They can even occur multiple times - e.g. when the user adds multiple items to the shopping cart or downloads several products.

Examples for events are:

  • Page visited
  • Product downloaded
  • Level completed (Game)
  • Added item to the cart
  • Finished purchase
  • Email opened
  • Link in email clicked

You can add properties to events to describe them in detail:

  • Shop: Product name and number of the item added to the cart
  • Web: Page visited, referrer, ad campaign
  • Game: Level completed, remaining health points, time, number of tries

Use the events in your reports to answer questions like:

  • How many users visited a page?
  • What was the average number of products bought per user?
  • What is the conversion rate from visit to purchase?
  • How much money does an average user spend in my shop?
  • How many per cent of the players complete level 5 after they completed 4?

Server-side Opt-In and Opt-Out

The MarvelMetrix SDKs use parallel server-side and client-side opt-in / opt-out. The client side controls the sending of the data, the server side controls the recording and processing.


With the client-side opt-in there is no transfer of tracking data to the MarvelMetix server until the user has agreed to the processing of the data. In case of a revocation of the consent no further data will be sent to the server in the future. The consent or rejection is stored in the form of a cookie in the user’s browser. Opt-Out cookies do not contain any identifiable user data.

In the case of tracking with a legitimate interest, an opt-out cookie will be set if the user objects.


MarvelMetrix stores events and properties only for known users — the server discards all other tracking data. Deleting a user from the database not only erases his data but also disables future data collection. There’s no data left in the database for an opted-out user - not even the information that the user does not want to be tracked.

To track users, you have 2 options:

  • If you are tracking the user with users’ consent: Send the create user message with the parameter ‘opt-in’ after the user gave his consent.
  • If you are tracking the user with a legitimate interest, send the create user message immediately without ‘opt-in’.

This server-side opt-in/opt-out has the advantage that tracking is globally disabled for a specific user ID — even if the user logs in from multiple devices using the same account. The user can also withdraw his consent from email tracking (tracking pixels).

A user requires 2 pieces of information to withdraw his consent:

  • the user ID
  • the ID of the project

MarvelMetrix provides an easy way to opt-out for web projects using a snippet that you can add to the privacy section on your web page.

If you track the user from an app or game, provide an easy to find button in the user interface where the user can withdraw his consent.

Cross-site tracking

MarvelMetrix, by default, creates unique IDs for each user per web page. Imagine that you have 2 domains: One is your marketing page, and the other is the checkout page which on a separate domain. Cross-site tracking ensures that the user shares the same ID on both domains — adding events to the same user profile.

Cross-device tracking

Tracking users across devices (e.g. tablet and mobile phone or desktop) is only possible if there is a common way to identify the user. E.g. the user is using the same account for your service or if he uses a personalized link that contains a user ID.

Combining user profiles

MarvelMetrix allows you to combine multiple tracking profiles into one. This process is called aliasing. Start tracking a user independently from multiple sources — e.g. email, web page and app. Create an alias if you find a way to tie the profiles together later — e.g. when the user logs into his account.

Reports & Analytics

You can currently create 2 types of reports in MarvelMetrix. We’ll add more types in the future such as A/B testing and cohort analysis.

  • Metrics
  • Funnels

MarvelMetrix calculates the reports always on the full data. No sampling — no interpolation. You can apply filters and segments at any time, and you can even create reports retroactively. The reports are displayed instantly (the average response time is less than 1 second).

Metrics reports

Metrics show you the change of a value over time.

Number of events

This metric counts all occurrences of a particular event. Events can happen multiple times per user.


  • Number of page views
  • Number of product downloads
  • Number of items sold
  • Number of emails sent

You can filter the events by event properties — e.g. to only see page views on a specific page.

Number of users

This metric is similar to the number of events metric but in contrast, only counts each user once.


  • Number of visitors on your web page
  • Number of newsletter signups
  • Number of users who completed a purchase

You can apply event filters — e.g. to only count users who have visited a specific landing page.

Average number of events per user

This metric calculates the average number of events a user performed.


  • The average number of pages visited per user
  • The average number of levels completed in a game
  • The average number of product downloads
  • The average number of songs played

You can, of course, apply a filter — e.g. see the number of times a user plays a specific song.

Average value per event

You can calculate this metric on events with number properties.


  • Average order value
  • Average playtime of a video
  • Average time on a page

Sum of a value

Use this metric to calculate the total sum of a property value.


  • Revenue in your store (daily, monthly, annual)

Average sum per user

This metric calculates the average sum of an event property value per user. The user must not necessarily have performed the event.


  • Calculate the average value of a web page visitor coming from an ad campaign

Average sum per active user

This metric calculates the average sum of an event property value per user who has performed the specific event.


  • Customer lifetime value (calculated on orders)

Conversion rate

The conversion rate is the relative number of users who have performed 2 events in sequence.


  • Web page visits -> newsletter signup
  • Email open -> click on link
  • Product download -> purchase

Average time between events

This metric is similar to the conversion rate but calculates the average time between two events.


  • Average time between starting a trial and making a purchase
  • Average time for completing a game
  • Average time between 2 purchases

Funnel reports

Funnel reports show you how users propagate through a series of events. They are similar to a conversion rate but with multiple steps.

For example an online store might have the following sequence of events that lead to a purchase:

  • A user visited a product page
  • The user added a product to the cart
  • The user visited the checkout
  • The user completed the purchase

Each of these steps takes the user closer to the goal of completing the purchase - but not all webpage visitors go through all steps. Some leave the funnel earlier.

The funnel chart shows you where users drop off and where you can make the most significant improvements in the purchase process.

  • If the users add items to the cart but don’t visit the checkout page you might check the placement of the checkout button
  • If the users visit the checkout but don’t complete the purchase you should check what’s holding them back. Too many fields in the checkout-form? Captcha? Payment method not supported?

The same applies if you use funnels to optimize a game. The players complete levels 1-6 without problems, and there’s a significant drop-off between level 7 to 8? Level 7 is what you should check.

Funnels also help you to analyze issues that occur suddenly — seeing a drop-off in your revenue? Create funnels retroactively from the events in your data set, including filtering and segmentation, to find the root of the problem.

Filtering users

Create filters that only show a distinct group of users or exclude specific users from the reports. You can build filters from any user property with value comparisons:

  • Number properties can be filtered with greater, less, equal or not equal
  • String properties can be filtered with equals, contains, starts with, ends with

User property filters can be combined using and and or logic.


  • See only users that come from Germany and use the Google Chrome on Windows.
  • See only users that use a mobile phone from Apple.
  • See only male users that come from a specific ad.
  • See only users that come from Twitter.
  • Exclude all British users from your metric.


Use segmentation to build groups of users and compare their values for a metric or funnel. You can build segments from any event or user property.


  • Compare how users from different countries propagate through the funnel.
  • Compare the number of downloads of your software from Windows, macOS and Linux.
  • See how the conversion rate differs for your ad campaigns.