Analytics Tools include web analytics and mobile app analytics.
This is the Big List of 200+ analytics tools which are currently available in the world.
Of course, most websites have to communicate with the backend (i.e. databases), and the codes may be written in PHP, Python, Java, Ruby, Asp.Net, etc. We aren't going to cover this topic.
The major objective of web analytics tools is to track data on websites.
Web analytics tools have been developed to solely track data for websites, whether the websites are optimized for desktop screens or mobile screens.
Websites identify unique users with cookies.
Cookies have been used on websites for many years. Cookies enables users to perform certain actions on websites. For example, the first time a user visits a ecommerce website and places an item in the shopping cart, but hasn't completed the entire transaction. A cookie has been placed on this user's web browser (e.g. Chrome) in order to remember him/her (and the item he/she places in the shopping cart). The second time the same user comes back to the ecommerce website and browses to his/her shopping cart. He/she sees his/her item in the shopping cart and continue to complete the transaction. Without a cookie, the website would not have been able to remember the shopping cart item for the user.
For web analytics tools, cookies are placed on users' web browsers. During subsequent visits of the same user to the website, the website will remember the user is the same person (cookie).
Below is an example of how the web browser cookie looks like.
HTTP/1.1 200 OK Set-Cookie: AHSID=AARONmxn67; Domain=example.com; Path=/; Expires=Wed, 13 Nov 2018 15:18:00 GMT; Secure; HttpOnly
The cookie's name is AHSID, and its value is AARONmxn67.
The cookies which were previously stored on the web browsers won't work for identifying unique users when:
For example, an iPhone runs the iOS operating system. Mobile apps running on iPhones (and/or iPads) are coded mainly in Objective-C and/or Swift.
For example, an Android phone runs the Android operating system. Mobile apps running on Androids are coded mainly in Java.
The major objective of mobile app analytics tools is to track data on mobile apps.
Depending on the specific mobile app analytics tool that you are using, usually a SDK (software development kit) must be implemented on your mobile app. When the SDK has been implemented, the mobile app analytics tool starts to track the data.
Note that mobile phones from different vendors are installed with different operating systems that are incompatible to one another. SDKs are operating system dependent.
Mobile app analytics tools have been developed to solely track data for mobile apps, whether the apps are installed on iPhone/iPad (i.e. iOS) or Android. Note, we aren't going to discuss mobile app analytics tools for mobile operating systems other than iOS and Android.
User -> Mobile -> iOS App -> SDK (for iOS) -> Data Collection -> Data Processing -> Data Reports Appears in Mobile App Analytics Tools User -> Mobile -> Android App -> SDK (for Android) -> Data Collection -> Data Processing -> Data Reports Appears in Mobile App Analytics Tools
Mobile apps identify unique users with some unique device / operating system IDs.
iOS uses IDFAs (Identifier for Advertisers) to identify unique iPhone (and/or iPad) users. An IDFA is a 32-digit string in which the format is 8-4-4-4-12. Example of an IDFA:
Android uses AIDs (Advertising IDs) to identity unique Android phone users. An AID is a 32-digit string in which the format is 8-4-4-4-12. Example of an AID:
IDFAs and AIDs have some issues when they are used for identifying unique users on iPhones and Android phones respectively.
On websites, you identify unique users with cookies. On mobile apps, you identify unique users with IDFAs and/or AIDs depending on the type of phones and/or operating systems.
The reason behind this is for in-depth data analysis of your users, you will want to build the click stream (or even the conversion funnel) of each user.
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