Hello There!

Lorem ipsum dolor sit amet, consectetur adipiscing elit,

Step-by-step Walkthrough: How to Implement Google Tag Manager v5 for your Android Application

gtm_v5

 

gtm_v5Google Tag Manager v5 is now all set with Firebase SDK for Apps, adding unique supplementary features to the Google Analytics arena.

Firebase was earlier a stand-alone company until Google purchased it in 2014. Google then tweaked Firebase as a whole new baggage for mobile app development, along with adding few obliging feature of Analytics to it. Firebase now includes tools for app development, like cloud messaging, database storage, hosting, etc. These tools can help us grow our app’s audience using push notifications and app indexing. Yes, Firebase Analytics sits right on top, pulling all the strings of the entire product.

In the previous blog, we had a walkthrough on how to implement tags with Google Tag Manager v4 in your Android application. Moving ahead, in this blog post, I will take you through the process of implementing Google Tag Manager v5.

Steps to set up GTM v5 in an Android Project
Setup Firebase
    1. Login to Firebase Console
    2. Create a Project and add your Application details as per the instructions.
    3. Download the google-services.json file and add it into your Android Application project as shown below.
      gtm

Image 1: Adding google-services.json file to your Android Application project

Add Google Tag Manager in Your Android Application
  1. Add Firebase SDK to your project in your Android Project. At the project level, add build.gradle file and include the google-services Plugin.

    gtm v5Image 2: Adding Firebase SDK  to your Android Application project

  2. At your app level, add the build.gradle file and include dependencies of both Firebase and Google Tag Manager

    androidImage 3: Adding Firebase SDK  to your Android Application project

  3. Create a Firebase Analytics Object and use it to track event by adding appropriate event name and its parameters.

    implement gtm v5Image 4: Creating Firebase Analytics Object in  your Android Application project

With these 3 steps, your Google Tag Manager v5 is now configured with your Android app. But we are missing out on something very important. The question you should be asking is:

Will setting up Firebase and GTM SDK be enough to track the event?  

Well, if we are using Google Tag Manager, it’s mandatory to configure a tag by setting the right triggering event to it. Hence, moving forward with GTM v5, with the features that it provides over the GTM v4 version, we can now control the event configuration with three different action types for a single event that is to be tracked.

Google Tag Manager Tag Configuration for Custom Events
  1. To start off with Google Tag Manager, first create a Container of Firebase type in Google Tag Manager Console :

    gtm console
    Image 5: Creating container

  2. We now begin with the configuration of an event in GTM. As opposed to the v4 tag configuration, v5 event tags are remarkably advanced in providing more actions. We have three actionable options in tag configuration :

    • Add  Event
    • Modify Event
    • Block Event
      Let us understand the strengths of these 3 actions by using it in our event configurations.

      1. Add Event
        Configure a Login event in Google Tag Manager v5 as shown below, for when the user logs into the app. For this use, let’s say the name of the event that fires if “new_login”

        android app
        Image 6: Tag Configuration - Add Event

        gmt v5
        Image 7: Trigger Configuration for the above tag

      2. Edit Event
        Post the successful tag configuration, we have an event for users logging in the app. But down the road, when the app is published on Playstore, we will be required to edit the name of the event that is being tracked from “new_login” to “Login”. Here’s how we can modify our existing Login event tag as shown below, without any efforts from app implementation.

        implement gtm v5
        Image 8: Tag Configuration - Modify Event

      3. Block Event
        Now, If user is signing up in the app for the first time, and it leads user to login automatically for the instance, then in this case we don’t require the Login event to be triggered in Firebase. The block event feature comes in handy for such an instance. Here is how you can use the feature of blocking the event on specific screen(i.e. Sign up screen) as shown below.

        android gtm
        Tag Configuration - Block Event

        google tag manager
        Trigger Configuration for the above tag

  3. Once the tags are configured, we will then need to publish the container, download it and add it to the Android Project. In assets -> container folder.

    google tag manager androidImage 9: Adding Container to Android Project

Please Note :

  • It is necessary to publish the container each time when new tags are configured in GTM
  • Adding the container file to the project is to be done only once when the container is published for the first time.
Concluding

We are now ready to run the application and verify the results as follows:

In the terminal, write following three commands:

gtm v5

View the logs for configured events by applying the filter of “D/FA” in Android Monitor,  or visit your Firebase Console for the same.

So, that’s it. This is how you can integrate Google Tag Manager version 5 in your Android app. Happy Tagging!

If you are stuck anywhere or need guidance while implementing the GTM v5 for your Android app, please feel free to leave us a comment in the section below and our Android experts will be glad to help you out.

Stream & Export your Google Anaytics data to Bigquery Guide

[vc_row][vc_column][vc_column_text]Google Analytics 360 Data BigQuery ExportAs a passionate Google Analytics 360 and BigQuery User, I always want to take quick actions on the current day data within a couple of minutes. And today, I am ecstatic that Google has rolled out a new streaming export feature. Google Analytics 360 users can now export their Google Analytics data in BigQuery within 10 minutes.

This enables you to carry out analysis and take actions six times within one hour using BigQuery which seems almost real-time data export. Aren’t you excited? Let me elaborate on just how awesome this new feature will prove to be!

Power of Unlocking Data Streaming Delivery Feature

All business giants who deal with tons of data points flowing into Google Analytics, require faster data access to identify high intent users, analyse internal promotions and quickly discover anomalies in your critical business metrics. Listed below are the few real-time actions that you can take based on your data:

  • Instant retargeting for higher conversions:
    In today’s fast-paced, dynamic world, every second counts. It is observed from the recent market trends that users are highly likely to convert if they get instant incentives. The sooner they come back to your website, better are the chances of them converting.

    Dynamic and instant remarketing approach will prove to be more promising and effective in driving greater engagements.
  • Real-time Prediction:
    This amazing feature will enable Data Scientist to run predictive algorithms in real-time. With quick download of data, predictions can be tested in a short span of time and new results can be used to retrain for better accuracies. One use case that analysts can make use of, is Predictive Lead Scoring. This will give marketers a score of leads with higher propensity to convert customers within a short span of time. And then automated emailers or push notifications can be sent to the leads where conversion rates can go up due to recency effect. Currently, with the data that is processed, predictions are carried out a day after and chances of conversion become comparatively slimmer.
  • Quick Issue Debugging:
    Frequent data updates in BigQuery will allow organizations to identify issues and help them to fix it quickly.
  • Taking data stitching to the next level:
    Business intelligence tools can also be empowered using raw, hit level, online-behavior data with offline data sources like CRM, call centres and POS data.

4 Easy Steps: Get Started with the all new Data Streaming Feature Now

You can start getting data more frequently by just changing your streaming preference option.

  1. Navigate to your Google Analytics 360 Admin settings
  2. Go to BigQuery Integration Page
  3. Click on Adjust link

You will now see a Streaming Preferences Options. Choose “Data exported continuously” option as shown following:

And voila! You are all set! And that too without any help from your go-to tech guy!

Got questions? Don’t worry, we got you covered!

Once you will opt for this feature, Google Analytics data will start streaming into your BigQuery project as fast as every 10 minutes. Note that this might take few hours to reflect in your BigQuery. As exciting as this is, I am sure this update must have lead to few queries for all of you. I am going to attempt and answer a few FAQs that we’ve experienced from within our team as well as our clients.

  • Is this chargeable? If yes, what is the cost?
    Yes, you will be. The new streaming export uses Google Cloud Streaming Service and that costs a $0.05 per GB. That’s why Google recommends that you choose your own streaming preferences so that you don’t end up with unknown additional cost.
  • Will I see changes in BigQuery?
    Yes, you will start seeing two new tables in your BigQuery cloud platform.
  1. ga_realtime_sessions: In this table, you will get the current day Google Analytics data.
  2. ga_realtime_sessions_view: This is a view - virtual table in BigQuery.

In the detailed section of ga_realtime_sessions_ table, you will also find information regarding the table’s Streaming Buffer if it is present. If there is no data in Streaming Buffer or table is not being streamed to (ga_sessions_intraday_), this section will be absent.

  • What additional data will I see?
    You will able to see updated BigQuery schema under ga_realtime_sessions_view_. Following fields are introduced : 

    1. exportTimeUsec - Unix timestamp when data gets exported to Google Cloud
      For ex. 1505981096384
    2. exportKey - It’s a combination of fullvisitorId, visitStartTime/visitID,
      exportTimeUsec
      Format : fullvisitorId:visitStartTime/visitID: exportTimeUsec
      For ex. 3601279501650676672:1505976859:1505981096384
    3. visitKey -  It’s a combination of fullvisitorId and visitStartTime/visitID
            For ex. 3601279501650676672:1505976859

If you don’t opt for the data streaming feature, then you will continue to see data streaming like you do today, which is about thrice a day i.e. every eight hours.

Concluding Thoughts:

All that which is captured through analytics tracking is included in this streaming export. Although be aware, data sources like AdWords and DoubleClick, Search console will be not included in same.

Happy data streaming!

What do you think about this new data streaming feature introduced by Google? I would love to hear your views and take on it. Please do write to me in the comments section below, I am looking forward to it. 

We at Tatvic also provide BigQuery Training for Corporates & Developers.[/vc_column_text][/vc_column][/vc_row]

10-Google Analytics Advanced Custom Segments for Marketers to Measure

Google Analytics Advanced Segments

Google Analytics Advanced Segments

Google Analytics Advanced Segments are one the most valuable tools in Google Analytics for someone looking to understand their business performance in a better manner. It is a way to quickly segment the traffic in Google Analytics.

Using Google Analytics Advanced Segments is much like mining for gold. It allows isolating specific types of traffic in your reporting.

Do you want to see reports for visitors only from a particular city? Or do you want to see how visitors from organic search behave compared to visitors from paid search? Advanced Segments can do these for you and so many other things. In this blog, I shall demonstrate 10 must-have Advanced Segments to up your analytics game.

1. Mobile Traffic (Excluding Tablet)

It’s useful to know how many people are visiting your website from their mobile phones and how many are using tablets.

This helps you ascertain how important it is to have mobile-friendly sites and understand how their performance and conversions differ across devices.

Google Analytics has a pre-defined Advanced Segment for mobile traffic, but this includes tablet traffic too. Since mobile and tablets can be very different, it makes sense to look at it individually.

Google Analytics groups iPhone and iPad traffic into one group: Operating System = iOS. You can exclude screen resolutions of iPad from this segment, meaning it should only show you mobile traffic, excluding tablets.

Mobile Traffic (Excluding Tablet)

Mobile Traffic (Excluding Tablet)

2. Traffic Source with Conversions

For every business with an online presence, it is imperative to know where the conversions are coming from. Below are some advanced segments that you should look at, to know the converting visits from specific traffic sources:

  • Organic Visits with Conversions
  • Social Visits with Conversions

For this social media traffic segment, you can use the following regex to capture the majority of social sites.

3. Not Provided Segment

Missing keyword data (Not Provided) is a big hassle for marketers and this segment can tell you exactly how much of a pain it is. To see the impact of missing data, I would recommend using these two segments:

  • Not Provided Data
  • Excludes Not Provided Data

Compare these two segments with each other to see whether they contain keywords that are actually valuable to your business. Analyse content report, conversion report to understand the difference between these two types of users.

4. Keyword Length 

Knowing what type of keywords are bringing most traffic, most interactions and most conversations on your site are really insightful in terms of getting to know what searches are bringing the most users to your website.

I use the following segments to analyze the important terms that are driving traffic to the site. I’ve also provided the regex that I use to create these Google Analytics Advanced Segments

  • 1 Word Keywords -  Regex ^s*[^s]+(s+[^s]+){0}s*$)
  • 2 or 3 Words Keywords - Regex ^s*[^s]+(s+[^s]+){1,2}s*$
  • 4+ Words Keywords - Regex ^s*[^s]+(s+[^s]+){3,}s*$

Keyword Length

Keyword Length

5. Cart Abandoners by Traffic Source

If you are an eCommerce site, then there are quite a few scenarios when you probably wonder why people abandon your cart without checking out. The answer tends to vary largely, often by source. Explore the differences in cart abandonment by creating a segment by traffic source.

Cart Abandoners by Traffic Source

Cart Abandoners by Traffic Source

In the above example screenshot, this segment gives you data on the cart abandoners visiting from Facebook. The same can be replicated for any other traffic source.

6. Business Hours vs. Off Hours

Does the conversion rate of your website change between working and non-working hours? This segment compares traffic received during and after business hours. Adjust this segment to align with your business hours and then apply this to reports to investigate differences in site performance both before and after work hours.

7. Depth of Visits

This segment is a good way to understand how engaged your visitors are on your website. Use this segment to see the number of visitors viewing three or more pages on your site. You can also enhance this segment to understand which traffic source keeps your visitors most engaged.

Bonus Advanced Segments

Here are some more Google Analytics Advanced Segments you might want to consider, depending on what makes a difference on your website.

  • Segmentation by demographics.
  • Segmentation by a Technology platform.
  • Segmentation by Geography.
  • Segmentation by Visitor type. (New vs Returning, Registered vs Non-registered)
  • Segmentation by Landing Page.

Concluding.

The list of Advanced Segments you could create is endless. You will have to decide what is most valuable to you. It is very important to use the data wisely, try and compare data to other segments, and make informed decisions.

Moreover, if you are a Google Analytics 360 user, you can create these advanced segments and export them to DoubleClick For Publishers in order to target a customized audience to achieve a greater conversion rate. Read this blog and learn how to create an advanced segment and export it to DFP.

If there are other advanced segments that you use and you absolutely think are a must-have, please tell us about them in the comments section below. We would love to know!

All You Need to Know About Targeting Customized Audience in DoubleClick For Publishers using Google Analytics 360 Audience Segment

Targeting Customized Audience in DoubleClick For Publishers using Google Analytics 360

Targeting Customized Audience in DoubleClick For Publishers using Google Analytics 360

Wouldn’t it be awesome if you could increase your Ad Revenue and Click-Through-Rates by using Google Analytics audience behavior? In this blog, I am going to show you just that. Let’s start with the basics of how to target a customized audience from Google Analytics 360 and export it to DoubleClick for Publishers. As a follow-up to this blog, I shall also come up with some eye-opening use cases and benefits that I’ve been able to deliver myself, using this re-marketing strategy.

DoubleClick For Publishers (DFP)

is a Google product that provides a way for online publishers to serve ads on their websites or Mobile-sites or Apps. DFP is available in 2 different versions based on the features and value propositions. (Source: Google)

DoubleClick For Publishers Premium: DFP Premium which has inventory in millions and wants to sell their inventory directly to the advertiser via Programmatic or direct need to use this feature.

DoubleClick For Publishers Small Business: DFP Small Business is a free ad management solution that helps growing publishers sell, schedule, deliver, and measure all of their digital ad inventory.

Key Takeaways:

When two tools as powerful as Google Analytics 360 and DoubleClick For Publishers combine forces, the benefits are bound to be valuable. Here are some key benefits worth listing:

  • Targeting the audience who are coming from a particular channel or source/medium
  • Using GA custom metadata information to segment the audience for Remarketing. This maximizes accuracy and minimizes the costs
  • Figuring out which keywords are helping to generate revenue for your business in terms of SEO
  • Understanding those users’ customer persona that generates more revenue. Also, know, from which inventory

What is Google Analytics Segment?

The segment of data is a subset of your Google Analytics data. Example: If I consider the entire set of users, one segment of users from a particular city and another segment of users who purchase a particular line of products. Segments will help in creating audience segments as per the user requirement with all the appropriate conditions.

(Source: Definition by Google Support)

Segments can be of 3 types:

  1. Subsets of users: Defined as, those users who have viewed the Entertainment section but didn’t view any section related to the News
  2. Subsets of sessions: Example All sessions during which a sports section read
  3. Subsets of hits: For example, all hits in which pageviews were greater than 5

You can create an audience with users who perform some actions or a set of actions on your website which clearly showcases the intent of the users. Here are the examples for the same:

  • Viewed more than 5 pages & “News enthusiasts”
  • Spent more than 5 minutes & viewing the “Sports” category articles
  • Are high-value users who are having pages/sessions of more than 5 or 7 or 10
  • Serving different ads based on those users who subscribed and non-subscribers

Carrying Out Custom Tagging in Google Analytics

Custom Tagging is done based on Custom Dimensions available in Google Analytics. If you have multiple categories on your website, place a custom dimension for that page and assign the category it belongs to. This way you can segment visits that include that category.

  • Example:  ga(‘send’, ‘pageview’, {‘dimension2’:  sports’});

If you have multiple authors/article tags on your website, place a custom dimension for that page and assign the author/article tags it belongs to. This way you can segment visits that include the author/article tags.

  • Example-1: ga(‘send’, ‘pageview’, {‘dimension2’:  manish sharma});
  • Example-2: ga(‘send’, ‘pageview’, {‘dimension3’:  demonetisation});

How to Create Audience Segments and Export to DoubleClick For Publisher

Step-1: Create a segment in GA 360.

How to create a segment

How to create a segment

Step-2: Build an Audience

Building audience

Building audience

Step-3: Select the respective view which will be the source from where we need to select the data and click next to enable remarketing

enable remarketing

Selecting the view from the source to enable remarketing

Step-4: Export to DoubleClick For Publisher

Exporting audience to DFP

Exporting audience to DFP

  • Select the Audience destination which is DFP of your respective network code.
  • Click on Enable button

Benefits of DoubleClick For Publishers and Google Analytics 360 Integration:

We can view the publisher reports data along with GA 360 standard dimensions and metrics:

  • Affinity-Based Content Classification:

    Content Group of data in GA 360 along with the standard DFP metrics. Based on these content grouping we can create a segment of the audience that is interested in a particular segment generating more revenue for the company.

  • Monetizing Publisher Referrals:

    Knowing traffic sources that provide top-performing impressions along with the DFP metrics. Accordingly, we can plan our marketing budget to make sure to invest our money in the right traffic source to generate ROI.

  • Monetizing Publisher Pages:

    Once you know the revenue per page or cost per page, your marketing team can modify their budget plan based on the type of pages from which the revenue is generated and where exactly the cost is too higher. It provides the comparison between investing the amount on a particular page and expecting a return on the same.

  • Know Your Best Content-Type:

    Know whether or not you are investing your money in the correct content where Ad Revenue or if the CTRs generated are low. You can determine the same by knowing which content is driving more revenue or any other DFP metrics.

Concluding Thoughts:

To conclude, GA 360 will provide you with as many numbers of segments as you would require to customize and ensure your users are better engaged. To give you a better sense of audience segments that have great impacts on your business, I invite you to check out

7 Absolutely Must-Have Google Analytics Advanced Segments for Marketers for Unlocking Actionable Insights.

So, what are you waiting for now? Let’s create an audience segment and export it to DFP and start targeting. Are there any difficulties that you are facing while either creating an audience in GA or exporting it to DFP? Tell us about it in the comment section and we’ll be happy to help!

Reduce Your Website Downtime with Real-Time Alert Management with Anomaly Detection Tool

Anomaly Dectection

Anomaly Dectection

Anomaly Detection is an in-house tool by Tatvic that identifies certain user behavior or actions or a set of actions by users which do not conform to an expected pattern(s) in a dataset. Expected patterns can be generated from historical data sets or idealistic data sets that you can configure as well - we’re big on customizations at Tatvic!

This blog is the second blog on this tool where I am going to focus on various use cases and how Anomaly Detection Tool can help achieve these goals. We will see how Google Analytics Data and Anomaly Detection collaborate beautifully for metrics with:

  • Only data
  • Dimension filters
  • Dimension values
  • Dimension values with dimension filter

To get a detailed sense of Anomaly Detection as a tool, I invite you to read the first blog on the tool where we have elaborated on what is Anomaly Detection, the importance of Anomaly Detection, methods and Case Study.

Anomaly Detection Use Cases:

For every use case, Anomaly Detection Tool extracts real time data from Google Analytics and performs anomaly check depending upon reporting option(Intraday / Daily). All these use cases can be used with or without segments. Let’s discuss each of these use case in detail and see how they can fit into your business.

Metric only data

Every business has some of the key performance metrics which impacts business significantly. For instance Revenue, Average order value, E-commerce conversion Rate are key indicators for an e-commerce store whereas Pageviews, Users, Sessions can be more important to Lead Gen site. Based on your business KPIs, keep your eyes open and be vigilant about how these metrics are doing on a regular basis.

Metric with dimension filters

Sometimes in business, we also want to know how a metric is performing with regards to specific dimension values. For instance, I want to be notified if my Revenue from City A and/or Browser B has increased or decreased significantly. Anomaly Detection digs deeper into your dimensions and gives you an idea of how a set of dimensions affect your critical business metrics.

Metric with dimension values

With this tool, you can set a filter for some of the values of dimensions but say you want to set anomaly on top “N” values of dimensions. For instance, you know that you have 10 various Source / Medium from which your website received healthy traffic. With this tool, you can track the spike or drop from any of these Source / Medium real time.

Metric with dimension values with dimension filter

This is when you need Metric with dimension values and filters combined. Let’s extend the examples from our previous uses cases and let’s say I want to set an anomaly on top 10 Source / Medium from City A and/or Browser B. Guess what? You can do this with the help of Anomaly Detection Tool.

About Anomaly Alerts

Anomaly alerts can be reported either on intraday basis or daily basis. In Intraday reporting anomaly detection is performed several times a day while on daily basis anomaly detection is performed on previous day’s data and reported to value found out to be Anomalous. Anomaly Detection alerts also provide the time since the anomalous trend in data is observed.

Recently one of our clients received an alert for a drop in traffic from a specific browser. Anomaly Detection Tool reported the alert to the client within 3 hours of the drop. The client did an inspection on it and turned out that there was some javascript error on the page which led to the drop in traffic. Client team fixed the issue and traffic from that specific browser became normal on the same day.

Does the Anomaly Detection Tool sound like something that you would like to know more about? Are there any anomaly issues that you face recurrently? Tell us how you track your spikes and drops in traffic in the comment section below.

To request a demo of the tool, I invite you to check out the tool and leave a demo inquiry with our team.

Pay Attention to Your Users’ Actions by Tracking Client ID in Google Analytics and Stay at the Top of Your Game

Google Analytics is a ginormous platform that lets you track the user actions and behavior in the digital era of merchandising and provides insights based on those user actions, in various ways. There are many root node of Google Analytics which hold hands together in providing insights, such as customizable reports, real time visitors views, automated data collection, easy integrity with other platforms, etc. But to make these specified features significant, in the core of Google Analytics tracking lies the Client ID. After we go through the benefits of Client ID, we will grease the wheels on how to track Client ID from iOS device.

What is Client ID ?

Client ID can be described as a unique identifier for any user, limiting the user’s sphere to a specific devices or a browser. It can be considered as a pivot point for the data relative to a unique user. It also contributes majority in the Audience report in Google Analytics to provide measurement of user count with a cardinality of New Users and Returning Users. To sum up, Google Analytics is totally dependent on Client ID to measure the audience of your application, and using Client ID Google Analytics also provides brief detail on the Active Users for a specific time span.

Let us now capture the essence of Client ID and understand how it can be used in visualizing data in an eloquent way. We will walk through two different use-cases that utilize Client ID in visualizing the data.

  1. Mapping of events at user level :
    Assume we are a lead generation marketer and we have successfully implemented event tracking for various actions of the users. The manager now demands the count of those users who have performed some combinatorial action on a day or some specific day.
    In this case, Client ID will be a root node and behave as a unique identifier for each user. It will return the events performed by a particular user, fulfilling the combination requirement.
  2. Targeting a set of audience :
    Implementation of Client ID will give a facility to make a segment based on their activity and can be targeted as an audience to lead conversion. For every business, it is very important to know about the users, their activity and conversion. For example - There are 100 users who have visited your website. They take a set of actions and then exit. Client ID as a dimension will help businesses to find the user journey and these users can be targeted to see through a transaction or lead generation.

A list of ClientID can also be exported to Adwords and various remarketing activity such as personalized recommendation or showing products depending upon their past behaviour.

Looking on the other side of the coin, with the advantages of Client ID, we must also be aware of the limitations that it has. Client ID is a standard dimension of Google Analytics and unfortunately, we cannot use the Client ID in Custom Reports that we use to visualize data according to our requirements. But guess what, we can track the Client ID in a custom dimension and use it in Custom Reports to analyze the data.

Client ID Tracking Implementation

Moving further, lets take a look on how to track Client ID from iOS device’s either in a custom dimension or in an event through Google Tag Manager using the dataLayer method. Follow the below steps :

  1. To send Client ID in GA using dataLayer your app should have GA SDK as well as GTM SDK installed. Follow below mentioned links to install and initialize GA SDK and GTM SDK in your iOS project.
  2. Once SDKs are initialized, one instance will be created of GA Tracker which will be used to get the Client ID. After getting a Client ID a dataLayer instance will be created to push Client ID into a dataLayer.
    Below mentioned code snippet will get Client ID and push it into a dataLayer. This mechanism should be implemented inside the first screen of your application. Write below code in the viewDidLoad method of your ViewController.

                                          OR
    Add the variable clientId in the openScreen DataLayer as mentioned in this blog

    google analytics

    DataLayer push code snippet holding Client ID

  3. Since we are using Google Tag Manager it is necessary to configure a Tag in GTM which holds the setting to track the Client ID in Custom Dimension.iOS

    Tag configuration with setting Client ID in Custom Dimension.

    NOTE:
    The custom dimension for Client ID should be User level scope in Google Analytics. This will help you analyze and understand actions of the user.

With this step, we are now through with implementation of Client ID tracking. Once Client ID starts getting tracked in Custom Dimension, you can generate custom reports and visualize the data as per your requirements.

For any assistance in Google Tag Manager setup or Tag Configuration you can visit our blog  How to Implement Google Tag Manager in iOS Swift - Part 1 of 2 or feel free to leave a comment in the section below.

Bot Icon
Bot Icon

Tatvic Bot

Explore About Tatvic and Services