10-Google Analytics Advanced Custom Segments for Marketers to Measure

Posted on September 22, 2017 - 5:50 pm by Ravi Pathak

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)

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

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

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!

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

Posted on September 12, 2017 - 12:58 pm by Ravi Pathak

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.

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.
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 :

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.
- Objective-C
  - Install and initialize GA SDK
  - Install and initialize GTM SDK
- Swift
  - Install and initialize GA SDK
  - Install and initialize GTM SDK
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
```
DataLayer push code snippet holding Client ID
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.
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.

Implementation User ID Google Analytics [Free User Guide]

Posted on August 24, 2017 - 2:30 pm by Ravi Pathak

user id implementation

In today’s world, people can interact with your business through multiple touch points, thanks to a large number of devices. This means their behavioral data is split into silos.

Analytics is all about how your users behave. Do you ever think of how people use your website across devices? Are they starting a task using their computer but complete it using their mobile phone? Implementing User ID Google Analytics, you can answer questions like these with Google Analytics. Using User ID feature, one can accurately measure the behavior of users as they span across different devices. User ID enables a holistic approach to measuring user interactions such as attributing an interaction with a marketing campaign on one device to a conversion that is completed on another device.

De-Duplicate Your Users

User ID as a feature allows websites to use their own identifier in Google Analytics (an account sign in). When the data is processed in Google Analytics, it uses User ID to identify unique users across all platforms and de-duplicates users from multiple devices that have the same User ID. This result is a more accurate measurement of the actual number of users that engage with your business regardless of the platform they use to interact.

Multiple Devices

Generate Better Insights

Google Analytics provides a separate view for User ID feature with special cross-device reports which are not available in other views. There are three types cross device reports:

Device Overlap Report
Device Paths Report
Acquisition Device Report

1. Device Overlap Report

This report enables you to determine the combination of devices like desktop, mobile or tablet used by users to engage with your business.

Segment users by device type and compare important metrics like revenue and user transaction rate.

Device Overlap Report

2. Device Paths Report

This report is used to determine the order in which users used multiple devices to interact with your business and then convert.

This report is similar to ‘Conversion Paths’ in multi-channel funnel reports.

Devices Path Report

3. Acquisition Device Report

This report is used to determine whether or not a user converted from the acquisition device. Acquisition device is a device (desktop, mobile or tablet) through which a user was acquired for the first time. Using this report you can attribute an interaction with a marketing campaign on one device to a conversion completed on another device.

Acquisition Device Report

Other Significant Benefits of Implementing User ID Google Analytics:

Unify user sessions across devices without asking for login.
Compare segments of logged in users vs not logged in users and discover how different these two engage with your content.
Import User information from other sources into Google Analytics.
Find relation between acquisition, engagement and conversions.

Concluding Thoughts

Implementing User ID Google Analytics feature mitigates issues like cross-device usage and session unification. Although, tracking still relies on cookies and Javascript. These are susceptible to issues like deletion of cookies, disabling Javascript, using public devices etc. As with the data, you should focus on analyzing trends, changes, and patterns, rather than absolute numbers.

I hope this post will help you understand why User ID feature is such a popular thing and worth implementing it. In case of any queries or feedback, please feel free to leave a comment in the section below and we shall get back to you.

Also Read: Customize Google Analytics Campaign Timeout For Affiliates

Track Your Android Webview as Screenview in Google Analytics and Get a Perfect Flow of User Journey

Posted on August 17, 2017 - 12:59 pm by Ravi Pathak

webview

Are you struggling with tracking Webview data as normal Screen view in Google Analytics? In this blog post, I am going to take you through the process of achieving that step-by-step.

Why track Webview as Screenview in Google Analytics?

Your company has its business on an App as well as a Website with satisfactory Google Analytics(GA) tracking implemented using Google Tag Manager. You are rendering some of the pages like Terms & Conditions, Policies, etc in the webview within an App.

For the purpose of understanding, let me show you how you might have muddled up your GA Data in both App and Web Property:

Web Property of GA :
1. Page tracked in a web GA Property, even though it is opened in the App
2. Sessions created in a web GA Property with only a single Pageview
3. Unnecessary user and session created in a web GA property
4. Redundant user created in a web GA Property leading to false insights
App Property of GA :
1. No Screen view tracked for web page rendered in the App
2. Loss of screen view data, for the pages that are actually rendered in webview

I would sigh in despair encountering the above problems, thus to deduce the above-muddled data we will here try to unite the tracking data of both the app and webview in the most savvy manner.

The implementation includes two steps :

Track the page rendered in webview as a screenview in an app GA Property
Restrict the same page from being tracked as pageview in a web GA Property

1.) Track the page rendered in webview as a screenview

To track a screen view for the webview page we will utilize the readily available function of webview onPageFinished().

Every time when a page loads in webview, the above function is called implicitly, hence we add the code snippet of tracking screen view within this function. This code will identify which URL is opened and using this we will track the screenview for the opened webpage.

DataLayer push to track screenview

NOTE :

A Screenview Tag must be configured in the Google Tag Manager console, with the trigger event.

In the above scenario, the triggering event for Screenview Tag is “OpenScreen”.

Chances are that there may be more than one page being rendered in webview one after another and we need to track all the pages rendered in webview.

Well we don’t need to worry much as the above-mentioned function will be called every time when a web page is loaded in the webview, either it is the same page or a new one. You just need to fetch the URL of the opened web page, identify which page is opened, and accordingly apply a condition to send Screenview hit by defining the appropriate screen name for each different page opened in webview.

2.) Restrict the same page from being tracked as a pageview

As above we have tracked a web page as Screenview in App Property of Google Analytics, it is necessary that we restrict the same page from being tracked as Pageview in Web Property of Google Analytics at that particular instance.

To do so we will set a unique identifier for App Webview, by altering the UserAgent of it. This will help us identify whether the web page is being rendered in the webview of your Application.

Also, this will be the key point for us to restrict the firing of pageview hit in the Google Tag Manager configuration.

The below code in the native App alters the UserAgent of the webview.

Android Screenview

Altering the Useragent

Once we have set up the tracking code in the native app, it’s now time to plunge into the Google Tag Manager configuration. Please Note that, as we need to restrict the Pageview firing we are here referring to the Web Google Tag Manager Setup.

The Google Tag Manager configuration involves two steps :

Configure Custom HTML Variable in Google Tag Manager of Web, which identifies whether the web page is opened in Webview or not.
Configure the Custom variable with the below code snippet, that fetches the UserAgent of the current application where the web page is loaded. The code will either return true if the page is rendered in webview of our App, or it will return false otherwise. Script to identify webview

Use the Above variable in Pageview Trigger to restrict the firing of Pageview Tag when the page is opened in Webview.

Trigger setting for pageview tag

After working our fingers to the bones we have finally accomplished collecting the Webview data in the correct Google Analytics Property. You can now explore your Google Analytics reports to substantiate your implementation.

Hopefully, by now, we have aptly tracked the webview data as screenview in the correct Google Analytics Property of App. At the very same time, we have also restricted the pageview firing for it. Thus we have now apprehended the perfect flow of user journey in our Google Analytics Report.

If you have any queries with regarding the process described above, I invite you to come back here and tell us about the before-and-after. I bet you’ll have something to say! Moreover, check out our recent most webinar on Deep Dive in App Analytics where we have covered this as a use case.

Video Engagement Tracking Analytics: Know the User Engagement rate of Your Video Channel

Posted on July 25, 2017 - 9:37 am by Ravi Pathak

Video Tracking Analytics

Videos have always been more effective medium of communication. Studies shows that retention rate of information is 80% for what you see and hear. For hearing it is 10 % and 20% for seeing. Better internet infrastructure has allowed online businesses to use videos as part of the content strategy. According to KPCB¹ study, online video will account for 74% of online traffic by end of 2017.

Around 50% of internet users look for product related videos before visiting store². In education content distribution industry, companies like coursera, udacity have been successful in terms of creating, publishing and tracking such videos for engaging their viewers.

Is Your Video Tracking Exhaustive?

Videos are helpful in increasing user engagement and retention. We should have efficient event tracking in place to measure video consumption metrics. For text or image content, marketers have been measuring user interactions like pageviews, clicks or hover events. For videos, it is not enough to track how many times video was being played. For getting true engagement insights, interactions like play, pause, seek should be tracked. Some of the important metrics for tracking videos on websites are video watch time, total play count, etc.

Use custom dimensions to track Video category, language, genre, total video duration, release date, etc.

Having category, language, total duration as custom dimensions helps in creating custom reports. Comparing user engagement on webpages with and without videos gives useful insights. It helps in deciding video positions on the webpage.

Drawing Actionable Insights

Tracking events on 25%, 50%, 75%, 100% of video help us understand consumption and drop-off rates. We can then decide Ads placement or Click To Action buttons placement accordingly. For example, let’s say we find out that, people leave the website or play another video on 95% completion of movie. This is likely to happen as last 5% content may show movie credits. Then it makes sense to show ads or ‘Click-to-Action’ links much earlier.

There are many analytics tools which help businesses measure user interactions for videos. With over a billion users, YouTube Analytics solution is most popular in the industry. It allows us to track user interactions like total video play, pause,etc. events.

Track Much More Than Basic Events

Most of the analytics tools in the industry track video events like play, pause, seek, clicks on ads, etc. This is where effective measurement plan comes into picture. Considering the business requirements, Tatvic team has developed a solution for video tracking.

Features of Video Analytics Tool by Tatvic

Actual video watch time:

When user is watching a video, user may pause a video for some time or does some other work and then again resumes play. Or, video is being played on the webpage but user is browsing some other websites in another tab. In such scenarios, metrics like video play count, watch duration will give misleading picture. Tatvic team identified this possible problem. We developed a solution for calculating actual watch duration. It considers special cases like tab switch, pause, screen size.

PWA Implementation:

Progressive Web Apps are gaining popularity with better performance. Online traffic consumption across mobile has grown significantly over last few years. Tatvic team has implemented Video tracking solution for PWA websites as well.
Personalized Recommendations of video content:

‘Recommended videos’ feature played a major role in success of YouTube. Similar is the case with Facebook videos. 500 million people are watching videos on Facebook every day3. Tatvic Data Science team has developed a Recommendation Engine. It uses machine learning algorithms to suggest recommended videos.
Video Players covered:

YouTube, HTML5, Kaltura, JW Player etc.

What’s Next:

Since survey reports⁴ show that 11% of the global internet population is blocking ads on the web, if you are showing ads in videos then tracking the number of users with AdBlocker tools is imperative. Tatvic has also developed a solution for detecting Ad Blocker scripts which is a universe in itself and we shall be covering it in a separate blog post.

“If You Can’t Measure It, You Can’t Improve It”

We hope the blog proved to be insightful to you and helped you in understanding the value of having video tracking for your website/app in place. If you have any doubts or are looking for clarifications, please drop in comments and we shall be sure to get back to you.

Edit Button for Google Analytics Custom Reports with Chrome Extension by Tatvic

Posted on June 28, 2017 - 2:59 pm by Ravi Pathak

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chrome extension for google analytics

Google is constantly making efforts to make the world a better place with its products and services. Recently, Google Analytics was reborn with new features and a revamped desktop UI. These changes are rolling out globally on a gradual basis. We, as a reseller of Google Analytics, love the new features being rolled out. We are especially glad to have an insightful Homepage.

As the product is upgrading, we were exploring with the aim to get to know these changes in detail. One typical pain point is not having the “Edit” button on Google Analytics’ Custom Report. For us, it is a basic task to create a custom report and edit it on the fly while analyzing the data collected in Google Analytics.

Everyone on the floor was asking each other, “When will Google add this Edit custom report button?”. And the other person replies, “Don’t know about that but anyway you can go to the Custom Reports Overview page and select Edit from the Actions drop-down”.

edit button chrome extension

This dialogue exchange inspired an internal discussion, we arrived at a fruitful decision to work on creating and launching a Chrome Plugin that will provide an Edit button on a temporary basis. Having an Edit button on the Custom Report itself will ease the process of editing the report and checking the data repeatedly.

chrmose extension for editing custom reports in google analytics

Initially, we had released this extension only internally. But after receiving positive feedback from all the users, we decided to roll out this extension globally as it was actually serving a purpose.

How to get it?

You can get this extension from the Chrome Web Store or simply click on the below button.

Click on Add to Chrome button and Voila! You’re good to go. Check our extension in the action.

edit custom reports

Download the extension, use it, and send us feedback as to how you liked it and if there are any issues that you might face.

How to implement Google Tag Manager for Android

Posted on June 5, 2017 - 11:30 pm by Ravi Pathak

Editor’s Note: This blog has been updated on June 06, 2017 as per the latest version of GTM and Android

featured_image

At I/O 2013, Google added new features to the Google Tag Manager. They launched Google Tag Manager for Android and iOS devices. It is used in Mobile App along with Google Analytics to track various user behavior and help the marketers identify the trends, needs of users, app performance and other peculiar insights.

Google Tag Manager for mobile app developer devices also makes their development easy and dynamic. It enables the developers to change configuration values in their mobile applications using the tag manager interface, without having to rebuild and resubmit application binaries to the app marketplaces.

In order to walk through the implementation, you must be familiar with Android and iOS development to understand and implement tags for web analytics using Google Tag Manager.

Before starting implementing GTM, I recommend drafting a plan for tagging for google tag manager it will help to structure the core objective of data collection.

Steps to set up GTM in an Android Project (Click here or iOS)

Create a Google Tag Manager Account
Create a Mobile App container
Note down the Container ID (It would be of the form of GTM-XXXXX)
Add Google Play Services library to your project
NOTE: Check for latest updated version of Google Play services library when adding it in project.
Add the following permissions in your AndroidManifest.xml
Also Add the Install Referrer Receiver in AndroidManifest.xml to track Campaign Data.
Now, Create a Trigger with the following configuration in Google Tag Manager Container.
Create a DataLayer Variable to fetch the value of screenName from the datalayer.
Create a Tag to fire the Screen View from the app.
Add Google Tag Manager’s Default Container to your Project.
- Within Google Tag Manager interface select VERSIONS -> ACTION -> DOWNLOAD this will download the container binary file.
- Within your Android project, create a raw folder in project-root / res path.
- Copy the downloaded binary file to the path project-root / res / raw with changing the filename to gtm_defaultcontainer_gtm_id.

Now, Let’s get started with initializing Tag Manager Instance and using DataLayer

Create a ContainerHolderSingleton Class.
ContainerHolderSingleton class is used to have access to a single instance of TagManager Object at a time.
Create a class ContainerLoadedCallback Class.
ContainerLoadedCallback class is used to load the fresh GTM Container when it is available
Initialize Tag Manager in Application Class of your app (Recommended) or First Screen of the App (i.e. Splash Screen or Main Screen)
Load the latest container by specifying the CONTAINER_ID
Use ResultCallback to return the ContainerHolder once it has finished loading or has timed out for fetching the latest container
After Initializing GTM well, it’s time to add the tracking code, which is implemented using the DataLayer Object.
DataLayer provides a layer of persistence that you use to store data in key-value pairs form and then send it to Google Analytics.
Create one method in general until class to push the openScreen event and start tracking the screen views from your app. You can call this method in onCreate()/onStart Method of your app activities with the screenName that you want to send.

With the above steps performed we have successfully implemented the Google Tag Manager in Android. To know that your implementation is working well, verify your data in Google Analytics Report.

Also please note that to track any kind of action through GTM, an event must be pushed in dataLayer and for the very same event, a Tag must be configured in GTM Interface.

So, that’s it. This is how you can integrate Google Tag Manager version 4 container in your Android app. Recently, Google rolled out version 5 container for the app

Now, the question is which version should you use in your app. Stay tuned for the benefits of the version 5 container over the version 4 container and steps to integrate it.
Till then HAPPY TAGGING!

Tangled up in DeepLinking? Firebase has a solution!

Posted on December 13, 2016 - 1:47 pm by Ravi Pathak

DeepLinking

Deep Links simply help you merge the two different worlds of app & web. They allow the user to land on a specific screen or section in the app by clicking a web URL. The user can dive into the app seamlessly rather than fumbling on various pages of the website on mobile devices.

I was actually scrapping my head off when I first sat to implement Deep Linking. Do you also find Deep Links complex? Then worry not! Because there’s Firebase to the rescue!

Firebase is a platform that provides various tools and infrastructure to build better apps. One of its awesome features is Dynamic Links. With the help of Dynamic Links, we can set up Deep Links. This is actually the crux of this blog.

Now let’s put our heads together to learn:

Why do we need Deep Link?
How does Deep Linking actually work?
How to implement Deep Link in your app using Firebase?

Why Deep Linking?

Let’s talk about a practical issue that everyone faces.
Suppose, you have an app installed in which you have already logged in.

One fine day you receive an email regarding a tempting offer and you click on the link in the mail.

All it does is opens your browser in the mobile web asking you to login again. And then all you do is blurt out crap in frustration!

Instead of the browser, the installed app should’ve opened, right? And that would be possible with Deep Linking.

Deep Links are also useful for promotional notifications as they take users to the most relevant screen in the App. That’s pretty magical, isn’t it?

How does Deep Linking Work?

Within a mobile phone and its native app ecosystem, the operating system uses a mechanism that allows any native app installed on the phone to register for a specific URI scheme.

A URI scheme will tell the operating system which app to open up when the URI is clicked.

Mechanism of Deep Linking

For example, an app is listening to http://shop.www.tatvic.com/shop. If anyone clicks on this link, and an app is installed on the device then the app will open. If there is no app registered with this URI, then the link will open in the browser.

How to implement Deep Linking in android using Firebase?

To implement the Deep Link, you need to make changes in:

The Firebase Console
The Native coding in your android app

Firebase Console:

To work with Firebase, you need to first register your app with Firebase.
Post registration, add the following dependency for Firebase Dynamic Links to your app-level build.gradle file.

compile 'com.google.firebase:firebase-invites:9.4.0'

You can now proceed to create a dynamic link in firebase console. Here’s how:

Open the Dynamic Links section by clicking Dynamic Links on the sidebar menu of Firebase Console.
Click on New Dynamic Link and proceed to accord the basic details of the dynamic link in the form that appears on the screen, as shown in below image.

Advance Option:

Use Advanced options if required, to add more attribute to our deep link.

Below are the optional fields that can be provided in your deep link.

Advanced options details for Deep Link

This is the fallback link that will be fired if in case the Link set for deep link is not fired.
Here, you can also provide a minimum version of the app that can open the deep link that is configured.
This can use any link scheme if specified, it takes priority over the link parameter on Android.
5 and 6 are related to the campaign.

After you provide all the relevant details, just click the CREATE LINK button. The link generated will be as follows :

http://shop.www.tatvic.com/shop&apn=com.rj.firebasedemo&amv=4&afl=http://shop.www.tatvic.com/&utm_source=demo_source&utm_medium=demo_medium&utm_campaign=demo_campaign

Also along with the above link, a short deep link is generated which will be used in your deep link configuration, in the native app coding.

https://uw55y.app.goo.gl/?n9ro

Native coding in your android app

Now follow below steps for coding configuration in native coding part in android app also.

1. In the intent filter of the activity (i.e activity of splash screen or main screen) that will handle the deep link, in Android Manifest.xml , append the following code.

In the java file of the activity, that will handle the deep link, append this code.

Now I would happily say that we have successfully implemented Deep Linking in the app!

But wait!!!

Don’t you want to know whether the configured deep link is working?
Well, here’s how you check it!

You can send a long URL(Generated by Firebase console) to your device.
Click URL from the device. Your device will either ask you to open the link in the app (if the app is already installed) or in the web browser. Preferably, you should opt for the app to test your configurations.

If the app opens up, pat your back! If not, then just take a nap break and follow up the steps again!
Before winding up with this post, I would also like to dispense an astonishing feature of Firebase. It automatically logs a few Analytics events of Deep Linking. Refer below screenshot for the same…

For any assistance on Deep Linking or Mobile App Analytics, please drop us a comment in the section below & our experts will be glad to assist you!!

How Google Analytics with CRM Intergration helps in Digital Re-marketing?

Posted on September 22, 2016 - 8:15 am by Ravi Pathak

Integrate Google Analytics with CRM for Digital Remarketing

Google Analytics is a tool that helps you measure the effectiveness of your marketing channels. It stores the online behavioral (web and/or app) data of your visitors. However, your CRM has additional data stored with your customer’s offline activity.

Using your CRM data, you can run different types of campaigns such as email, SMS & calling campaigns for your warm and hot leads. These traditional campaigning strategies are used by all and hence your product/service offering has to fight a tough battle against your competitors.

The case is slightly different in the case of online remarketing. Since online remarketing is carried out using first-party cookies, it means you can exclusively reach out to visitors of your website while they are surfing other websites on Ad Networks (like Google Display Network, DoubleClick, Amazon, etc.). Specifically, in the case of lead generation and eCommerce websites, if we combine the two data silos (GA and CRM), then we can create a platform for user segments and carry out online remarketing with smart and effective remarketing lists.

Let’s move to the next section to understand a few use cases and the steps to implement this.

First, we will discuss Lead Generation websites and then eCommerce websites.

Lead Generation Websites:

Typically, for lead generation websites, the flow is such that traffic lands on your website from different sources and shows interest. Hence, a lead is generated. Post lead generation, the sales activity starts and CRM tracks the sales funnel.

Online Lead Conversion Funnel:

online lead conversion funnel

Offline Sales Conversion Funnel:

offline sales conversion funnel

Following are some most common attributes that are available in Google Analytics as well as CRM for generating and evaluating a lead.

Google Analytics

The marketing channel that brought the user
Number of sessions
Average time on the website
Pages visited
Demographics
Geographical information
Device information
Last visited

CRM

Current stage of sales process (e.g. Stage A -> Stage B -> Stage C -> Lead closed)
Type of lead (Cold/Warm/Hot)
Lead income
Gender
Occupation type
Age bracket

You can create smart remarketing lists for:

Users who have visited your website but have not yet submitted a lead. (Non-converters)
Users who have recently submitted leads and are yet on stage C of the conversion funnel. (Recent lead but sales process not moving ahead may be because of temporary unavailability of the user)
Leads from organic channels but have not yet started sales funnel steps. (These users came organically by searching and so have a very strong intention to buy)
Users from organic medium and after submitting lead they have lead income as > XYZ
Users who came to the site from Facebook who is from the age bracket of 21-25 years & profession as working professionals & gender as male

Here are the different types of remarketing campaigns that can be run:

Ads created for brand awareness
Ads providing a limited offer
Ads providing discount coupons
Call campaigns having direct business phone numbers
Video campaign showing a demo of your product

eCommerce Websites:

In the general flow of eCommerce websites, users complete transactions on the website, and CRM records post-sales activities. Users might return the products they purchase call up at the call center for some assistance; & provide feedback through an email survey. Let us list down a few common attributes that are available for a user in Google Analytics as well as CRM.

Google Analytics

The marketing channel that brought the user
Number of sessions
Average time on the website
Products views
Demographics
Geographical information
Device information
Last transacted

CRM

User loyalty
Goods returned
Customer care rating
Email survey feedback

You can create smart remarketing lists for

Users with high user loyalty.
Users who have browsed products after refunding a transaction. (They had an issue with a specific product but do not mind purchasing a different product)
Users who have added products to their cart and are in general happy with customer care service. (Users are already happy with the service and just need to be slightly pushed)
Users from metro cities with decent email survey feedback. (Their feedback shows that they are happy and being from metro we can try doing an upsell)

Here are the different types of remarketing campaigns that you can run:

Ads creating brand awareness
Ads providing discount coupons
Ads showcasing 24×7 customer support
Video ads showing product features

Here we have understood the different scenarios under which a user can be retargeted.

However, the key here is an integration of GA and CRM. The steps mentioned below show how can you integrate and create a remarketing audience, though it might involve a bit of support from the technical team.

1. Preparation for Integration-

The primary requirement for GA and CRM integration is the availability of a common key between the two data sets. This can be done in either of two ways: -

a. Expose the CRM ID onto the website and pass it to GA as a custom dimension.
b. GA generates a unique Client ID for each unique visitor. Pass this Client ID to your CRM for every user.

The first approach requires a very small implementation update to expose an ID to the front end (as a hidden field). The second approach requires a change in the CRM API and adding a field in the CRM database to store an additional field. Thus, the first approach is comparatively easier than the second one. Alternatively, if CRM ID cannot be exposed to the front end, then a phone number or email address can be hashed to generate a unique ID that can be sent to GA.

2. Uploading CRM Data into GA-

Once a unique key has been set up in both systems, we then have to upload CRM data to GA. To do this, there are two methods, (1) the Data Import feature and (2) sending Measurement Protocol hits. There are a few limitations also for each of these methods. These methods have been explained here.

Depending on the exact use case, the implementation team at Tatvic has designed a few workarounds and automated the implementation process.

3. Create GA segments for verification-

Once the data has been uploaded to GA, create segments in GA and verify if the number of users in the segment is equal to the expected number of users that need to be remarketed

4. Build an Audience list-

Once the above verification step is done, we can export the same segment to Adwords/DoubleClick as a remarketing list. Once the list gets synced and sufficient audience size is achieved, campaigns can be configured, and remarketing can be started.

Also, keep in mind:
1. For Google Analytics premium clients, BigQuery can also be used to identify user segments.
2. Remarketing list creations for Google Display Network(GDN), Doubleclick Bid Manager (DBM), and Search Ads (RLSA) have their own limitations in terms of the time period within which a user can be added to audience lists.

Data sent via the measurement protocol can be used to trigger RLSA list addition only if it is sent within 6 hours of those users’ most recent visit. In addition to a display remarketing list, the data must be sent via the measurement protocol within 10 days of those users’ visits.

To summarize, our experts at Tatvic have created online remarketing campaigns by combining GA and CRM data for our clients, which has helped them in generating new business and in turn increase revenue.

For more information, & assistance on integrating your CRM with GA, drop us your details in the comment section below. We will be glad to assist you!!

What is Product Bundling & Product Analytics and Some of its Examples?

Posted on November 19, 2014 - 12:11 pm by Ravi Pathak

Product bundling is unique and probably most underutilized way to increase e-commerce revenue of store. I haven’t seen many stores that uses this tactic to increase revenue for e-commerce stores. If you head over to our E-commerce Revenue Optimization Framework that I built recently, it is pretty evident that if you can increase avg. quantity per transaction, it can have a strong boost on the revenue of e-commerce stores.

I wanted to use this article to explain some of the new practices are coming to make customers buy more if they are deal seekers using product bundling:

Product Bundling:

A Product Bundle is basically a group of products that you offer to your users, mostly at a discount. It’s a nice way to encourage impulse buying and increase order value. When a customer is on a product page, you can suggest a bundle of products that would go well with that product.

It works as normal recommendations. In bundling, all products that you recommend have a relation and they are sold together. The hitch here would be, “why would people buy 3 products when we are not even sure that they’re not even going to buy one?

They will. Actually, they do.

We implemented Product Bundling with one of the customers of Liftsuggest. Within 15 days, his order value for the customers who bought bundles increased the order value from $160 to $182. We learned that about 3% of visitors who saw bundles actually bought them.

How does bundling work? How are these bundles created?

Tatvic’s recommendation engine can be implemented on your shopping cart. It will analyze your website’s customer’s behavior using data from Google Analytics. It creates groups of users from the analytics data, and creates bundles based on which products are being bought together for the most of time, within that group. Then it serves targeted bundles to each specific group of customers.

How does it benefit the customer?

The customer has to see value. Here’s one of the 3 reasons a customer will consider buying the above bundle:

She sees a huge saving
She loves the product combination you are offering as a bundle
Both of them

How does it benefit the vendor?

If offered discounts, the vendor has to lose some margin. He makes less money per product, but more money on the total order value. Also, sells more products. Find below 3 product bundling strategies you can use for your e-commerce store:

Product Bundling Strategy:

There are some bundling patterns to create targeted bundles that customers would like to buy.

1) Bundling main product with accessories

Above is a perfect example of bundling main product with accessories. An Indian wear is bundled with a necklace and a purse. The customer will buy this because she’s getting a matching set and with discounts.

2) Bundling main product with similar products

This kind of bundles will go well for books, apps, software’s, music and movies.

3) Bundling main product with different products

You can use this pattern to cross sell. E.g., A washing machine can be bundled with a microwave or a TV.

Product Bundling Tips:

Offer discounts

Bundle products together and give good discounts. The customer will see direct value and a reason to buy the bundle. In above image, “Best deal..” as a heading is a nice way to promote the discounts and attract customers.

Build urgency

When offering discounts, or showing a value deal, urgency can be built. to push the purchase. Again in above image, see this line, “Valid for next 4 hours”. It builds and urgency in customer’s mind, and pushes her to buy it right away.

In this blogpost, we learned what is product bundling, how to begin with product bundling and few tips that will help you improve your overall product bundling strategy.

Hello There!

About Ravi Pathak

What is Client ID ?

Client ID Tracking Implementation

De-Duplicate Your Users

Generate Better Insights

1. Device Overlap Report

2. Device Paths Report

3. Acquisition Device Report

Other Significant Benefits of Implementing User ID Google Analytics:

Concluding Thoughts

Why track Webview as Screenview in Google Analytics?

1.) Track the page rendered in webview as a screenview

2.) Restrict the same page from being tracked as a pageview

Video Tracking Analytics

Is Your Video Tracking Exhaustive?

Drawing Actionable Insights

Track Much More Than Basic Events

Features of Video Analytics Tool by Tatvic

Actual video watch time:

PWA Implementation:

Personalized Recommendations of video content:

Video Players covered:

What’s Next:

How to get it?

DeepLinking

Why Deep Linking?

How does Deep Linking Work?

How to implement Deep Linking in android using Firebase?

Firebase Console:

Native coding in your android app

Lead Generation Websites:

Online Lead Conversion Funnel:

Offline Sales Conversion Funnel:

Google Analytics

CRM

You can create smart remarketing lists for:

Here are the different types of remarketing campaigns that can be run:

eCommerce Websites:

Google Analytics

CRM

You can create smart remarketing lists for

Here are the different types of remarketing campaigns that you can run:

1. Preparation for Integration-

2. Uploading CRM Data into GA-

3. Create GA segments for verification-

4. Build an Audience list-

Product Bundling:

How does bundling work? How are these bundles created?

How does it benefit the customer?

How does it benefit the vendor?

Product Bundling Strategy:

1) Bundling main product with accessories

2) Bundling main product with similar products

3) Bundling main product with different products

Product Bundling Tips:

Offer discounts

Build urgency

Service

AI Solutions

Company

Tatvic Bot