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Overview of Advanced Analysis in Google Analytics 360 - Be Better Informed and Be More Responsive and Confident

A customer goes through different steps while initiating a purchase. Google Analytics primarily shows numbers pertaining to users who dropped out or made a sale, in five steps at the most. It does not showcase customer journeys in the most granular detail.

Companies rely on Google Analytics to gauge the audience and their behaviour through definitive metrics.  

But very few businesses know for sure if changes like site design revamp, or the new product presentation triggered a change in their purchasing behaviour. Generating reports based on these scenarios and metrics is a tough ask.

For enterprises looking to understand customer journeys better, Advanced Analysis delivers hard-to-find insights. This feature is yet in Beta phase but is sure to enable companies to spring into immediate action.

  • The new data exploration feature enables “instant visualizations” of website data.
  • The Funnel Analysis technique provides decision-makers with better visibility into customer actions
  • The Segment Overlap feature provides better insight into audience segments

The features are a part of Google Analytics’ efforts to equip website owners with better analytics for extracting business value from their data.

Salient Features of Advanced Analysis

With Analytics 360, enterprises leverage data-driven insights to understand customers better. Marketers often need to slice and dice data in unique & insightful ways to analyze them when subjected to diverse metrics and dimensions.

This approach of deep analysis can be challenging since it needs organized information sources. The derived data from different customer touch-points makes the data synthesis quite difficult.

With Advanced Analysis, marketers have a flexible and intuitive feature to gauge customer experience. Featuring detailed analytical capabilities and better depth in reporting, Advanced Analysis reveals key insights for business. It also offers audience discovery options with granular segmentation. It introduces a plethora of variables to determine primary customer segments too. You can address questions such as

  • How do users who have not checked out differ from those who purchased a product from the site?
  • Does a specific device or browser impact users and their purchasing behavior?
  • Does the audience consist of new or returning customers? Are they from India or elsewhere?

Three Reporting Tools of Advanced Analysis

Advanced Analysis comprises three reporting tools primarily:

  • Exploration
  • Segment Overlap
  • Funnels

The Advanced Analysis Homepage

The Advanced Analysis Homepage

The Advanced Analysis homepage resembles the Data Studio homepage, with a smart dashboard inclusive of all reporting tools.

To begin the analysis, one can choose a predefined template from each of the reporting tools. If you want to create a custom report, select “Blank.” You can view all created reports under “All” or “Owned by Me.” The upper left-hand corner includes GA Account name, Property, and View that is currently selected for analysis. One can change the view for the same organization, from the upper left-hand drop-down box. You can even switch between multiple organizations by clicking the ‘Organization’ icon.

The Variables Pane

The Variables pane across the Advanced Analysis reporting interface lets you add more tabs to your report.

  • Define the date range for the analysis and compare two periods.
  • Below the date range, the Segments section specifies the diverse criteria for the reports. If you use a specific template, there are some preloaded segments but one can add more with the Plus sign. Choose segments accessible in your Google Analytics - up to 10 segments at any given point of time.
  • In the Dimensions and Metrics section, one can add up to 15 dimensions and 10 metrics in the pane at any given point of time.

The Variables Pane

  • You can add Segments, Dimensions, or Metrics to the resulting reports; double-click them or drag-and-drop them to the main window.

A.The Exploration Report

The Exploration Report

Perform deep analyses in a few clicks. Drag and drop diverse variables like dimensions, segments, and metrics to visualize datasets, within a single, specific view. Multiple tabs can present separate views for specific queries while comparing insights across those views.

The Exploration Report resembles a standard Google Analytics report, but with better data analysis. Standard reports include primary and secondary dimensions only, while Advanced Analysis allows users to interact within 5 nested rows and columns. Analysts can pivot the table, modify rows/columns, change visualization style from tabular to a pie chart to a line graph, and more. The Exploration report thus presents a fantastic point to commence analysis.

Data interactions through the Exploration Report

Right-click values in any view to open up the Interaction menu

It is simple to interact with data through the Exploration report.

  • Simply right-click on a data value from the table or any other graph, to know the options. Include or exclude a data selection and then filter onto the tab settings to update the same.
  • Secondly, you can “Create segment from selection” to add another segment on the Segment panel for analysis. One can even use the segment in Google Analytics.

Publish Segments for use in Google Analytics

  • Build audience from selection - Create audiences from the selection with a subset of users.
  • Explore user detail in your data subset by selecting “View users” to view the user explorer report.

B. The Segment Overlap Report

The Segment Overlap Report allows users to visualize the intersection of segments with one another (up to three segments at a time).

The Segment Overlap Report

The top-most metric in the “Values” pane, determines the segment overlap in comparison of other metrics mentioned in the pane. Check out intersection points of different audience segments to reveal overlaps. For example, you can see the return of first-time visitors after they purchased something from the site. This is helpful when one needs to understand user behavior and how it leads to conversions.

One can view the values for each segment by hovering over them. One can switch between the default “Users” metric and Sessions, Transactions, or other metrics.

Add dimensions to the “Breakdowns” shelf to witness real-time report changes. Also, right-click on specific segments or data values to create independent segments, filter criteria, audiences, and users.

C. The Funnel Analysis Report

The Funnel Analysis Report is useful for customer journey analysis. Google Analytics 360 hosts the Custom Funnels feature too but one can define only up to 5 steps. Advanced Analysis boosts the number to 10, driving the depth of analysis to a large degree. Compare how different audience segments navigate through your site, and use the data insights to optimize customer journeys better to drive more conversions.

The Funnel Analysis Report

Apply an independent color to each segment in the funnel. The funnel analysis report consists of the same functionality for creating segments, building audiences, and the like, as in other reports. You can even target users who dropped off from the funnel in between steps, by building a custom audience for retargeting purposes, through Google Ads and Video 360.

Advanced Analysis Funnel Analysis Reports

Define the steps of your funnel, with help of the pencil icon in Tab Settings. The funnel includes metrics to define custom steps unlike the similar feature in Google Analytics 360.

Also, all funnels are “closed” funnels here, since users need to be present right from the first stage of the funnel and then strive for further qualification. The customization options are limited too compared to Custom Funnels.

Conclusion

Advanced Analysis offers major benefits for enterprise organizations who are keen to leverage analytics better. Get actionable insights that can help your business to deliver better customer experiences. Once you derive insights, build custom audiences, and experiment with site changes, you are ready to make critical business decisions successfully. Learn more on how advanced analysis in GA 360 can work wonders for your business by contacting us here

How Google Analytics Client ID is a Boon for Marketers and Its Step-by-Step Implementation in Android

 

Google Analytics Client ID offers infinite possibilities for marketers 

Google Analytics Client ID is one of the most important and core concepts in Google Analytics. It ensures that we get deep insights into understanding user behavior and user journey. Before moving ahead, it is essential to understand what is Client ID. In simple terms, it is a part of the Google Analytics cookie which is generated by default to track users. Google Analytics Client ID plays an instrumental role in deriving cross-domain tracking reports and a unique way to identify users. Insights from cross-domain tracking help us to de-duplicate users across domains for businesses with multiple websites. Marketers can also study user behavior and user journey for effective re-marketing with user classification.

A broader outlook on the utilization and implementation of Client ID on Websites

The ga_cookie gets updated when any user returns to a particular website that has Google Analytics implemented on it. For every new user, a new cookie is created along with the new Client ID. The cookie is valid for 2 years (and so is the Client ID). If a user deletes the cookie, then a new one is generated along with a new Client ID such that the user will be considered new.

De-duplication of Users with Client-ID

For websites with multiple domains, remarketing is nothing short of a nightmare when it comes to targeting users across the said domains. When you target the same person multiple times, the budget doubles, and the ROI is slashed by half. With the help of Google Analytics Client ID, one can determine which of these users are moving across domains and are the same ones.  This way, it’s possible to de-duplicate targeted users and run highly efficient re-marketing campaigns.

Client ID - Attribution modeling

How it works:

The attribution of the source depends on the client ID. Google Analytics uses the last click (non-direct) model by default. For example, if a user lands directly on a website, Google Analytics checks for the cookie to identify whether the user is new or an existing one and applies the last known source through which the user has landed on the website.

It is important to note that in case if the user does not have any source information then the user source will be attributed to a direct channel.

Offline remarketing for conversion

There are many digital businesses that use a 2 step completion process. One is online data collection and the second is offline conversion. 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.

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: -

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

Once the data integration has been uploaded to GA, we can create a segment in Google Analytics based on the ClientID as a dimension and can use it for remarketing purposes.

Tracking Google Analytics Client ID and Implementation for Android

While you can also track Client ID in iOS, over here we shall understand how to track Google Analytics Client ID from Android devices. This can be done either in a custom dimension or an event through Google Tag Manager using the data layer method.

Follow the below-mentioned steps to implement:

In-App Implementation

There are two approaches to fetching ClientID in Android:

  • In the App, create an AsyncTask and retrieve Client ID using GoogleAnalytics Object.
Retrieve Client ID using Google Analytics

 

  • If it is not possible to create the “GoogleAnalytics” object then create a function as shown below. This function will return clientID that is stored within the Android device.

 

 

Google Analytics will thus help in gathering a lot of data on top of Client Id at an initial level.

Concluding Thoughts

One can draw a conclusion on how to effectively measure the audience behavior through client Id. Evidently, user acquisition cost is very high and companies spend big amounts on audience acquisition. This marketing expenditure can be optimized if companies have access to precise data points regarding the user behavior and user journey performed on the website or app. Analyzing such near-to-precise data can help them understand their audience more precisely and know about the user journey stage-wise. Based on such analysis, companies can take an informed decision on performing cost reduction processes and learn how to prioritize their marketing spend or future campaign expenses.

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