Case Background :

In this case study, we have shared highlights of our Google Analytics 4 enhanced ecommerce implementation for Circles.Life

Circles.Life is Asia’s first fully digital telco. Providing game-changing digital products and no-contract, data-focused mobile plans, revolutionizing the digital services industry through a customer-centric user journey.

Google Analytics 4 is the latest version of Google Analytics. It is not mandatory to upgrade to Google Analytics 4, but here are a few reasons why companies should. Considering the following reasons, for the best interest of our partners we suggested the implementation of GA4 :

Data Availability

Even though it is stated as an “Upgrade" this is actually an additional GA4 property. This does not affect your existing analytics setup. Since it’s a new separate property, it starts collecting data only once it’s implemented, it does not report the historic data collected in your existing version of GA. The sooner you implement this, the more historic data you will have with you.

No Sampling

With sampling, Universal Analytics reports a sample of data with minimum viable precision to support decision making. But, sampling confuses plenty of business users and stakeholders across teams. In GA4, there is no concept of sampling as such. GA4 property is a developed version of the erstwhile Google Analytics web + app property. No sampling means you get more accurate data for driving your digital decisions. This greatly reduces confusion and also boosts the confidence of the teams with analytics.

Analysis Hub

Analysis Hub is the new reporting User Interface which was available only in the premium version of Google Analytics – the GA360. With Analysis Hub it’s remarkably easier to create reports on the fly and leverage them for advanced analysis and insights. You need to use it to experience it – It’s very different.

Cookie Less Tracking

Official statement from Google: “Because the technology landscape continues to evolve, the new Analytics is designed to adapt to a future with or without cookies or identifiers. It uses a flexible approach to measurement, and in the future, will include modelling to fill in the gaps where the data may be incomplete. This means that you can rely on Google Analytics to help you measure your marketing results and meet customer needs now as you navigate the recovery and as you face uncertainty in the future."

Our Action:

Data layer Implementation

Most of the businesses will have a data layer setup for Universal Analytics property. However, GA4’s eCommerce tracking requirement would necessitate the creation of dataLayer with slight variance in taxonomy. Many digital analysts make the mistake of creating a new data layer API call for GA4. For Circles Life, we came up with a more optimized approach to update the existing data layer in such a way it takes care of both universal analytics and GA4 with minimal API calls.

Creating Triggers

The majority of digital analytics implementation processes begin with the creation of tags, which are then mapped to triggers. We firmly believe in setting triggers initially and then reusing them across multiple tags. Because the same logical trigger is driving all of the marketing and analytics pixels, consistency is assured. And moreover, this approach is more scalable, easy to maintain & less labour intensive in the long run.

Purchase ID

Duplicate purchases are fairly prevalent as a result of minor errors such as a receipt page that can be accessed via the browser cache or history. When users return to the receipt page, the transaction details are frequently written into dataLayer again, resulting in the inflation of your eCommerce data. To avoid duplicate purchase tracking we created a custom javascript code to track transactions by unique purchase ID.

Automated validation

We helped Circle.Life to link GA4 to BigQuery and from BigQuery export data to Google Data Studio. Then we linked the backend data set with google sheets and exported data to google data studio. Where we blended both data sets (Google Analytics 4 & Backend data set) to present an automated match rate between the two datasets. This made it considerably easier to manage the accuracy and effectiveness of the GA4 Implementation.

Partner Feedback:

“Their technical knowledge and proactiveness in solving problems are impressive." 

DataVinci Analytics Agency team has successfully implemented analytics for the firm’s marketing campaigns, distinguishing between web orders and actual orders. They have an effective workflow, and they impress the client with their expertise and problem-solving skills.

Himanshu Jha, Lead Data Analytics and Data Science, Circles.Life

Results from DataVinci over the last 60+ projects :