Google Analytics is currently the most widely used accessible data analysis service by Google. It is an essential tool for marketing execution. In October 2020, Google Analytics introduced GA4 as an updated version of UA (Universal Analytics), and marketers around the world have been concerned. By July 2023, the existing UA will be completely discontinued, making GA4 setup and learning essential. By July, there is a need for various measures, not only for setting up data collection with GA4 but also for how to utilize it.

What changes after setting up GA4? 

There are two significant changes after setting up GA4. First, all user activities are stored as "events." "Events" are unique data that can only be collected in GA4. An "event" refers to specific actions such as visitors accessing webpages or apps, clicking buttons, or scrolling pages. Collecting all interactions as "events" allows for simultaneous tracking of web and app activities in one place.

Second, there are more e-commerce-related events available for tracking online shopping activities. E-commerce tracking events are provided separately. However, GA4's e-commerce tracking based on new events may be somewhat challenging.

What are the advantages of GA4 e-commerce?

1. Analyzing sales factors at a glance. You can identify which sources/media generated sales in your online store.
2. Facilitating understanding of consumer acquisition paths and shopping behavior patterns.It is possible to understand the flow of visitors and drop-offs, the number of order form submissions, the number of actual payments, and other steps.
3. Easily grasping sales by product.You can easily examine detailed sales data for products and sales trends by period through graphs.
4. Predicting products with a high probability of purchase.Using predictive measurement items, you can determine purchase probability, churn probability, and expected revenue.
5. Generating targets for each user stage.You can segment buyers into different stages and execute advertisements tailored to their characteristics.

Is the functionality only available with GA4 setup? Datarize integration screen that can replace GA4 setup

E-commerce functionality is also available in Datarize. GA4 setup can be complex. It requires adding various events, installing scripts, configuring settings for navigation analysis, and adding custom definitions, which require learning. Many people find the provided guides difficult to understand. With Datarize, you can use GA4 e-commerce data functionality with just script installation and metadata integration. In particular, metadata integration allows easy and fast integration of not only e-commerce but also other information within the online store. Once integration is complete in just 5 minutes, you can quickly grasp key metrics for growth strategies, predict purchase probability, dropout probability, and execute campaigns immediately.

How can Datarize's data analysis capabilities be utilized instead of GA4 setup?

Datarize allows data analysis based on campaign statistics, funnels, acquisition, products, and high-relevance products for purchase association. Let's take a look at examples using funnels, acquisition, and product data.

1. You can identify sales factors through "Acquisition" analysis. 

Based on the purchase conversion rate, you can see the efficiency by source/media. In the example image, Naver, remarketing, and AlimTalk are considered the most efficient sources. You can focus more on sources with a purchase conversion rate of more than 5% and find improvement measures, such as strategies to increase conversion rates or modifying ad targets for media with low conversion rates. Datarize automatically inputs UTM when executing campaigns, allowing source/media management without any additional work.

2. With the "Funnel Chart," you can quickly understand customers' purchase journey.

You can visually understand the shopping journey from visit to product view to purchase attempt to completion. By using the funnel chart, even without GA4 setup, you can see the conversion rate at each step. Analyzing the causes of low conversion rates at certain stages and finding improvement methods can help increase the purchase conversion rate. Datarize also provides conversion rate benchmarks compared to the market, allowing you to infer objective performance. (Learn more about how to use the funnel chart)

3. With "Product Data" and "High-Relevance Products for Purchase," you can understand product sales and customer responses.

"Product Data" provides data such as impressions, click-through rates, purchase conversion rates, views, clicks, purchases, and revenue for each product, allowing you to identify products with the best customer responses. You can plan promotional actions, such as discount promotions for popular products or sending product recommendation messages to abandoned customers, to encourage purchases. Additionally, using impressions, which greatly influence product sales, as a basis, you can plan product promotion. At this time, you can also use the recommended products from "High-Relevance Products for Purchase." By displaying or sending messages about products that are frequently purchased together, you can increase the purchase conversion rate.

Analysis is just a beginning. Action is the key.

Ultimately, data analysis is necessary to find improvements and determine marketing actions. Datarize not only provides data analysis capabilities offered with GA4 setup but also allows you to execute automated marketing campaigns. You can generate targets based on customer characteristics and automatically execute campaigns, such as sending messages recommending the most likely products to be purchased or sending discount coupons. With Datarize, you can take action while analyzing, making it more practical than GA4.

In conclusion, quantitative metrics can provide insights and become the competitiveness of our online stores. Datarize can be a starting point to make quantitative metric analysis, which is considered difficult due to the complexity of GA4 setup, a little easier. By using numbers to find the next "what we should do" and taking action, we can grow our business.