Navigating the Data Deluge: Prioritizing Key Metrics in the Age of Google Analytics 4

Published: 28 March 2024

Navigating the Data Deluge: Prioritizing Key Metrics in the Age of Google Analytics 4

With the advent of Google Analytics 4 (GA4), the key business challenge becomes not collecting data but discerning what truly matters in the sea of data. 64% of marketing executives believe data-driven marketing is crucial to success in a hyper-competitive global economy. By prioritizing key metrics and avoiding the trap of tracking everything, businesses can gain meaningful insights to drive informed decision-making and optimize their online presence effectively. In this article, we want to share our thoughts about the ‘tracking everything’ mindset and what to look at in GA4.

Table of Contents:

  1. You Can’t Improve What You Don’t Measure
  2. Measure As Much As Possible Mindset
  3. How to Overcome It
  4. What Are the Metrics in Google Analytics?
  5. Metrics And Dimensions in Google Analytics 4
  6. Key Google Analytics Metrics to Track
  7. Google Analytics 4 Custom Metrics for eCommerce

You Can’t Improve What You Don’t Measure

Tracking is a key pillar of a thriving business. You should discern what is effective and what is not; otherwise, you remain in the dark. There are plenty of things that can and should be regularly measured and monitored. If you can’t measure them, you won’t be able to make data-driven decisions to manage or expand effectively.

Big Data and Analytics Market Share by Countries The global big data analytics market is expected to grow significantly over the coming years, with a forecasted market value of over 650 billion dollars by 2029. It is the biggest market in the US. Data-driven marketing is predicted to grow at a compound annual growth rate (CAGR) of 20.4% from 2021 to 2028.

According to a 2023 survey by Drexel University’s LeBow College of Business, 77% of professionals focused on data and analytics emphasize the importance of prioritizing data-driven decision-making in their programs. Almost 73% of those using data saw improvements in operational efficiency, and 62% noted that relevant data significantly cut costs. Additionally, 57% of respondents mentioned that prioritizing data helped ensure regulatory compliance and minimized risks, highlighting a holistic approach to data-driven strategies.

Data-driven decisions statistics

Marketing analytics influence just over half (53%) of marketing decisions, according to a survey by Gartner in 2022. Based on a Harvard business survey, 26.5% of businesses considered themselves data-driven.

Too much data overwhelms businesses, making it tough to grasp all the available data and determine how it can be leveraged to enhance business outcomes. That’s why businesses must separate what they want from analytics to what they need. But instead of this, mistakenly comes the “tracking-as-much-as-possible” mindset.

Measure As Much As Possible Mindset

Businesses might think they know what metrics they want to be tracked, but in reality, they don’t match their business goals. That’s how “the measure everything mindset” comes about. Rather than gaining actionable insights, this approach can lead to data overload and a lack of meaningful analysis, ultimately hindering informed decision-making and impeding progress toward desired outcomes.

There are a few common reasons why businesses adopt the mindset of “tracking everything.” We will highlight the key ones:

Insufficient KPIs

Many companies have specific goals they want to achieve but find it hard to turn these into measurable KPIs that can track their progress. This challenge is particularly noticeable when they’re just starting and trying to figure out what data they should gather from their online interactions.

Confusion between optional and vital data

It’s essential to differentiate between “nice-to-have” and crucial data your business needs. Having extra data that’s just optional can be useful, but it’s not always necessary. As businesses evolve and digital tools advance, “nice-to-have” becomes outdated. Dealing with this kind of data can sometimes cause more headaches than useful insights, especially if there are costs involved in collecting, managing, and storing it.

Concerns about not capturing enough data

The idea that data might not be able to address important business concerns can stress out business owners, leading them to want to track everything “just in case”. However, this approach collects huge amounts of data that often get overlooked because it takes effort to make sense of everything. As a result, either the important business questions remain unanswered, or the data paints a distorted picture of what’s happening.

Low awareness of data utility or available analytics

The analytics field is always evolving, so it’s no surprise that many companies find it hard to stay on top. It is crucial to grasp the data your organization collects, but unfortunately, many organizations don’t feel confident enough in their data literacy skills, especially regarding analytics. This lack of understanding often pushes organizations toward the ‘tracking everything’ mindset. Without a clear understanding of how different analytics tools can benefit them and what all the technical terms mean, companies often end up not fully utilizing some parts of their analytics platforms while overusing others.

How to Overcome It

You should distinguish between desired and essential data to abandon the “track everything” approach. This requires fundamentally reevaluating your perspective on data and its role within your business. What else?

  • Setting KPIs can give you the lowdown on your organization’s standing compared to its goals. Setting these metrics is crucial; it’s hands down the most important step for any organization dipping its toes into analytics tracking. 
  • It’s crucial to monitor extra supporting data that will help those KPIs and expand your capacity to paint a fuller picture with the data. 
  • Gain insights from historical data to evolve in the present and future. Utilize current data to adjust for optimal future gains. Continuously iterate on future data to adapt to organizational changes.
  • Dive deeper into analytics platforms like Google Analytics, the most popular and utilized analytics platform worldwide. This tool could be the mainstay of your analytics setup, acting as the backbone for all your data requirements.

Google Analytics 4 dashboard


What Are the Metrics in Google Analytics?

A “metric” in Google Analytics is a quantitative measurement that provides insight into various aspects of your website or app performance. These metrics help business owners understand how users interact with their online presence and gauge the effectiveness of their marketing efforts. Metrics in GA4, such as sessions, bounce rate, conversion rate, average session duration, and others, are distributed among ten categories, facilitating a clear comprehension of the aspects you aim to gauge.

Metrics And Dimensions in Google Analytics 4

When working with GA4, grasping the distinctions between metrics and dimensions is super important. Dimensions, such as country, language, browser, device category, and others, are those attributes that give your data some context, typically expressed in words rather than numbers.

Keep in mind that dimensions and metrics aren’t the same thing. Dimensions refer to the qualitative side of your data, while metrics are all about the numbers and the quantitative measurements. In simple terms, metrics in GA4 are the hard numbers. Understanding the difference between dimensions and metrics in Google Analytics is crucial for marketers. Combining metrics with dimensions allows marketers to carve out more specific data sets and contrast them when merging.

If you encounter a roadblock with dimensions and metrics, be sure to visit VIDEN’s blog for extra insights on maximizing your GA4 experience.

Key Google Analytics Metrics to Track

We divided these metrics into 2 sections: default and custom (for eCommerce sites). Speaking about default metrics, we can highlight the following:

  • Users: Total number of users visiting your site.
  • Active Users: Users who have had an engaged session within a defined timeframe.
  • New Users: Users visiting your site for the first time.
  • Sessions: The total number of user sessions on your site.
  • Engagement Rate: Percentage of sessions where users engaged with your content.
  • Average Engagement Time: The average amount of time users spend engaged with your content per session. 
  • Events: Captures specific user interactions beyond pageviews.
  • Event Name & Parameters: Provide details about the specific events and any associated data.
  • Conversions: Measures successful completion of actions you define as valuable.
  • Session Conversion Rate: Percentage of sessions resulting in a conversion.
  • User Conversion Rate: Percentage of converted users.
  • Traffic Source (Dimension): Shows how users found your website.
  • Channel Grouping (Dimenstion): Groups traffic sources into broader categories (e.g., Paid Search, Organic Search, Social).
  • Page Views: The total number of individual page loads on your site.
  • Pages per Session: The average number of pages viewed per session.
  • Bounce Rate: Percentage of single-page sessions where users leave without further interaction.

Google Analytics 4 Custom Metrics for eCommerce

Custom metrics within Google Analytics enables tracking of particular facets of your website’s performance, extending beyond the parameters covered in the standard reports. Check key metrics for eCommerce sites:

  • Purchase Revenue: Total revenue generated from online sales.
  • Purchase Count: Number of completed purchases.
  • Items Sold: Total number of items sold across all purchases.
  • Average Order Value: Average amount spent per order.
  • Item List Views: Tracks how many times a list of products is displayed on a page.
  • Add to Carts: Captures instances where a product is added to the shopping cart.
  • Removals from Cart: Tracks instances where a product is removed from the shopping cart.
  • Cart Abandonment Rate: Percentage of shopping carts abandoned before checkout.
  • Item Revenue by Brand/Category: Analyzes revenue generated by specific brands or product categories.
  • Select Item: Measures how often item is selected from the list.
  • Item Detail Page Views: Tracks how many times product detail pages are viewed.
  • Time Spent on Product Pages: Analyzes average time spent on product detail pages.
  • Coupon Redemptions: Tracks the number of times coupons are used at checkout.
  • Refund Rate: Percentage of orders resulting in a refund.
  • Checkout Steps: Tracks the number of steps in your checkout process.
  • Checkout Abandonment Rate by Step: Analyzes abandonment rates at each step of the checkout process.

Understanding and analyzing these metrics can provide valuable insights and help marketers make data-driven decisions to improve their online presence and achieve business goals. Contact the VIDEN team to make sure that you are tracking everything you need to track, especially the right kind of conversions. Get a free audit of your GA4 account now.  

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