Data Analytics Online Marketing April 19, 2023

Data Analytics on GA4: Dashboard, Metrics, & Filters

Writen by promoguynl

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GA4 Data Analytics

Data analytics are at the core of digital marketing and leveraging them is crucial for any online campaign. Data analytics is hard work but we have a number of tools that make it far easier, such as SEMrush and (today’s subject) Google Analytics. Let’s go over the basics so that your operations can be informed by numbers in the future.

Data-driven analytics is of interest to companies because it eliminates the guesswork from the (often hard to grasp) randomness of the Internet. Behavioural insights imbue companies with the ability to make their decisions count and produce reliable results. No more shots in the dark.

Analytics also provides ideas for content, detects niches to capitalise on, and is essential for competitor analysis. Aside from that, it also allows for setting KPIs, benchmarks, and business goals in a realistic manner.

What Does Data Analytics Include?

Data analytics entails examining data sets to detect trends and derive conclusions that emerge from them. In digital marketing, data analysis is all about evaluating the efficiency of marketing activities with the correct metrics and analysing them.

Upper Funnel Metrics

Upper funnel metrics measure how aware people are of your brand or website along with how widespread your audience is. The metrics worth paying attention to include:

  • Pageviews
  • Pages per session
  • Branded search
  • Website Traffic
  • Bounce rate
  • Targeted engagement
  • Inbound links
  • Brand awareness

Lower Funnel Metrics

The lower funnel metrics deal with conversions, sales, and ROI measures. In terms of the sales funnel, this is after interest and in the stages where deliberation and purchase are about to happen. 

Often, visitors aren’t ready to purchase upon first discovery. Allow them some time to reach further down the funnel. Metrics for this part of the funnel can include:

  • Sales qualified leads
  • Revenue
  • ROI
  • Conversion rate

You can transform these metrics into relevant KPIs for your business:

  • Customer acquisition costs
  • Quality of leads
  • Customer retention
  • Customer lifetime value

How to use Google Analytics Dashboard

Let’s go over how to use a data analytics dashboard to derive relevant insights. This article assumes you’ve already set up your Google Analytics, but in case you haven’t, learn how to do that from our dedicated article on the subject.

Here are some things you can do with GA’s dashboard:

  • It allows you to generate graphs.
  • You can alter the name of a Dashboard by clicking on the Dashboard’s title.
  • Add widgets, share, customize or remove the Dashboard using the action bar.
  • Add or remove segments of the dashboard.
  • You can configure date ranges or compare ranges with the date picker.
  • You can rearrange the widgets on the page by dragging them by the title bar to new locations. There are also edit/delete options that appear when your mouse is above the widget’s title bar.
  • Open a linked report by clicking on the widget’s title.
  • The Refresh Dashboard link allows you to readjust with updated data.

You can generate all of the metrics listed above and use them to derive insights. However, you first need to learn how to filter them.

What are the Options for Filtering Data in Google Analytics (Types of Filters)?

  • Predefined filters: These exclude/Include only traffic from the ISP domain. This option allows for categorising and filtering traffic from a specific domain.
  • Exclude/Include traffic with IP address filtering: Using this filter excludes/includes only clicks from a certain IP address. Filter out simple ranges of addresses by using ones that begin with or that end with similar parameters.

To filter more complicated ranges of addresses, apply Custom Filters, e.g. to Exclude/Include using IP Addresses or specify a regular expression as the Filter Pattern.

Exclude/Include only traffic to the subdirectories: Apply this filter to exclude/include traffic to a particular subdirectory only (such as “/about” or “/help” or similar subdirectories).

Exclude/Include only traffic to the hostname: This filter excludes/includes traffic to a particular hostname only.

Custom Filtering

  • Exclude: A type of filter that excludes log file lines which match the “Filter Pattern”. It can then ignore the matches to produce more specific, relevant data.
  • Include: This filter includes does the opposite of the previous one by including log file lines that match the Filter Pattern.
  • Case Changing: Convert the field into uppercase or lowercase characters. Filters only affect letters so they don’t interfere with special characters, symbols, or numbers.
  • Search & Replace: A simple filter you can use to search for patterns within a field and replace them with alternate forms.
  • Advanced Filtering: This option lets you build a field from other ones by applying Extract fields to the selected fields, then constructing a third one using the Constructor.

Uses for Filters

Filters can be used in several ways:

Exclude internal traffic: To filter out internal traffic from a report, arrange a filter setting that detects all of the IP addresses that you do not need.
Report on activity in specific directories: Similarly, to specify a directory, use an “Include filter” that identifies only that directory to include it.
Track subdomains in separate views: If you want to track www.example.com as well as its sub-directory, help.example.com and info.example.com, you can create separate views for each one.

In Which order does Google Analytics filter data?

On the default settings, Google Analytics will filter in the order in which the filters were added.

Deriving Data Analytics Insights

Here is what you can gather from the data you receive from GA4 or similar analytics software:

  • Users: If you’ve got low users compared to your ad spending, then your advertising is not bringing its target demo.
  • Bounce Rate/Exit Rate: A high bounce rate or exit rate isn’t necessarily a bad thing, but can be indicative of a lack of interest in the rest of the website. This is highly dependent on the purpose of the page (e.g., it’s fine for a one-off blog post to have a high bounce rate if it’s not designed to redirect traffic). Similarly, exit rates being in the right place is a good thing. We’ve covered this in more detail, previously.
  • Pages per Session: If you need to use your landing page to get viewers to click around the website and explore, you should be looking to optimise pages per session. Add CTAs and offers or have a clear design flow to do that.
  • Average Session Duration: Low session durations aren’t always a bad thing. If the time it takes to read a page is very low, it is doing its job. However, if you’re page has a lot of necessary info and the session durations don’t match up or if it’s meant to lead to a sale, something on the page isn’t resonating with your audience. You might want to see if you’re targeting the right audience, whether the info is clear, or if the page speed/UX is bothering your demo.
  • Page Views: Lower traffic, depending on the size of your target demographic, can be a bad thing. However, this also depends on how relevant the users are.
  • Conversions: Are conversions lower than the rate you need to make a profit? Find the barriers to conversion, improve UX, revamp your graphic design, put in offers, and have clear language that sets you apart from competitors.
  • Cost per Conversion: High CPC means you might be overpaying for your ads, in which case your options are to either pick new keywords or redirect your marketing efforts to a lower-cost method.

Tip: Enable real-time data analytics by enabling the Real-Time option. This will continuously update your GA with frequent hits as they come in.

Limitations of Google Analytics

Certain data is off-limits for collection and tracking. The data google analytics goals are unable to track is multiple types of “personal identifiable info” (for good reason). Data that Google Analytics prohibits collecting are things that allow personal identification, as stated in the terms of service, including an individual’s name, billing address, email address, etc.

When it comes to offline inventories, Google Analytics cannot collect data from these systems by default, but you can use the data import option for these jobs. These can be done by uploading CSV files (kind of like an Excel sheet) from a CRM or similar software package.

Similarly, the ability for GA4 to operate in certain regions may be subject to cookie policies. Regions with the GDPR may have systemic barriers in place. The free version of GA can also be a bit of a minefield, offering limited or inaccurate information.