A Practical Introduction to Google Analytics

, I had the chance to work with Google Analytics, a strong platform for monitoring and understanding person behaviour throughout an e-commerce web site that sells clothes. 

My activity was to construct an information pipeline that exports GA4 information to BigQuery, a Google Cloud information warehouse. Nonetheless, I rapidly bumped into a typical difficulty: lots of the accessible guides have been outdated or inconsistent, which made the method extra time-consuming than anticipated.

On this article, I’ll stroll you thru a transparent and up-to-date overview of Google Analytics, clarify its key ideas, spotlight a very powerful reviews, and present you a working instance of easy methods to export GA4 information utilizing the Google Analytics Information API with Python.

Curious to see what GA4 can do for you? Let’s dive in!

Desk of Contents:

• Life Cycle of Google Analytics
• Dimensions and Metrics
• Discover Core Stories of GA4
• Discover Information API

Life Cycle of Google Analytics

Google Analytics permits to know the completely different levels of the shopper journey, providing precious insights at every step.

It begins with the Acquisition, the place you entice customers and spark person curiosity in your enterprise. This stage focuses on channels and methods that deliver the shopper to your web site or app.

Subsequent is Engagement, which seems at how customers work together along with your content material or merchandise. For instance, they may browse pages, watch movies, or add objects to their procuring cart.

Then comes Monetization and Retention, that are a part of essentially the most vital section. Monetization section permits to know the place customers make purchases, turning them into prospects, whereas Retention measures how typically customers return, serving to to evaluate long-term satisfaction and loyalty.

By analyzing every stage of the journey, it’s attainable to establish what’s working, uncover areas for enchancment and make smarter and data-driven selections to spice up the model’s efficiency.

Dimensions and metrics

Earlier than going additional, it’s vital to know a elementary idea in Google Analytics: each report is constructed utilizing dimensions and metrics. Understanding how dimensions and metrics work collectively is important for decoding reviews and turning information into significant data.

Dimensions

Dimensions are qualitative attributes that group your information. The core dimensions are:

• Marketing campaign is a paid promotion or Marketing marketing campaign
• Supply is the place the person got here from. As an example, it may be from a web site or a social community like Instagram and Fb.
• Medium is the overall class of the visitors supply, similar to natural, CPC and referral. 
• Channel is a rule-based group of visitors sources, mediums, or different guidelines to separate visitors. Examples of channels are Natural Search, Paid Search and Social.

Metrics

Alternatively, metrics include quantitative values. A very powerful metrics are:

• Lively customers are individuals who interact with the positioning or app
• New customers are individuals who go to the positioning or app for the primary time
• Returning customers are individuals who have visited beforehand
• Classes are teams of person interactions inside a given time-frame
• Engaged Classes are classes lasting a minimum of 10 seconds
• Occasion is any tracked person motion, like clicking, scrolling and visiting for the primary time
• Key occasion is a big motion that contributes to enterprise objectives, similar to a purchase order or a sign-up
• Complete income is the earnings from purchases, subscriptions, and promoting

Begin to play with Google Analytics

As soon as you’re aware of the important thing ideas of Google Analytics, it’s time to place them into observe on the platform itself. An important start line is Google’s introduction course to Google Analytics, which supplies entry to a free demo account. This account permits you to discover real-world information and experiment with the platform’s options.

On this tutorial, we’ll use Google Analytics to discover and analyse the information from the Google Merchandise Retailer, a web based retailer that sells Google-branded merchandise. It’s an ideal sandbox for studying easy methods to observe person behaviour, monitor efficiency, and acquire actionable insights. You’ll be able to entry the Google Analytics demo account utilizing this link. It’s best to see a web page just like the screenshot beneath.

These are pages which are going to be explored:

• Normal overview
• Acquisition overview
• Engagement overview
• Monetisation overview
• Retention overview

Normal Overview

The primary web page you’ll see is the house web page, which supplies a high-level abstract of person behaviour on the Google Merchandise Retailer. It highlights key efficiency indicators, similar to Lively customers, Key occasions, Complete occasion rely and Purchases. These metrics provide a fast overview of how customers are participating with the web site or app and the way nicely it’s performing.

To view the metrics in real-time, click on the Stories button and choose Actual-time overview. This function offers a reside snapshot of present person exercise, making it straightforward to observe what’s taking place on the web site because it happens.

On the prime of the Actual-time Overview report, you’ll discover key efficiency indicators, together with the variety of lively customers within the final 5 and half-hour. Beneath, a sequence of tables present an in depth breakdown of person exercise, displaying:

• The place customers are coming from. It may be measured by metrics like supply, medium and channel.
• Demographic and geographic information will help to know who the customers are.
• What content material they’re viewing. Examples of content material are web page titles and display names.
• What actions they’re taking.
• Which key occasions they full.

Acquisition Overview

The acquisition report is a precious instrument for understanding the place customers and visitors are coming from. On the prime, you’ll discover KPIs like Lively customers and New customers, giving a snapshot of person exercise. Just under the KPIs, completely different tables present particular particulars of how customers are arriving on the web site. 

Throughout the overview part, there are two detailed reviews. The primary report is the person acquisition report, which focuses on marketing campaign supply and medium that we see from that person. Subsequent is the visitors acquisition report, which considerations session supply, session medium and session marketing campaign.

Engagement Overview

Whereas the acquisition report solutions the query “The place are Customers and visitors coming from?”, the engagement report helps to know how customers are interacting with the positioning or app. 

Key Efficiency Indicators on this report embody the common engagement time per lively person, the common engaged session rely per lively person, the variety of web page views (for web site) or display views (for app), and the rely of occasions.

Beneath KPIs, two primary tables present high-level particulars of person exercise. The desk grouping information by occasion title exhibits what customers are doing on the web site or app. Frequent occasions are viewing an online web page, starting a session or seeing a promotion banner or provide. The opposite desk segments the information by web page title and display class permitting us to know which pages individuals are staying on the longest or essentially the most seen pages. 

Monetization Overview

Now, we now have the Monetization overview which presents high-level metrics to quantify income. These embody whole income, whole income from purchases and the whole income from promoting.

To dive deeper into gross sales efficiency, you may discover the e-commerce buy report. This report accommodates a desk damaged down by merchandise title, permitting us to see which merchandise are essentially the most worthwhile, seen, added to the cart or bought.

From the desk, the Tremendous G Quilt Socks stand out as essentially the most performing objects with the very best income.

Retention Overview

Lastly, there’s the retention overview report that provides an concept of how nicely the web site or app retains customers over time. Key efficiency indicators embody the whole variety of new customers and the whole variety of returning customers.

One of the helpful options of this report is the Consumer Retention visualisation that exhibits how regularly customers return after their preliminary go to. As an example, it solutions questions like “What number of customers who first visited on a selected date (date 0) got here again within the following days?”.

This report is important for evaluating person loyalty and long-term engagement, serving to to establish tendencies and enhance methods to maintain customers coming again.

Discover Information API

Now that we perceive how the reviews are structured, let’s take a step additional and see easy methods to export information utilizing the Google Analytics Information API.

Arrange Information API

Earlier than writing any code, we have to full a couple of setup in Google Cloud Console:

• Create a brand new undertaking or choose an already current one
• Allow the “Google Analytics Reporting API” on your undertaking
• Create a service account, generate the credentials and obtain the JSON file. 

For deeper particulars, I like to recommend this YouTube video, which helped me lots with Google Cloud Console setup. 

After we should discover the property ID, which is required within the code later. This time we have to go to Google Analytics, press Admin from the menu and choose Property Particulars. Simply copy and paste the property ID in your code.

The final step consists of putting in the mandatory Python libraries:

pip set up google-analytics-data==0.18.18
pip set up google-auth-oauthlib==1.2.2

Export report Information utilizing Information API

As soon as the setup is full, we are able to use the Google Analytics Information API to obtain the report information with Python. Let’s say we need to export a report displaying lively customers and new customers, damaged down by date. On this case:

• Metrics: activeUsers, newUsers
• Dimensions: date

To search out the proper discipline names for dimensions and metrics utilized by Information API, consult with the official GA4 API reference. It contains complete tables for every.

Now, it’s time to point out an instance of code to export the information. First, we instantiate the analytics information shopper. Then, we outline the report request with the scale, metrics and date vary. Lastly, we are able to execute the report request.

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.sorts import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)

PROPERTY_ID = "your-property-id"
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "your-path-to-json-file"
shopper = BetaAnalyticsDataClient()

request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="city")],
        metrics=[Metric(name="activeUsers"),Metric(name="newUsers")],
        date_ranges=[DateRange(start_date="2024-01-01", end_date="yesterday")],
    )

response = shopper.run_report(request)

To transform the API response right into a pandas Dataframe, we want another strains of code:

# Extract column headers
headers = [header.name for header in response.dimension_headers] + 
        [header.name for header in response.metric_headers]

# Extract rows
rows = []
for row in response.rows:
    row_data = [dimension_value.value for dimension_value in row.dimension_values] + 
            [metric_value.value for metric_value in row.metric_values]
    rows.append(row_data)

# Create a DataFrame
df = pd.DataFrame(rows, columns=headers)

That’s nice! We now have efficiently retrieved the report information from Google Analytics utilizing the Information API. 

Remaining ideas:

This was an outline of Google Analytics, its core reviews and Information API. With these instruments, you may acquire a deeper understanding of the place customers are coming from, how they interact along with your content material, which merchandise are performing nicely and the way successfully your website is retaining guests over time. 

Nonetheless, it’s value noticing a couple of limitations of the Information API. There could also be discrepancies between the API and the GA4 Consumer Interface resulting from information processing delays. Google Analytics interface can replace even earlier day’s information after a brief lag. Furthermore, Google Analytics typically applies information sampling, particularly on giant datasets, which can result in mismatches when evaluating outcomes with the uncooked API output. 

Regardless of the challenges, getting began with Google Analytics is a precious step towards making data-informed selections. I hope this tutorial provided a transparent and sensible start line to start with confidence. Thanks for studying! Have a pleasant day!

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