A Practical Introduction to Google Analytics

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

My job was to construct a knowledge pipeline that exports GA4 knowledge to BigQuery, a Google Cloud knowledge warehouse. Nonetheless, I rapidly bumped into a typical problem: lots of the obtainable guides had been outdated or inconsistent, which made the method extra time-consuming than anticipated.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 studies, and present you a working instance of how one can export GA4 knowledge utilizing the Google Analytics Knowledge 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 Experiences of GA4
• Discover Knowledge API

Life Cycle of Google Analytics

Google Analytics permits to grasp the completely different levels of the client journey, providing worthwhile insights at every step.

It begins with the Acquisition, the place you appeal to customers and spark consumer curiosity in your online business. This stage focuses on channels and methods that deliver the client to your web site or app.

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

Then comes Monetization and Retention, that are a part of probably the most essential section. Monetization section permits to grasp the place customers make purchases, turning them into clients, 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 determine 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 grasp a elementary idea in Google Analytics: each report is constructed utilizing dimensions and metrics. Understanding how dimensions and metrics work collectively is crucial for deciphering studies and turning knowledge into significant data.

Dimensions

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

• Marketing campaign is a paid promotion or Marketing marketing campaign
• Supply is the place the consumer got here from. For 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, reminiscent of 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 comprise quantitative values. Crucial metrics are:

• Lively customers are individuals who interact with the location or app
• New customers are individuals who go to the location or app for the primary time
• Returning customers are individuals who have visited beforehand
• Periods are teams of consumer interactions inside a given timeframe
• Engaged Periods are classes lasting not less than 10 seconds
• Occasion is any tracked consumer motion, like clicking, scrolling and visiting for the primary time
• Key occasion is a big motion that contributes to enterprise objectives, reminiscent of a purchase order or a sign-up
• Whole income is the earnings from purchases, subscriptions, and promoting

Begin to play with Google Analytics

As soon as you might be aware of the important thing ideas of Google Analytics, it’s time to place them into follow on the platform itself. An important start line is Google’s introduction course to Google Analytics, which gives entry to a free demo account. This account permits you to discover real-world knowledge 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, an internet retailer that sells Google-branded merchandise. It’s an ideal sandbox for studying how one can observe consumer behaviour, monitor efficiency, and acquire actionable insights. You’ll be able to entry the Google Analytics demo account utilizing this link. You need to see a web page just like the screenshot under.

These are pages which are going to be explored:

• Common overview
• Acquisition overview
• Engagement overview
• Monetisation overview
• Retention overview

Common Overview

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

To view the metrics in real-time, click on the Experiences button and choose Actual-time overview. This characteristic offers a dwell snapshot of present consumer exercise, making it straightforward to watch what’s occurring 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 energetic customers within the final 5 and half-hour. Under, a collection of tables present an in depth breakdown of consumer exercise, exhibiting:

• The place customers are coming from. It may be measured by metrics like supply, medium and channel.
• Demographic and geographic knowledge can assist to grasp 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 worthwhile device 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 consumer exercise. Slightly below the KPIs, completely different tables present particular particulars of how customers are arriving on the web site. 

Inside the overview part, there are two detailed studies. The primary report is the consumer acquisition report, which focuses on marketing campaign supply and medium that we see from that consumer. Subsequent is the visitors acquisition report, which issues 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 grasp how customers are interacting with the location or app. 

Key Efficiency Indicators on this report embrace the typical engagement time per energetic consumer, the typical engaged session rely per energetic consumer, the variety of web page views (for web site) or display views (for app), and the rely of occasions.

Under KPIs, two fundamental tables present high-level particulars of consumer exercise. The desk grouping knowledge by occasion title exhibits what customers are doing on the web site or app. Frequent occasions are viewing an internet 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 grasp which pages individuals are staying on the longest or probably the most seen pages. 

Monetization Overview

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

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

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

Retention Overview

Lastly, there’s the retention overview report that offers an thought of how properly the web site or app retains customers over time. Key efficiency indicators embrace the whole variety of new customers and the whole variety of returning customers.

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

This report is crucial for evaluating consumer loyalty and long-term engagement, serving to to determine developments and enhance methods to maintain customers coming again.

Discover Knowledge API

Now that we perceive how the studies are structured, let’s take a step additional and see how one can export knowledge utilizing the Google Analytics Knowledge API.

Arrange Knowledge API

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

• Create a brand new undertaking or choose an already current one
• Allow the “Google Analytics Reporting API” to 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 required Python libraries:

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

Export report Knowledge utilizing Knowledge API

As soon as the setup is full, we will use the Google Analytics Knowledge API to obtain the report knowledge with Python. Let’s say we need to export a report exhibiting energetic customers and new customers, damaged down by date. On this case:

• Metrics: activeUsers, newUsers
• Dimensions: date

To seek out the right area names for dimensions and metrics utilized by Knowledge API, check 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 knowledge shopper. Then, we outline the report request with the size, metrics and date vary. Lastly, we will 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’d like 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’ve got efficiently retrieved the report knowledge from Google Analytics utilizing the Knowledge API. 

Closing ideas:

This was an summary of Google Analytics, its core studies and Knowledge API. With these instruments, you possibly can acquire a deeper understanding of the place customers are coming from, how they interact together with your content material, which merchandise are performing properly and the way successfully your website is retaining guests over time. 

Nonetheless, it’s value noticing just a few limitations of the Knowledge API. There could also be discrepancies between the API and the GA4 Person Interface because of knowledge processing delays. Google Analytics interface can replace even earlier day’s knowledge after a brief lag. Furthermore, Google Analytics generally applies knowledge 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 worthwhile step towards making data-informed selections. I hope this tutorial supplied a transparent and sensible start line to start with confidence. Thanks for studying! Have a pleasant day!

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