How to Start ROI for Beginners

How to Start ROI Tracking with Google Analytics 4 (GA4)

Understanding your return on investment (ROI) is crucial for making informed decisions about your marketing efforts. Google Analytics 4 (GA4) provides powerful tools to track and analyze your ROI, helping you identify which campaigns and strategies are driving the most value. This article will guide you through the essential steps to set up ROI tracking in GA4, focusing on configuring conversions, attributing value to them, and analyzing your data to optimize your marketing spend. We’ll explore practical examples and best practices to ensure accurate and actionable insights.

Table of Contents

• Defining Key Conversions in GA4
• Setting Conversion Values to Calculate ROI
• Configuring Attribution Models for Accurate ROI
• Analyzing and Reporting ROI in GA4

Defining Key Conversions in GA4

The first step in tracking ROI is accurately defining what constitutes a valuable conversion for your business. In GA4, conversions are based on events. You’ll need to identify and configure the specific events that represent meaningful interactions or outcomes that contribute to your revenue. These can range from simple actions like form submissions to complex transactions like e-commerce purchases. Defining these conversions precisely is paramount for accurate ROI calculations.

Here are some common examples of conversions you might track:

• E-commerce purchases
• Form submissions (e.g., lead generation forms, contact forms)
• Phone calls
• Email sign-ups
• Account creations
• Video views (e.g., watching a demo video)
• Downloading a resource (e.g., a whitepaper or ebook)

Let’s look at practical examples of configuring these conversions: E-commerce Purchase Tracking For e-commerce businesses, tracking purchases is the most crucial conversion. GA4 often automatically detects e-commerce events if you’ve properly implemented the enhanced e-commerce tracking in your data layer. If not, you’ll need to implement the necessary code to send the `purchase` event to GA4.

// Example JavaScript code to send a purchase event to GA4
gtag('event', 'purchase', {
  "transaction_id": "T12345",
  "affiliation": "Online Store",
  "value": 99.99,
  "currency": "USD",
  "tax": 5.00,
  "shipping": 10.00,
  "items": [
   {
      "item_id": "SKU_12345",
      "item_name": "Example Product",
      "affiliation": "Online Store",
      "coupon": "SUMMER_SALE",
      "discount": 0,
      "index": 0,
      "item_brand": "Brand Name",
      "item_category": "Category",
      "item_category2": "Subcategory",
      "item_category3": "Further Subcategory",
      "item_category4": "And even further",
      "item_category5": "And more",
      "item_list_id": "related_products",
      "item_list_name": "Related Products",
      "item_variant": "Variant",
      "location_id": "ChIJP3Sa8ziYEmsRUcEkFUiPYRk",
      "price": 99.99,
      "quantity": 1
    }
  ]
});

Once you’ve implemented this, go to GA4 > Configure > Conversions and click “New conversion event”. Enter `purchase` as the event name to mark it as a conversion.

Form Submission Tracking For lead generation, tracking form submissions is vital. You can configure this by creating a custom event in Google Tag Manager (GTM) that triggers when a form is submitted. First, set up a trigger in GTM that listens for form submissions. Then, create a GA4 event tag that fires when the trigger activates.

//Example in GTM for Form Submission
//Trigger Configuration:
//Trigger Type: Form Submission
//Trigger Fires On: All Forms or Specific Forms (based on your needs)

//GA4 Event Tag Configuration:
//Tag Type: Google Analytics: GA4 Event
//Event Name: form_submission
//Parameters:
//   form_id: {{Form ID}} (if available)
//   form_name: {{Form Element}} (if available)

In GA4, navigate to Configure > Conversions and create a new conversion event named `form_submission`. Now, every time a form is submitted, GA4 will record it as a conversion.

Phone Call Tracking Tracking phone calls requires a bit more setup, typically involving a call tracking service. These services provide unique phone numbers for different marketing channels. When someone calls a number, the service records the call and can pass data to GA4 using the Measurement Protocol or integrations.

Here’s an example using the Measurement Protocol:

// Example of sending a phone_call event using the Measurement Protocol
// Replace with your GA4 Measurement ID and API Secret
const measurementId = 'G-XXXXXXXXXX';
const apiSecret = 'YOUR_API_SECRET';

async function sendPhoneCallEvent(phoneNumber, callSource) {
  const url = `https://www.google-analytics.com/mp/collect?measurement_id=${measurementId}&api_secret=${apiSecret}`;

  const data = {
    client_id: 'YOUR_CLIENT_ID', // Replace with a unique client ID
    events: [{
      name: 'phone_call',
      params: {
        phone_number: phoneNumber,
        call_source: callSource
      }
    }]
  };

  try {
    const response = await fetch(url, {
      method: 'POST',
      body: JSON.stringify(data)
    });

    if (response.ok) {
      console.log('Phone call event sent successfully');
    } else {
      console.error('Failed to send phone call event:', response.status);
    }
  } catch (error) {
    console.error('Error sending phone call event:', error);
  }
}

// Example usage:
sendPhoneCallEvent('555-123-4567', 'Google Ads');

After sending the `phone_call` event, create a corresponding conversion in GA4 under Configure > Conversions, naming it `phone_call`. Remember to replace `YOUR_CLIENT_ID`, `G-XXXXXXXXXX`, and `YOUR_API_SECRET` with your actual values. You also need to have a system in place to generate and store the `client_id`.

Expert Tip: Focus on the 20% of conversions that drive 80% of your revenue. Prioritize tracking these key interactions to get the most impactful ROI data. It is important to properly set up the data layer to ensure the accurate flow of data.

Setting Conversion Values to Calculate ROI

Defining conversions is only the first step. To calculate ROI, you need to assign a monetary value to each conversion. This value represents the revenue generated (or expected to be generated) from that conversion. The accuracy of your ROI calculations depends heavily on how well you can estimate these conversion values. For e-commerce, this is straightforward – it’s the revenue from the purchase. For other conversions, it requires careful estimation based on your sales process and customer lifetime value.

Here are some approaches for assigning conversion values:

• E-commerce: Use the actual revenue from the purchase.
• Lead Generation: Estimate the average revenue generated from a lead. This can be calculated by multiplying your lead-to-customer conversion rate by your average customer lifetime value.
• Phone Calls: Similar to lead generation, estimate the value based on the likelihood of a phone call resulting in a sale.
• Email Sign-ups: Estimate the value based on the average revenue generated from email subscribers. Consider the rate at which subscribers convert to paying customers.

Let’s look at some practical examples:

E-commerce Conversion Value In the `purchase` event code, the `value` parameter represents the revenue from the transaction. GA4 automatically uses this value when you mark the `purchase` event as a conversion. Ensure your e-commerce tracking is sending the correct revenue value for each purchase. Also make sure the `currency` parameter is correctly set.

// Example JavaScript code for a purchase event (repeated for context)
gtag('event', 'purchase', {
  "transaction_id": "T12345",
  "affiliation": "Online Store",
  "value": 99.99,  // This is the conversion value
  "currency": "USD",
  "tax": 5.00,
  "shipping": 10.00,
  "items": [
   {
      "item_id": "SKU_12345",
      "item_name": "Example Product",
      "affiliation": "Online Store",
      "coupon": "SUMMER_SALE",
      "discount": 0,
      "index": 0,
      "item_brand": "Brand Name",
      "item_category": "Category",
      "item_category2": "Subcategory",
      "item_category3": "Further Subcategory",
      "item_category4": "And even further",
      "item_category5": "And more",
      "item_list_id": "related_products",
      "item_list_name": "Related Products",
      "item_variant": "Variant",
      "location_id": "ChIJP3Sa8ziYEmsRUcEkFUiPYRk",
      "price": 99.99,
      "quantity": 1
    }
  ]
});

GA4 will automatically sum all purchase values to give you total revenue.

Lead Generation Conversion Value Estimating the value of a lead requires some analysis. Let’s say you know that 10% of your leads become customers, and your average customer lifetime value is $500. Then, the value of a lead is 10% * $500 = $50. When configuring the `form_submission` event in GTM, you can add a `conversion_value` parameter.

//Example in GTM for Form Submission (adding conversion value)
//GA4 Event Tag Configuration:
//Tag Type: Google Analytics: GA4 Event
//Event Name: form_submission
//Parameters:
//   form_id: {{Form ID}} (if available)
//   form_name: {{Form Element}} (if available)
//   conversion_value: 50  // The estimated value of the lead
//   currency: USD

Then, in GA4, when you define the `form_submission` event as a conversion, ensure the “Value / Currency” setting is configured to use the value sent with the event. This way, GA4 will attribute $50 to each form submission.

Phone Call Conversion Value The process is similar for phone calls. If you determine that 5% of phone calls result in a sale, and your average sale value is $200, then the value of a phone call is 5% * $200 = $10. When sending the `phone_call` event using the Measurement Protocol, include the `conversion_value` parameter.

// Example of sending a phone_call event using the Measurement Protocol (with value)
const measurementId = 'G-XXXXXXXXXX';
const apiSecret = 'YOUR_API_SECRET';

async function sendPhoneCallEvent(phoneNumber, callSource, conversionValue) {
  const url = `https://www.google-analytics.com/mp/collect?measurement_id=${measurementId}&api_secret=${apiSecret}`;

  const data = {
    client_id: 'YOUR_CLIENT_ID', // Replace with a unique client ID
    events: [{
      name: 'phone_call',
      params: {
        phone_number: phoneNumber,
        call_source: callSource,
        conversion_value: conversionValue,
        currency: 'USD'
      }
    }]
  };

  try {
    const response = await fetch(url, {
      method: 'POST',
      body: JSON.stringify(data)
    });

    if (response.ok) {
      console.log('Phone call event sent successfully');
    } else {
      console.error('Failed to send phone call event:', response.status);
    }
  } catch (error) {
    console.error('Error sending phone call event:', error);
  }
}

// Example usage:
sendPhoneCallEvent('555-123-4567', 'Google Ads', 10); //Value of $10

Expert Tip: Regularly review and update your conversion values based on your actual sales data. Conversion values should be refined over time to reflect changes in customer behavior and market conditions.

Conversion value is critical to understanding how much a conversion is worth. You can use different conversion values for different campaigns. For example, leads generated from a higher targeted campaign might have a higher conversion value.

Configuring Attribution Models for Accurate ROI

Attribution models determine how credit for a conversion is distributed across different touchpoints in a customer’s journey. Choosing the right attribution model is crucial for accurately assessing the ROI of different marketing channels. GA4 offers several attribution models, each with its own strengths and weaknesses. The default model in GA4 is data-driven attribution, which uses machine learning to determine the contribution of each touchpoint based on your specific conversion data. Understanding how each model works is critical for interpreting your ROI data correctly.

Here’s a comparison of common attribution models:

Attribution Model	Description	Pros	Cons
Data-Driven	Uses machine learning to distribute credit based on your conversion data.	Most accurate for complex customer journeys.	Requires sufficient data to train the model.
Last Click	Gives all credit to the last click before the conversion.	Simple to understand and implement.	Ignores all other touchpoints in the customer journey.
First Click	Gives all credit to the first click in the customer journey.	Highlights the importance of initial touchpoints.	Ignores all subsequent interactions.
Linear	Distributes credit evenly across all touchpoints.	Simple and fair.	Doesn’t account for the varying influence of different touchpoints.
Time Decay	Gives more credit to touchpoints closer in time to the conversion.	Recognizes the increasing importance of recent interactions.	Can undervalue earlier touchpoints.
Position-Based (U-Shaped)	Gives 40% credit to the first click, 40% to the last click, and divides the remaining 20% among the other touchpoints.	Acknowledges the importance of both initial and final interactions.	May not accurately reflect the influence of mid-funnel touchpoints.

Let’s look at some practical examples of configuring and interpreting attribution models:

Configuring the Attribution Model in GA4 To change the attribution model in GA4, navigate to Admin > Attribution settings. Here, you can select the reporting attribution model. The options are “Data-driven,” “Last click,” and “Cross-channel rules-based models.” You can select the attribution model that best reflects how you believe credit should be assigned for your conversions. Data-driven is generally recommended because it dynamically adjusts based on your data.

By default, GA4 uses the data-driven attribution model. If you switch to a different model (like Last Click), GA4 will re-attribute historical data based on the selected model. Note that this will only affect *reporting* of conversions. The data itself is not altered.

Analyzing Attribution Data with Model Comparison Reports GA4 provides Model Comparison reports that allow you to compare how different attribution models would affect the reported value of your marketing channels. To access these reports, go to Advertising > Attribution > Model comparison. This report shows you how many conversions and how much revenue each channel would receive under different attribution models.

For example, you might see that your “Direct” traffic receives significantly more credit under the “Last Click” model than under the “Data-Driven” model. This suggests that “Direct” traffic is often the final touchpoint before a conversion, but other channels may be playing a more significant role in driving those conversions. This information can inform your investment decisions, for example, by suggesting that you should invest more in channels that are undervalued by last-click attribution.

Here’s an example scenario:

• A user first clicks on a Google Ads ad (Paid Search).
• Later, they visit your website through a social media post (Organic Social).
• Finally, they type your website address directly into their browser (Direct) and make a purchase.

Under the Last Click model, “Direct” would receive 100% of the credit for the purchase. Under the First Click model, “Paid Search” would receive 100% of the credit. The Linear model would distribute credit evenly between all three. The Time Decay model would give the most credit to Direct, followed by Organic Social, and then Paid Search. The Data-Driven model would analyze the specific conversion data and assign credit based on the observed patterns. Each model tells a different story about the value of each channel.

Using Path Exploration for Visualizing Customer Journeys GA4’s Path Exploration report (Explore > Path exploration) allows you to visualize the paths users take on your website leading up to a conversion. This report can help you identify common customer journeys and understand the role of different touchpoints.

For example, you can start the path exploration with a specific conversion event (e.g., `purchase`) and then trace back the steps users took before converting. This can reveal which channels are most frequently involved in the conversion path. By visualizing these journeys, you can gain a deeper understanding of how different marketing channels contribute to conversions and optimize your marketing strategy accordingly.

“Attribution is not about finding the perfect model, but about understanding the influence of each touchpoint in the customer journey.”

Avinash Kaushik, Digital Marketing Evangelist

It is important to remember that data-driven attribution models need sufficient data to make accurate assessments. With little data, it may be best to stick to simpler models.

Analyzing and Reporting ROI in GA4

Once you’ve defined conversions, assigned values, and configured attribution, you can begin analyzing and reporting on your ROI in GA4. GA4 offers various reporting options to track your ROI across different channels, campaigns, and user segments. Custom reports are essential for focusing on the specific metrics that are most relevant to your business. Remember that ROI is typically calculated as (Revenue – Cost) / Cost. GA4 can provide the revenue data (conversion value), but you’ll need to integrate your cost data to calculate the complete ROI.

Here are some key metrics to track:

• Conversion Value: The total revenue generated from conversions.
• Conversions: The total number of conversions.
• Cost per Conversion: The cost of acquiring each conversion (Total Cost / Conversions). This metric requires you to import cost data into GA4.
• Return on Ad Spend (ROAS): A more specific form of ROI that focuses on advertising spend (Revenue from Ads / Ad Spend). This also requires importing cost data.
• ROI Percentage: ((Revenue – Cost) / Cost) * 100. Requires imported cost data.

Let’s explore some practical examples of how to analyze and report on these metrics:

Importing Cost Data into GA4 To calculate true ROI, you need to import your cost data into GA4. This can be done using the Cost Data Upload feature (Admin > Data import). You can upload cost data from various sources, such as Google Ads, Facebook Ads, and other advertising platforms. You’ll need to create a CSV file with the following columns:

• Date: The date of the cost data (YYYYMMDD format).
• Source: The source of the traffic (e.g., google, facebook).
• Medium: The medium of the traffic (e.g., cpc, organic).
• Campaign: The name of the campaign.
• Cost: The cost incurred for that day, source, medium, and campaign.

Here’s an example CSV file:

Date,Source,Medium,Campaign,Cost
20240101,google,cpc,Summer Sale,$100
20240101,facebook,cpc,Summer Sale,$50
20240102,google,cpc,Summer Sale,$120
20240102,facebook,cpc,Summer Sale,$60

In GA4, create a new data source with the type “Cost data.” Map the columns in your CSV file to the corresponding fields in GA4 (Date to Date, Source to Source, etc.). Once you upload the file, GA4 will start attributing the cost data to your traffic sources. Important: Ensure the Source, Medium, and Campaign values in your cost data match the values used in your UTM parameters.

Creating Custom Reports for ROI Analysis GA4’s Exploration feature (Explore) allows you to create custom reports tailored to your specific ROI analysis needs. You can create reports that show conversion value, cost, and ROI for different channels, campaigns, and user segments.

Here’s how to create a custom report:

• Go to Explore and select a Blank template.
• In the Variables section, add the following dimensions:
  • Source / Medium
  • Campaign
• Add the following metrics:
  • Conversions
  • Conversion value
  • Cost
• Drag the dimensions to the Rows section.
• Drag the metrics to the Values section.

This will create a report that shows the conversions, conversion value, and cost for each source/medium and campaign. You can then add a calculated metric to calculate the ROI percentage:

//Calculated Metric Formula (ROI Percentage)
((SUM(conversion_value) - SUM(cost)) / SUM(cost)) * 100

This calculated metric will show the ROI percentage for each row in your report. You can further customize the report by adding filters to focus on specific channels, campaigns, or user segments.

Analyzing ROI by User Segments Understanding how ROI varies across different user segments can provide valuable insights for optimizing your marketing efforts. GA4 allows you to create segments based on various criteria, such as demographics, interests, behavior, and technology.

For example, you can create a segment for users who have made a purchase in the past (purchasers) and compare their ROI to that of users who have not made a purchase (non-purchasers). This can help you identify the most valuable user segments and tailor your marketing messages accordingly.

To create a segment, go to Explore and click the “+” icon next to Segments. Choose the criteria for your segment (e.g., “Users who have triggered the `purchase` event”). Then, add the segment to your custom report to see the ROI for that segment.

By analyzing ROI across different user segments, you can identify opportunities to improve your marketing ROI and acquire more valuable customers. The customer acquisition cost may also need to be taken into account in ROI.