How to Use Lookalike Audiences in Google Ads

As businesses look to scale their marketing efforts, one of the biggest challenges they face is expanding their reach while maintaining a high level of targeting precision. Prospecting for new, high-quality users beyond traditional remarketing can feel like trying to find a needle in a haystack. This is where lookalike segments in Google Ads come in.

Lookalike segments (also known as “Lookalike audiences” or “Similar audiences”) help marketers reach new users who share characteristics with their existing, high-value customers. By leveraging Google’s powerful machine learning, lookalike audiences enable you to tap into new pools of potential customers who are more likely to engage, convert, and grow your business.

These segments matter because they take the guesswork out of finding new users. Instead of targeting broad, undifferentiated audiences, lookalike segments enable you to improve your targeting efficiency, driving better conversion rates by reaching people most likely to behave like your best existing customers. This targeted approach reduces wasted ad spend and maximizes the impact of your marketing efforts.

In this article, we’ll dive deep into lookalike segments: what they are, how they work, how to set them up in Google Ads, and how to optimize them for the best results. Whether you’re just getting started with lookalike audiences or looking to refine your strategy, this guide will provide you with the key insights and best practices to maximize their effectiveness in your campaigns.

What Are Lookalike Segments in Google Ads

Lookalike segments in Google Ads are groups of users who share common characteristics with your existing “seed” audience. These users are identified through Google’s machine learning algorithms, which analyze behaviors, interests, and other key factors to create audiences similar to your current high-value customers. By targeting these segments, you can reach new users who are more likely to convert and engage with your business. 

How Google Builds Them:

Lookalike segments are built using first-party data collected from a variety of sources, including:

• Customer Lists: Email or phone number lists uploaded to Google Ads.
• Website Visitors: Using Google’s remarketing tags to track site visitors.
• App Users: Data from users who interact with your mobile app.
• YouTube Engagement: Data based on user interactions with your YouTube videos or channel.

Google then applies machine learning to analyze this data and identify patterns that can be used to find new users who share similar traits. The segment is then applied to relevant campaigns, allowing you to scale your reach with higher accuracy. 

Important Distinction from Old “Similar Audiences”:

Previously known as “Similar audiences,” Google Ads now uses more advanced machine learning models to identify and create lookalike segments. While Similar audiences were mainly created automatically based on your remarketing lists, the current version of Lookalike segments offers more granular control and is optimized for Demand Gen campaigns. Unlike the old system, which used a simple reach slider (narrow vs. broad), lookalike segments allow for more tailored targeting with better alignment to campaign objectives. 

Core Benefits:

• Expand Reach to New Likely-to-Convert Users: By targeting users who share traits with your best customers, lookalike segments help you discover new audiences that are more likely to engage and convert. 
• Better Alignment with Your Best Customers: Instead of casting a wide net with broad targeting, lookalike segments refine your targeting, ensuring that your ads are shown to people who are most likely to act similarly to your current customer base.
• Automated Refreshing of the Segment: Lookalike segments are updated automatically every 1-2 days, ensuring that your audience data remains fresh and relevant, which helps maintain campaign performance over time. 

By utilizing lookalike segments, advertisers can significantly improve their ability to find high-quality prospects and scale their campaigns more efficiently.

When & Why to Use Lookalike Segments

Lookalike segments are primarily used to prospect new audiences and scale existing campaigns by reaching users who share characteristics with your best customers. Here are some key scenarios where lookalike segments can be highly effective:

• Prospecting New Audiences: Instead of relying on broad targeting, lookalike segments help you find new users who are highly likely to engage and convert because they share traits with your most valuable customers.
• Scaling Successful Campaigns: Once you’ve established a successful remarketing or prospecting campaign, using lookalike audiences can help you expand your reach by targeting users who resemble your best-performing segments.
• Complementing Remarketing: Lookalike segments work well alongside remarketing efforts. While remarketing targets users who have already interacted with your business, lookalike segments allow you to expand your audience by reaching users who haven’t yet engaged but are likely to behave similarly.

Campaign Types Supported:

It’s important to note that lookalike segments in Google Ads are supported primarily for certain campaign types, particularly Demand Gen campaigns. These campaigns are designed to discover and reach new potential customers at scale. Lookalike segments are not available in every campaign type, such as Search or Display ads unless specifically integrated with the campaign’s targeting features.

Business Goals Lookalike Segments Support:

Lookalike segments are most effective for businesses that aim to:

• New Customer Acquisition: Use lookalike segments to find new users who are likely to be interested in your products or services, expanding your customer base.
• Drive Conversions at Scale: Reach users who are highly likely to convert, making it easier to achieve your conversion goals even as you scale your campaigns.
• Reach Fresh but Relevant Users: If you’re looking to extend your reach without compromising on quality, lookalike segments provide a way to target users who have similar behaviors and interests to your existing customers.

Comparison to Other Audience Options:

• Remarketing: Remarketing focuses on users who have already interacted with your business (e.g., visited your website or app). While highly effective, remarketing has a limited pool. Lookalike segments, on the other hand, allow you to expand your reach beyond this pool by targeting fresh users with similar characteristics to your best customers.
• Customer Match: Customer Match uses your existing customer data (e.g., email lists) to create a segment for targeting. Lookalike segments use a similar concept but expand the reach by finding users who resemble your existing customers without needing a direct list.
• Custom Intent Segments: Custom intent segments allow you to target users based on their search behavior and intent. While this can help capture high-intent users, lookalike segments refine this by targeting users who are similar to your high-converting audience, potentially increasing the likelihood of conversion.

In essence, lookalike segments combine the best aspects of prospecting and remarketing, enabling you to expand your audience while still maintaining relevance and efficiency in your targeting.

Preparing Your Seed Audience

A seed audience is the group of existing users whose traits and behaviors Google will analyze to create your lookalike segment. These are the people you know are valuable to your business—such as high-converting customers, recent purchasers, or engaged website visitors. Google uses the seed audience to identify common characteristics, which it then applies to find similar users who are likely to be interested in your products or services. The stronger and more relevant your seed audience, the more effective your lookalike segments will be. 

Qualities of a Strong Seed List:

To maximize the effectiveness of your lookalike segment, it’s essential to create a strong seed list that reflects the users who bring the most value to your business. Consider the following qualities:

• High-Value Customers: Users who have made a purchase, engaged with premium content, or repeatedly interacted with your business. These customers are typically your best bet for creating a high-performing lookalike segment.
• Recent Purchasers: Customers who have made a purchase in the last 30–60 days. These users are more likely to have current, active needs similar to new potential customers.
• Engaged Users: Those who regularly interact with your website, app, or YouTube content. For instance, frequent visitors or users who spend a significant amount of time engaging with your content are excellent seed audiences because their behaviors can be more easily matched to fresh prospects.

A well-defined seed audience helps ensure your lookalike segment targets the right people from the start.

Requirements & Minimums:

Google has specific requirements for the seed audience to build a successful lookalike segment.

• Minimum of 100 Matched Users: To create a lookalike segment, you must have at least 100 matched users in your seed audience. This is the minimum threshold Google needs to ensure that the machine learning algorithm has enough data to identify patterns and build accurate lookalike segments.

Data Sources for Seed Audiences:

Google allows you to create seed audiences from various first-party data sources, including:

• Customer Match: Lists of customer data (such as email addresses or phone numbers) that you upload directly into Google Ads. This is one of the most direct methods for targeting your existing customers.
• Website Visitors: Using Google’s remarketing tags to capture users who have visited your website. Google then uses this data to find similar users.
• App Users: Data from users who have installed or interacted with your mobile app. This helps target app users who have a similar profile to your most valuable customers.
• YouTube Engagement: Users who have interacted with your YouTube videos or channel. These users tend to be highly engaged and interested in your content, making them ideal candidates for creating lookalike segments.

These data sources ensure that your lookalike audience is built on accurate and relevant data, which is crucial for successful targeting.

Data Quality and Privacy Considerations:

While building your seed audience, it’s essential to ensure that your data is of high quality and complies with Google’s policies and privacy regulations. Key considerations include:

• Match Rate: The more accurate and consistent your data, the higher the match rate will be. Ensure your email lists, phone numbers, or other data points are up to date and correct.
• Up-to-Date Lists: Regularly update your customer lists to ensure they reflect your most recent and engaged users. Stale data can lead to irrelevant lookalike segments, which can decrease the effectiveness of your campaigns.
• Privacy Compliance: Ensure that your data collection and usage comply with GDPR (if applicable), CCPA, and Google’s data usage policies. This is critical to avoid potential violations that could affect your ad account. Google enforces strict data privacy regulations, so it’s essential to maintain compliance throughout your campaign.

By preparing a strong seed audience, ensuring data quality, and staying compliant with privacy regulations, you set yourself up for success in creating effective and high-performing lookalike segments in Google Ads.

Step-by-Step Setup Guide for Lookalike Segments in Google Ads

Setting up lookalike segments in Google Ads allows you to target new users who share similar behaviors and characteristics with your best existing customers. Follow these easy steps to create and apply your lookalike audience effectively.

Step 1: Upload or Select Your Seed Audience

Before you can create a lookalike segment, you first need to define your seed audience. This audience should consist of your most valuable customers, recent purchasers, or highly engaged users.

• Navigate to Audience Manager: In your Google Ads account, go to Audience Manager. You’ll find this under the Shared Library section.
• Select Your Seed Audience: You can either upload a new seed audience (e.g., customer email lists, website visitors, app users, etc.) or select an existing audience that has already been defined.

This seed audience serves as the foundation for Google’s machine learning model to create the lookalike segment.

Step 2: Create a New Lookalike Segment

• Once your seed audience is ready, you can now create your lookalike segment.
• Go to the Audience Manager: In Google Ads, choose “New audience”.

Select “Lookalike”: From the options, choose “Lookalike”. This will allow Google Ads to generate an audience based on users who resemble the behaviors and characteristics of your seed audience.

Step 3: Set Targeting Parameters

Next, you need to define how broad or narrow your lookalike audience will be. This allows you to control the reach and precision of your targeting.

• Choose Geography/Location: Select the target geography or location for your lookalike audience. Google Ads allows you to target specific countries, regions, or cities.
• Set Reach Type: Choose the reach type for your lookalike segment:
  • Narrow: More closely resembles your seed audience, resulting in fewer users but higher likelihood of conversion.
  • Balanced: A mix of precision and reach, offering a good balance between targeting quality and audience size.
  • Broad: Targets a larger pool of users, with less emphasis on similarity but more reach.

Example Reach Type: If you select 2.5%, 5%, or 10%, this refers to the percentage of the population that will be targeted based on how closely they match your seed audience.

Step 4: Apply the Lookalike Segment to Your Campaign/Ad Group

After creating your lookalike segment, the next step is to apply it to an existing campaign or ad group. Lookalike segments are best used in Demand Gen campaigns or other campaigns focused on acquiring new customers.

• Select Campaign Type: When setting up your campaign, choose a Demand Gen campaign or another type where reaching new, similar users is a priority.
• Apply Audience: In your campaign settings, navigate to the audiences section and select the lookalike segment you’ve just created. You can apply it to individual ad groups or the entire campaign.

Step 5: Timing & Readiness

After applying your lookalike segment, it’s important to be aware of the timing and refresh rate for the segment to be fully optimized.

• Refresh Time: Lookalike segments may take 1-2 days to refresh and optimize. During this time, Google Ads will analyze new data and continuously update the segment to ensure it remains accurate.
• Optimal Performance: You may start seeing initial results sooner, but expect the segment to perform optimally after a few days of data processing.

Optimising and Scaling Lookalike Segments

Once you’ve set up your lookalike segments in Google Ads, it’s essential to optimize and scale them effectively to maximize performance. Here are key strategies and best practices to ensure your lookalike audience delivers the best results.

Monitoring Performance

To ensure your lookalike segments are working as intended, you’ll need to monitor the performance of your campaigns continuously. Key metrics to track include:

• Impressions: Measure how often your ad is shown to users in the lookalike segment.
• Clicks: Track how many users from the lookalike audience engage with your ads.
• Conversions: The most important metric, as it indicates how many of these users actually take the desired action (purchase, sign-up, etc.).
• Cost per Acquisition (CPA): Measure the cost to acquire each new customer. Optimizing for CPA ensures you’re getting the best value for your spend.

You can view and analyze these metrics using ad_group_audience_view or campaign_audience_view in Google Ads, which provide detailed insights into how well your lookalike segments are performing.

Experimenting with Reach Slider

Google Ads allows you to adjust the reach of your lookalike segments using a reach slider that controls how closely the audience will resemble your seed list. You have three main options:

• Narrow: This option focuses on the most similar users to your seed list. It offers a highly targeted group, which typically results in higher conversions but at a smaller audience size.
• Balanced: This is a middle ground between reach and precision. It expands your audience size slightly while still maintaining a good level of targeting accuracy.
• Broad: A broader audience allows you to reach a larger group of users. While it can deliver more impressions, the conversion rate may be lower, as the targeting becomes less specific.

By experimenting with these settings, you can find the right balance between reaching a larger audience and maintaining a high conversion rate. It’s important to test each option and measure which gives the best return on investment (ROI).

Combining Seeds

Another strategy for optimizing your lookalike segments is combining multiple seed lists. Instead of relying on a single seed audience (e.g., past customers), you can:

• Use multiple seed audiences, such as recent purchasers, high-engagement users, and website visitors. This allows Google Ads to create a lookalike audience that combines characteristics from different groups, increasing the likelihood of finding new, valuable customers.
• Testing different seed lists: Evaluate which combination performs best in terms of conversion rates, cost per acquisition, and other KPIs.

Combining seeds helps you segment your audience more effectively, ensuring a better match between your lookalike audience and your desired customer base.

Exclusions

To further optimize your campaigns, it’s crucial to exclude low-value segments or existing customers from your lookalike targeting. Here’s how to do it:

• Exclude Existing Customers: If you already have a customer list, ensure that you exclude these users from your lookalike segment to avoid wasting ad spend.
• Exclude Low-Value Segments: Use negative audiences to exclude users who are unlikely to convert. For example, you can exclude people who engaged with your content but did not complete a conversion event.

By excluding these users, you ensure that your budget is spent on acquiring fresh, high-potential prospects.

Testing Different Campaign Types/Creative

Once your lookalike segments are live, it’s important to test various campaign types and ad creatives to complement your audience targeting:

• Campaign Types: Experiment with different campaign types (e.g., Demand Gen, Video Ads, or Display Ads) to find which one performs best for your lookalike audience. Different formats may resonate better with your targeted segment, so try varying your approach.
• Creative Variations: Test different ad creatives (e.g., videos, carousel ads, or static banners) to see which content drives the highest engagement and conversion rates. Even within lookalike segments, user preferences can vary, so tailoring the creative for different demographics is key.

Always be ready to iterate based on performance to find the best combination of campaign type and creative.

Refreshing Seed Lists

Your seed audience data needs to stay current for your lookalike segments to remain effective. Regularly refresh your seed lists by:

• Adding new high-value customers to your seed list to ensure your lookalike audience reflects your most recent users.
• Removing any inactive or outdated users who no longer align with your current customer base.

By maintaining up-to-date seed lists, you ensure that your lookalike segments continue to target relevant users who are likely to convert, keeping your campaigns effective and efficient.

Advanced Optimisation

For advanced campaign management, consider using the following tactics to further optimise your lookalike segments:

• Layering Bids: Adjust your bidding strategy to match the value of users in your lookalike segment. For example, you might increase bids for more similar users (those who more closely resemble your seed audience) and decrease bids for broader users.
• Smart Bidding: Utilize Smart Bidding strategies like Target CPA or Maximise Conversions. These automated bidding strategies use Google’s machine learning to adjust bids in real-time, helping you achieve the best possible results within your set goals.
• Adjusting for Device, Time, and Geography: Fine-tune your campaigns by setting bid adjustments for mobile, time of day, or geographic location. For example, if you know that your audience converts better on mobile devices during evenings, adjust your bidding strategy accordingly.

These advanced tactics allow you to scale your campaigns with greater precision, ensuring that you’re always optimizing for the best performance.

Common Mistakes & How to Avoid Them

While lookalike segments in Google Ads are a powerful tool for scaling and targeting new audiences, there are common pitfalls that can lead to ineffective campaigns or wasted ad spend. Here’s a rundown of these mistakes and how you can avoid them to maximize the performance of your lookalike segments.

1. Using Small or Low-Quality Seed Lists (Lack of Data = Weak Results)

Mistake: Using seed audiences that are too small or of low quality can result in weak lookalike segments. With limited data, Google’s machine learning cannot accurately find high-converting users who resemble your existing customers.

How to Avoid It:

• Ensure you have at least 100 matched users in your seed audience for optimal performance. 
• Use high-value, recent customers for the best results. The more relevant and engaged your seed list, the better the lookalike audience will be.
• Regularly clean and update your seed lists to keep them fresh and relevant.

2. Applying Lookalike Segments to Unsupported Campaign Types

Mistake: Lookalike segments are supported only in certain Google Ads campaign types, such as Demand Gen campaigns. Applying lookalike audiences to unsupported campaign types, like Search, can result in ineffective targeting and wasted budget.

How to Avoid It:

• Ensure your campaign type supports lookalike segments. As of now, lookalike segments work best for Demand Gen, Display, and Video campaigns.
• If you’re running a Search campaign, use Customer Match or Remarketing Lists for Search Ads (RLSA) instead, as lookalike audiences are not supported in that context.

3. Failing to Exclude Existing Audiences, Causing Overlap and Inefficiencies

Mistake: When you don’t exclude existing customers or low-value users from your lookalike targeting, your audience becomes overlapping, leading to inefficiencies and wasted spend.

How to Avoid It:

• Always exclude current customers from your lookalike audience. This ensures that you’re not targeting people who have already converted or are likely already aware of your product.
• Use negative audiences to remove people who fall into low-conversion groups, ensuring that your budget is spent on high-potential users.

4. Overly Broad Targeting (Choosing “Broad” Reach Prematurely Without Testing)

Mistake: Selecting the “Broad” reach setting on the lookalike segment slider without sufficient testing can result in targeting a huge audience that may not be relevant or likely to convert. This may lead to low conversion rates and high costs.

How to Avoid It:

• Start with a Narrow or Balanced reach type and test performance before expanding to Broader settings.
• Carefully monitor the performance of your campaigns, and only increase the reach once you’ve tested and optimized for smaller, more specific audiences.
• Test, measure, and scale: Testing is key when it comes to reach. Be sure to experiment with different segment sizes to find the best balance between targeting precision and audience size.

5. Not Monitoring or Cleaning Seed Data, Causing Stale or Irrelevant Segments

Mistake: If your seed audience is not regularly updated or cleaned, it may include users who are no longer relevant or engaged. This can lead to the creation of stale or irrelevant lookalike segments, which negatively impacts campaign performance.

How to Avoid It:

• Keep your seed lists fresh by adding recent, high-value users and removing outdated ones. Regularly review and clean your data.
• Ensure your customer data complies with privacy standards and is up-to-date for optimal match rates.
• Use dynamic remarketing or app user lists to refresh seed data automatically for continued relevance.

6. Ignoring Conversion Attribution and Measuring Only Top-of-Funnel Metrics

Mistake: Focusing solely on top-of-funnel metrics, such as impressions and clicks, can give you a false sense of success. While these are important, they don’t reflect true campaign performance unless tied to conversions.

How to Avoid It:

• Track conversion-based metrics such as Cost Per Acquisition (CPA), conversion rate, and Return on Ad Spend (ROAS) to better understand the performance of your lookalike segments.
• Set up conversion tracking and utilize Smart Bidding strategies to optimize towards meaningful actions. 
• Regularly review the full customer journey from ad impression to conversion to ensure that your lookalike segments are driving valuable results, not just clicks.

By avoiding these common mistakes, you can ensure that your lookalike segments are set up for success, maximizing the ROI of your campaigns while effectively scaling your customer acquisition efforts. Always be testing, optimizing, and refining to achieve the best results possible.

Case Studies & Example Scenarios

Example 1: E-commerce Store Using Lookalike Audience of Past 30-Day Purchasers to Scale

Scenario:

An e-commerce store specializing in fashion apparel wants to expand its reach and scale its customer acquisition efforts. The business has an established base of recent purchasers (within the past 30 days) who frequently buy from the store.

Solution:

• The e-commerce store uses a lookalike audience created from the past 30-day purchasers (i.e., their seed audience) to target new customers who resemble these high-value, recent buyers. The campaign is set up as a Demand Gen campaign, targeting users who share behaviors and characteristics with the seed audience, including purchase frequency and interaction with the website.

Performance Improvements:

• Improved Conversion Rate: The e-commerce store experiences a 15% improvement in conversion rates. The new customers acquired via the lookalike audience are more likely to make purchases because they share similar traits to recent buyers.
• Reduced CPA: With highly targeted lookalike segments, the business sees a 20% reduction in Cost Per Acquisition (CPA). By reaching users who are more likely to convert, the store spends less on acquiring each customer.

Example 2: B2B Service Using Lookalike Audience of High-Value Leads to Expand Into New Geography

Scenario:

A B2B service provider offering marketing automation software is looking to expand its reach into new geographical markets. The company has a list of high-value leads in its home market who have shown strong engagement, including demo requests and trial sign-ups.

Solution:

• The B2B provider creates a lookalike audience based on its high-value leads (users who have interacted deeply with the brand) and targets a new geography—the Southeast Asian market. The campaign is set up as a Display Network campaign with targeting tailored to industry-specific interests. Additionally, the company uses a smart bidding strategy to optimize for conversions (demo sign-ups).

Performance Improvements:

Improved Conversion Rate: The B2B service experiences a 30% higher conversion rate compared to traditional prospecting efforts in the new geography. Lookalike segments help the company reach users with behaviors similar to high-converting leads.

Reduced CPA: The use of lookalike audiences in a new market results in a 25% decrease in CPA, as the ads are shown to a more qualified audience who is more likely to engage with the offer.

Key Learnings:

• Importance of Seed List Quality: The service provider used a seed list of highly engaged leads (those who interacted with the demo and trial features), ensuring that the lookalike audience had a higher likelihood of success.
• Creative Relevance: The creatives were tailored to the new geography, incorporating region-specific value propositions (e.g., localized case studies) that resonated with the target audience.
• Iterative Testing: The team experimented with different bidding strategies (Manual CPC vs. Smart Bidding) and adjusted targeting based on region-specific data, optimizing for the highest-performing segments.

Technical & API Considerations (for Advanced Users)

For advanced users and developers, leveraging the Google Ads API to manage lookalike audiences can offer greater flexibility, automation, and control. Here’s an overview of how the API can be used to work with lookalike segments, along with some automation tips and code examples.

Overview of Google Ads API Support for Lookalike User Lists

The Google Ads API allows advanced users to create, manage, and monitor lookalike audiences programmatically. Through the API, you can interact with lookalike segments just like you would within the Google Ads interface, but with the added benefit of automation and integration into your systems.

Using the API, you can:

• Create and manage seed audiences for lookalike segments.
• Create LookalikeUserListInfo objects for defining lookalike segments.
• Set targeting parameters such as expansion level and geography programmatically.
• Monitor audience performance and track metrics directly through the API.

For further details on the API and its capabilities, refer to the Google Ads API documentation

 for audience segments and lookalike lists.

Code Example: Creating a LookalikeUserListInfo Object

The following is a simple example of how to create a LookalikeUserListInfo object using the Google Ads API. This object specifies the parameters for a lookalike segment based on your seed audience.

from google.ads.google_ads.client import GoogleAdsClient

def create_lookalike_user_list(client, customer_id, seed_user_list_ids, expansion_level, country_codes):

    # Initialize the Google Ads client

    ga_service = client.get_service(“GoogleAdsService”)

    user_list_service = client.get_service(“UserListService”)

    # Define Lookalike User List

    user_list = client.get_type(“UserList”)

    user_list.name = “Lookalike Audience for Seed List”

    user_list.description = “Lookalike audience based on past purchasers”

    # Create Lookalike User List Info

    lookalike_user_list_info = user_list.rule_based_user_list.lookalike_user_list_info

    lookalike_user_list_info.seed_user_list_ids.extend(seed_user_list_ids)  # List of seed audience IDs

    lookalike_user_list_info.expansion_level = expansion_level  # Narrow, Balanced, Broad

    lookalike_user_list_info.country_codes.extend(country_codes)  # e.g., [“US”, “CA”]

    # Create the user list operation

    user_list_operation = client.get_type(“UserListOperation”)

    user_list_operation.create.CopyFrom(user_list)

    # Add the user list via the API

    response = user_list_service.mutate_user_lists(customer_id=customer_id, operations=[user_list_operation])

    return response

# Example usage:

client = GoogleAdsClient.load_from_storage(“google-ads.yaml”)

customer_id = “INSERT_CUSTOMER_ID_HERE”

seed_user_list_ids = [123456789, 987654321]  # Example seed list IDs

expansion_level = “BROAD”  # Can be “NARROW”, “BALANCED”, or “BROAD”

country_codes = [“US”, “CA”]

response = create_lookalike_user_list(client, customer_id, seed_user_list_ids, expansion_level, country_codes)

print(f”Created Lookalike Audience with ID: {response.results[0].resource_name}”)

In this example, you:

• Set up a LookalikeUserListInfo object using the seed_user_list_ids (IDs of existing seed audiences).
• Specify the expansion_level (Narrow, Balanced, Broad) to define how close the lookalike audience should be to the seed list.
• Define country_codes to target specific geographic regions.

Monitoring via API: Query Audience Views for Metrics

Once you’ve created a lookalike audience, you can monitor its performance via the API. This allows you to query key metrics such as impressions, clicks, and conversions. The AudienceView object in the Google Ads API provides a way to access these metrics.

def get_audience_metrics(client, customer_id, lookalike_audience_id):

    # Initialize the Google Ads API service

    ga_service = client.get_service(“GoogleAdsService”)

    # Query the audience view metrics

    query = f”””

    SELECT

        campaign.id,

        ad_group.id,

        ad_group_criterion.criterion_id,

        metrics.impressions,

        metrics.clicks,

        metrics.conversions,

        metrics.average_cpc,

        metrics.cost_micros

    FROM

        audience_view

    WHERE

        audience_view.resource_name = ‘customers/{customer_id}/audienceViews/{lookalike_audience_id}’

    “””

    # Run the query

    response = ga_service.search_stream(customer_id=customer_id, query=query)

    # Process the response and print results

    for batch in response:

        for row in batch.results:

            print(f”Campaign ID: {row.campaign.id}”)

            print(f”Impressions: {row.metrics.impressions}”)

            print(f”Clicks: {row.metrics.clicks}”)

            print(f”Conversions: {row.metrics.conversions}”)

            print(f”Average CPC: {row.metrics.average_cpc.micros / 1e6}”)

            print(f”Cost: {row.metrics.cost_micros / 1e6}”)

# Example usage:

get_audience_metrics(client, customer_id=”INSERT_CUSTOMER_ID_HERE”, lookalike_audience_id=”INSERT_AUDIENCE_ID_HERE”)

This query retrieves detailed metrics from the AudienceView for the lookalike audience, helping you track performance on key KPIs like impressions, clicks, conversions, average CPC, and cost.

Automation Tips: Programmatically Refresh Seed Lists & Monitor Size Thresholds

Automation can significantly improve the efficiency of managing lookalike audiences. Here are some tips for automating tasks using the API:

• Programmatically Refresh Seed Lists: Regularly refresh your seed lists by adding new high-value customers and removing outdated users. Use scheduled jobs or triggers to ensure your seed list is up-to-date.
• Monitor Audience Size Thresholds: You can automate the process of checking if your seed list exceeds the minimum threshold of 100 matched users. If your seed audience grows too small or becomes ineligible, you can programmatically adjust or exclude certain users to maintain effective targeting.

def monitor_seed_list(client, customer_id, seed_user_list_id):

    # Fetch the seed user list details

    user_list_service = client.get_service(“UserListService”)

    user_list_resource_name = f”customers/{customer_id}/userLists/{seed_user_list_id}”

    # Get the seed list information

    user_list = user_list_service.get_user_list(resource_name=user_list_resource_name)

    # Check the size of the seed list

    if user_list.size < 100:

        print(“Seed list size is too small. Consider adding more users.”)

    else:

        print(f”Seed list has {user_list.size} users, ready for use.”)

Handling “Ineligible” States: If a seed list becomes ineligible (e.g., due to data issues or privacy violations), you can automate alerts or take action to resolve the issue by either updating the list or selecting a new one for the lookalike segment.

Frequently Asked Questions (FAQs)

1. What minimum seed size is required for lookalike segments?

Google requires at least 100 matched users in your seed audience to generate a lookalike segment. Larger, high-quality seed lists generally produce better-performing lookalikes because Google’s machine learning has more data to model from.

2. Can lookalike segments be used in Search campaigns?

No. Lookalike segments cannot be used in Search campaigns. They are currently supported only for specific campaign types such as Demand Gen, Display, and Video.

For Search, rely on Customer Match, RLSA, or keywords to refine your targeting.

3. How soon after creating a lookalike segment can I expect results?

Lookalike segments typically take 1–2 days to refresh and populate after creation. While ads may start serving sooner, optimal performance usually stabilizes once Google completes its refresh and begins optimizing based on early engagement signals.

4. My lookalike segment says “Ineligible” – why?

A lookalike segment becomes Ineligible for several reasons:

• The seed audience has fewer than 100 matched users.
• Privacy or data policy violations.
• The seed list is too new and has not been processed yet.
• The selected location has insufficient eligible users to model from.
• Updating or replacing your seed list usually resolves the issue.

5. Should I use narrow or broad reach for lookalike?

It depends on your goal and budget:

• Narrow: Best for maximizing conversion efficiency; closely resembles your seed audience.
• Balanced: Safe default for most advertisers; good mix of reach and precision.
• Broad: Use only after testing narrower options; ideal for scaling and upper-funnel expansion.

Start narrow, test performance, then gradually expand reach to avoid overspending on low-quality users.

Conclusion

Lookalike segments in Google Ads offer a practical and scalable way to reach new users who behave like your highest-value customers. When built on strong seed audiences and paired with thoughtful optimisation, they can significantly improve acquisition efficiency, lower CPA, and unlock new growth opportunities across Demand Gen, Display, and Video campaigns.

The key is to treat lookalikes as a strategic layer, not a set-and-forget tool. Keeping your seed lists fresh, testing different reach levels, refining creative, and monitoring performance ensure that your lookalike targeting stays relevant and cost-efficient. With the right structure, lookalike segments become a dependable engine for expanding beyond remarketing and sustaining long-term pipeline growth.

If you want expert support building high-performing customer acquisition systems, explore:

• Google Ads services
• Google Remarketing services

These services can help you implement advanced audience strategies, strengthen campaign performance, and scale results with confidence.