FAQ: Using Customer Lists for Advanced Ad Targeting
Using your first-party customer and prospect data is a powerful way to enhance digital advertising effectiveness. By uploading curated lists from your CRM directly into platforms like Google Ads and LinkedIn, you can run highly specific campaigns to target high-value accounts, re-engage prospects who are stuck in the sales funnel, and improve overall efficiency by excluding current customers from acquisition campaigns. This approach moves beyond broad, cookie-based targeting to focus your budget on the users who matter most to your business, creating more relevant and impactful ad experiences.
How can we use our existing customer and prospect lists for ad targeting?
You can use your existing customer and prospect lists to create highly targeted advertising audiences on platforms like Google Ads and LinkedIn. This process, often called "Customer Match" on Google or "Matched Audiences" on LinkedIn, involves uploading a securely hashed list of customer contact information (such as email addresses or phone numbers) from your CRM. The ad platform then matches this data against its user base.
Once a match is found, you can:
- Target specific users directly: Serve tailored ads to your existing customers, promoting new products, upsells, or loyalty programs.
- Re-engage prospects: Create lists of leads who have shown interest but haven't converted and target them with specific messaging to guide them through the funnel.
- Exclude existing customers: Create suppression lists to prevent your current customers from seeing ads meant for new prospects, which improves ad spend efficiency.
- Find new customers: Use your uploaded lists as a foundation to create "similar" or "lookalike" audiences, allowing platforms to find new users who share characteristics with your best customers.
This strategy is central to account-based marketing (ABM), where you can upload a list of target companies and their key decision-makers to focus your advertising efforts precisely.
What is a 'Customer Match' list in Google Ads?
A 'Customer Match' list is a powerful audience targeting feature in Google Ads that allows you to use your own first-party data to reach specific users. You upload a list of customer information, such as email addresses, phone numbers, and mailing addresses, that you have collected directly from your users. Google takes this information, hashes it for security, and matches it against its own database of Google accounts.
Once the list is processed and a sufficient number of matches are found, you can use this audience segment for several strategic purposes:
- Targeting: Show personalized ads to this specific group of high-value users as they use Google Search, YouTube, Gmail, and the Google Display Network.
- Observation: Add the list to a campaign in "Observation" mode. This allows you to monitor the performance of this specific audience without restricting your campaign's reach, and you can apply bid adjustments if you see they perform better.
- Exclusion: Exclude this list from campaigns, which is particularly useful for preventing existing customers from seeing ads designed for new customer acquisition.
Customer Match helps you re-engage with known customers or prospects and serves as a crucial signal for Smart Bidding strategies, helping Google's AI better understand the characteristics of your ideal customer. This makes it a cornerstone feature for moving from broad targeting to a more precise, data-driven advertising approach.
What are the privacy requirements for uploading customer data to Google or LinkedIn?
Key Privacy Obligations
Both Google and LinkedIn have strict privacy requirements to protect users. Before uploading any customer data, you must ensure you comply with their policies and all applicable laws like GDPR or CCPA.
The fundamental requirements include:
- First-Party Data Only: You can only upload information that was shared directly with you by the customer (first-party data). This includes data collected from your website, app, or physical stores. Purchasing or renting email lists is prohibited.
- User Consent: You must have obtained proper consent from individuals to share their information with third parties for advertising purposes. This is especially critical in regions governed by regulations like GDPR, which require explicit, informed consent.
- Privacy Policy Disclosure: Your company's privacy policy must clearly state that you share customer information with third parties to perform advertising services on your behalf. It should also explain how users can opt-out of this data usage.
Data Handling and Security
To ensure security, the platforms do not receive your raw data. When you upload a list, the contact information (like email addresses) is converted into hashed codes using a secure, one-way algorithm like SHA256. The platform then matches these hashed codes against its own hashed user data. This process ensures that the raw personal information is not directly exposed. The data you upload is used only for creating your audience and ensuring policy compliance; it is not used to build profiles of your customers or shared with other advertisers.
Can we create an audience based on high-scoring leads from our CRM?
Yes, creating an audience based on high-scoring leads from your CRM is a highly effective and recommended strategy. This allows you to focus your advertising budget on prospects who have already demonstrated a strong level of interest or fit, making them more likely to convert.
The process typically involves these steps:
- Segment in your CRM: First, you create a dynamic or static list within your CRM (e.g., HubSpot, Salesforce) that isolates leads based on their lead score or other key attributes that define them as "high-scoring" or "sales-qualified."
- Export and Format: Export this list, ensuring it contains contact information like email addresses or phone numbers. The data should be formatted according to the ad platform's template.
- Upload to Ad Platforms: Upload this as a "Customer Match" list on Google Ads or a "Matched Audience" on LinkedIn. For security, the data is hashed before being matched against the platform's users.
- Automate for Freshness: For maximum effectiveness, it's best to automate this process. You can use platform integrations or tools like Zapier to automatically sync new high-scoring leads from your CRM to your ad audiences. This ensures the list is always up-to-date, adding new prospects as they qualify and removing those who have already converted.
This approach is perfect for nurturing campaigns. For example, you can target these high-value prospects with specific content, case studies, or demo offers designed to move them from the consideration phase to a final decision.
What's the difference between a Customer Match list and a remarketing list?
While both Customer Match and remarketing lists are used to target users who have previously interacted with your brand, they are fundamentally different in how they are created and who they can reach.
Remarketing Lists
A standard remarketing list (or retargeting list) is based on user behavior tracked via a pixel or tag installed on your website or app. This is primarily cookie-based targeting.
- How it works: When a user visits your site, a cookie is placed on their browser. You can then show ads to this user as they browse other sites within an ad network.
- Data Source: Anonymous browser cookies or mobile device IDs. You don't know the user's actual identity.
- Limitation: It is device-specific and cookie-dependent. If a user clears their cookies or uses a different device, you can't reach them. This method is becoming less reliable with the deprecation of third-party cookies.
Customer Match Lists
A Customer Match list is based on personally identifiable information (PII) that you have collected directly from your customers (first-party data).
- How it works: You upload a list of contact information (e.g., email addresses, phone numbers) from your CRM. The ad platform hashes this data and matches it to its user accounts.
- Data Source: Your own first-party data. You are targeting known individuals, not anonymous browsers.
- Advantage: It is people-based, not device-based. As long as the user is logged into their Google or LinkedIn account, you can reach them across any device—desktop, mobile, or tablet. This makes it more persistent and powerful in a cookieless world.
In essence, remarketing targets anonymous users based on recent website actions, while Customer Match targets known individuals from your database, enabling more precise, cross-device engagement.
How do 'lookalike' or 'similar' audiences work, and how effective are they?
How They Work
Lookalike audiences (on platforms like LinkedIn and Meta) and similar audiences (on Google Ads) are powerful tools for new customer acquisition. They work by using an existing, high-quality audience you provide—known as a "seed" audience—as a model to find new people who share similar characteristics.
The process is driven by machine learning algorithms:
- You Provide a Source Audience: This must be a high-quality list, such as your best customers (a high LTV list), a Customer Match list of high-value leads, or website visitors who have all completed a key conversion (like a purchase).
- The Platform Analyzes the Source: The algorithm identifies thousands of common attributes among the users in your seed audience, including demographics, interests, online behaviors, and engagement patterns.
- It Finds New, Similar Users: The platform then scans its entire user base to find a new group of people who "look like" your source audience based on those shared traits.
- You Control the Size/Precision: You can control the size of the lookalike audience. A smaller audience (e.g., a 1% lookalike) will be more precise and closely match your source, while a larger audience (e.g., a 10% lookalike) will offer greater reach but with less precision.
What Determines Their Effectiveness?
The effectiveness of a lookalike audience is not guaranteed; it is a direct result of your inputs and strategy. Performance depends on three main factors:
- 1. Seed Audience Quality (The "Garbage In, Garbage Out" Principle)This is the most important factor. The algorithm is only as good as the data you provide. A lookalike audience built from a high-value, specific seed list (e.g., "customers with a high lifetime value") will perform significantly better than one built from a broad, low-intent list (e.g., "all website visitors" or "newsletter subscribers").
- 2. Seed Audience SizeYour seed list must be large enough for the platform to find statistically significant patterns. While platforms may have a technical minimum (often 100-300 matched users), a more robust seed audience of 1,000 to 5,000 high-quality users is often recommended for optimal modeling.
- 3. The Size vs. Precision Trade-offThis is your primary strategic lever for controlling performance.
- Small (e.g., 1%-3%): Selects users who most closely resemble your seed. This delivers a smaller, more precise audience, ideal for performance-focused goals like high-quality lead generation.
- Large (e.g., 5%-10%): Provides broader reach but less precision. This is better suited for top-of-funnel goals like brand awareness and new user acquisition.
Ultimately, effectiveness should be measured against your goal. A 1% lookalike should be benchmarked against other high-intent tactics, while a 10% lookalike should be benchmarked against broad, interest-based targeting.
Can we target specific accounts from our target account list on platforms like LinkedIn?
Yes, absolutely. Targeting a specific list of companies is a core feature of account-based marketing (ABM) on platforms like LinkedIn, and it's highly effective for B2B advertisers. LinkedIn's "Matched Audiences" feature allows you to do this through a capability called Account Targeting.
Here’s how you can target specific accounts:
- Prepare Your Account List: Create a CSV file containing the names of the companies you want to target. You can also include other identifiers like company websites to improve matching accuracy. LinkedIn allows you to upload a list of up to 300,000 companies.
- Upload the List to Campaign Manager: In LinkedIn's Campaign Manager, navigate to the audience creation section and choose to create an audience by uploading a list of accounts. LinkedIn will then process your file and match the company names to the LinkedIn Company Pages in its database. This matching process can take up to 48 hours.
- Layer Additional Targeting (Optional): Once your account list is matched and ready, you can use it as your primary targeting criteria. For even greater precision, you can layer on additional filters. For example, you can choose to only show ads to people who work at those specific companies AND have certain job titles (e.g., Director, VP), job functions (e.g., IT, Marketing), or levels of seniority.
This method ensures your ad budget is spent reaching decision-makers and influencers exclusively within your most valued target accounts, eliminating wasted spend on irrelevant companies.
What is the minimum audience size required to run a Customer Match campaign?
The minimum audience size requirements for Customer Match and Matched Audience campaigns vary by platform and are in place to protect user privacy and ensure a large enough pool for ad serving.
Google Ads
For Google Ads, the minimum requirement depends on the network where you intend to run your ads. Historically, the minimum was 1,000 active matched users for most campaign types. However, Google has made this more accessible:
- Search, Gmail, YouTube, and Display: The general requirement is to have a list with at least 1,000 active users that Google can match. An active user is someone who has been active on a Google property recently.
- Recent Update for Search: In a significant update, Google lowered the minimum for Customer Match lists used in Search campaigns to just 100 matched users. This makes the feature much more accessible for smaller businesses or those with niche B2B lists.
It's important to note that your uploaded list needs to be larger than the minimum, as not all contacts will successfully match to a Google user.
LinkedIn Matched Audiences
For LinkedIn, the minimum size for a Matched Audience (either a contact list or an account list) is 300 matched members. This means that after you upload your list of companies or contacts, at least 300 of them must successfully match with LinkedIn profiles for the audience to be usable in a campaign. While 300 is the technical minimum, for broader campaigns like Sponsored Content, LinkedIn often recommends larger audiences (e.g., 15,000 to 50,000) to ensure sufficient reach and delivery.
How can we use these audiences to re-engage high-profile prospects who haven't converted yet?
Using custom audiences to re-engage high-profile prospects who are stalled in the sales funnel is a highly effective mid-funnel marketing tactic. It allows you to deliver tailored messaging to a valuable audience that is already aware of your brand but needs an extra push to convert.
Here is a strategic approach:
- Identify and Segment Your Audience: Start by creating a specific list in your CRM of these high-profile prospects. This could be based on criteria such as high lead scores, engagement with key content (like pricing pages or webinars), or those who have been in the "consideration" or "evaluation" stage for a certain period without progressing.
- Upload the Segmented List: Upload this curated, hashed list to Google Ads (as a Customer Match audience) and LinkedIn (as a Matched Audience). This creates a specific targeting group composed only of these individuals.
- Develop Tailored Ad Creative and Messaging: Don't show them the same top-of-funnel ads they've already seen. Instead, create content that addresses potential barriers and reinforces your value proposition. Good examples include:
- Case Studies and Testimonials: Build trust by showing how similar companies have succeeded with your solution.
- Targeted Webinars or Demo Offers: Invite them to a live demo or a webinar that tackles a specific pain point relevant to their industry.
- Competitive Differentiators: Create ads that highlight what makes your solution unique compared to alternatives they may be considering.
- Run a Multi-Channel Campaign: Target this audience across multiple platforms. For example, reach them on LinkedIn where their professional mindset is active, and reinforce the message on YouTube or the Google Display Network. This consistent, multi-touch approach keeps your brand top-of-mind and guides them toward a decision.
This focused strategy helps nurture valuable relationships and can successfully reactivate promising leads that have gone cold.
Should we exclude our existing customers from our prospecting campaigns?
Yes, in almost all cases, you should absolutely exclude your existing customers from your top-of-funnel prospecting campaigns. This is a fundamental best practice for improving ad spend efficiency and delivering a better customer experience.
Why Exclusion is Critical
- Avoid Wasted Ad Spend: The primary goal of a prospecting campaign is to attract new leads and customers. Showing these introductory ads to people who have already purchased your product or service is a waste of your advertising budget. Every dollar spent on an existing customer is a dollar not spent on a potential new one.
- Improve User Experience: It can be irrelevant or even annoying for a loyal customer to be served ads with introductory offers or basic brand messaging. It suggests you don't recognize them as a customer. By excluding them, you ensure the ads they see (if any) are relevant to them, such as those for new features, upsells, or loyalty programs.
- More Accurate Campaign Metrics: By creating a clean separation between prospecting and customer marketing, you can more accurately measure the true performance of your new customer acquisition efforts. Your cost-per-acquisition (CPA) and return on ad spend (ROAS) metrics will be more meaningful.
How to Implement Exclusions
The process is straightforward. Maintain an up-to-date list of your current customers from your CRM. Upload this as a "suppression list" to Google Ads and LinkedIn and apply it as an exclusion to your prospecting campaigns. It's crucial to refresh this list regularly to ensure new customers are promptly removed from prospecting audiences.
How often should we refresh our uploaded customer lists?
Refreshing your uploaded customer lists frequently is crucial for maintaining targeting accuracy, campaign relevance, and overall performance. Stale lists can lead to wasted ad spend and poor user experiences. The ideal frequency depends on your business cycle and goals, but a general best practice is to refresh them constantly.
For Exclusion/Suppression Lists
Lists used to exclude existing customers from prospecting campaigns should be updated as frequently as possible, ideally in near real-time. When a prospect becomes a customer, they should be removed from acquisition-focused audiences immediately. This prevents them from seeing irrelevant ads and stops you from wasting money trying to acquire someone you've already won. A daily or weekly refresh is a good manual cadence, but the best approach is to set up an automated sync between your CRM and the ad platform.
For Targeting and Re-engagement Lists
For lists used to target specific segments (like high-scoring leads or stalled prospects), the frequency should align with how often that audience changes. For example:
- If you are targeting leads in a specific funnel stage, the list should be refreshed as soon as a lead moves into or out of that stage.
- For broader customer lists used for upsell campaigns, a weekly or bi-weekly refresh might be sufficient.
Google Ads recommends regular refreshes and notes that lists can have a maximum membership duration of 540 days, after which members become ineligible if not updated. Constant updates not only keep your audiences accurate but also provide fresh data to the platforms, which can improve match rates and overall campaign performance.
What kind of match rates can we expect when uploading our contact lists?
The match rate—the percentage of your uploaded contacts that an ad platform can successfully match to a user account—can vary significantly based on several factors. It is uncommon to achieve a 100% match rate.
A typical match rate range for Google Ads is generally between 30% and 60%. Some sources indicate that many advertisers see rates between 29% and 62%. From a practical standpoint, achieving a match rate of 40-50% is often considered a good starting point and a solid result.
For B2B advertisers using work emails, match rates on platforms like Google and Meta can sometimes be much lower, potentially in the 10-20% range, because people often use personal emails for their platform accounts.
Factors That Influence Match Rates:
- Data Quality: The accuracy and cleanliness of your data is the most important factor. Outdated or incorrect email addresses and phone numbers will fail to match.
- Amount of Information Provided: You can significantly increase your match rate by providing multiple data points for each contact. For example, advertisers who upload two identifiers (like email and phone number) see an average list size increase of 28%, and with three identifiers, that increases to 35%.
- Data Hashing: Incorrectly formatting or hashing your data before upload can lead to errors and a lower match rate.
- Platform User Base: The match rate is ultimately limited by whether your customers have an account on the platform using the contact information you have for them.
Google Ads now provides an estimated match rate immediately after you upload a list, which helps you quickly identify any potential issues with your data file.
Can we use Customer Match to target users across different Google properties like YouTube and Display?
Yes, one of the primary strengths of Google's Customer Match is its ability to reach your targeted audience across Google's vast ecosystem of properties. When you upload a customer list and it's matched to Google users, you are not limited to just one channel.
You can use your Customer Match audiences for campaigns on:
- Google Search: You can tailor your bids for users on your list when they search for your keywords, or exclusively target them with specific ads.
- YouTube: Target your audience with video ads. This is highly effective for re-engagement, telling a brand story, or finding new users by creating similar audiences based on your most valuable customers.
- Gmail: Reach users with personalized ads that appear at the top of their inbox tabs, a direct way to get in front of a known audience.
- Google Display Network: Show visual ads to your customer list as they browse millions of websites and apps that are part of the Display Network.
- Google Shopping: Optimize your Shopping campaigns by adjusting bids for users on your Customer Match lists, as they are likely higher-intent shoppers.
This cross-property capability allows you to create a cohesive and persistent advertising strategy, engaging your customers and prospects wherever they are active within the Google universe. Campaigns using Smart Bidding can even automatically leverage your Customer Match lists to optimize performance and find users most likely to convert.
