Understanding Customer Match Lists to Enhance Audience Targeting

Poor audience targeting and wasted ad spend are common problems for e-commerce merchants. Many ad campaigns fail to target the right audience, leading to low conversion rates and a lack of return on investment (ROI). Traditional advertising methods depend on guesswork, making it difficult for relevant engagement with potential customers.

Let’s talk about a solution.

What is a Customer Match?

Through Customer Match, advertisers can find new, similar customers throughout the advertising network and re-engage past ones using their own customer data from their online store. 

For the advertising platforms to match their profiles, advertisers simply need to upload a list of the contact details of their customers or prospects, such as phone numbers or email addresses, etc… This data is safely matched with user accounts to create custom audiences for ad campaigns across various advertising platforms. 

Through this blog, we’ll cover the importance of using customer match lists for better audience targeting and optimising your ad performance. Further, we’ll also understand how it works and the best practices to be followed. Let’s get started.

First-party Data’s Significance

The data used here is first-party data, which means the customers have agreed to share their information with you. Further, to comply with local laws like the CCPA or GDPR, ensure that everyone on the list has granted you permission to use their data.

The data can be useful because it’s accurate, complies with privacy regulations, helps with precise targeting, builds similar audiences, and improves campaign performance.

Key ways Customer Match Lists empowers advertisers

Using customer match lists for your advertising platforms gives advertisers several significant benefits. These advantages include:

1. Precise Targeting 

Advertisers can target users using their own first-party data. This includes phone numbers, addresses, and email IDs, which create a highly relevant audience. By using data from past customer interactions, advertisers can target people who are most likely interested. It eliminates guesswork, unlike traditional methods.

2. Increased Conversion Rate

Targeting people who are already familiar with a brand or are similar to your current customer base could lead to higher conversion rates than cold audiences. Merchants usually notice a rise in conversion rates when they customise advertisements for both lookalike audiences and current customers.

3. Optimised Advertising Spend 

By focusing on more relevant audiences, advertisers can boost their return on investment (ROI) and reduce wasted ad spend on irrelevant users. It helps to focus advertising efforts on people who have already shown interest or who have already converted into buyers.

4. Personalised Ad Delivery

Based on the data they upload, advertisers may customise their strategy to specific audience segments. As a result, the advertisements become more impactful and relevant. Customised ads can improve brand visibility and build closer relationships with the audience.

5. Cross-Device Targeting

Unlike cookie-based remarketing, Customer Match can remember users across different devices and web browsers, provided, they can be identified by the uploaded contact information, leading to more consistent reach.

6. Customer Retention and Loyalty

In addition to promoting new products or discounts, advertisers can re-engage with their previous customers and strengthen their bonds with current customers. Custom Audiences make it easier to connect with previous customers and prospects, encouraging repeat purchases.

7. Prospecting for New Customers

Advertising platforms such as Facebook and Microsoft can use the insights collected from existing customer lists to find and target users who share similar characteristics. Advertisers can use these Similar Audiences across various properties. 

How Customer Match Works

Uploading Customer Data: The process begins with uploading customer data files to the advertising platform. These files generally include identifiers like email addresses or phone numbers, formatted according to platform guidelines. Accurate and properly formatted data ensures higher match rates.

Data Matching and Privacy: When the data is uploaded, the platform hashes it for privacy and security before matching it with relevant user profiles. It ensures that sensitive information is protected, adhering to the privacy regulations like GDPR and CCPA. Only matched users are added to the advertiser’s custom audience list.

The dont’s while using a Customer Match List

There are several not-so-good practices to avoid to ensure effectiveness and a positive user experience. Here are the top things e-commerce merchants should NOT do when using Customer Match:

1. Not ideal for new advertisers

If you’re just launching, you likely don’t have a sizable email/phone list to match. Even if you upload a small list, it may not match enough users for effective targeting. As a new advertiser, focus on broader, intent-based strategies first.

2. Do not use outdated or low-quality data

Invalid emails/phone numbers lead to low match rates, wasting ad spend. Instead, regularly clean your lists (remove inactive/bounced emails) and prioritise recent purchasers (last 6-12 months).

3. Do not ignore audience segmentation

Sending the same ad to all customers (e.g., first-time buyers vs. loyal customers) is irrelevant. You may use segmented lists, which can be easily created by our app. 

4. Do not overlap customer match

Ensure not to overlap customer match with other audiences. This could lead to accidentally double-serving ads. You can use exclusion lists to avoid overlap. Ex: Exclude recent purchasers from prospecting campaigns.

5. Do not forget to test and optimise

Customer Match needs refinement. Make sure to A/B test creatives for different segments. 

6. Do not ignore post-campaign analysis

Make sure not to miss insights on what worked. Ex: which lists led to maximum ROI. It would be useful to track conversions by audience segments and then set bids accordingly.

Do you know you can automate it?

Instead of manually uploading and updating the customer match audiences, there’s a way you can automate this process. That’s right. With the Simprosys Customer Match Lists app, which works on the API method, you can automate the syncing of customer lists from the Shopify & Shopline store to Google Ads, Meta Ads, & Microsoft Advertising. It helps efficiently control your present customer targeting and optimise your ad spends. This time-saving app enables precise targeting & exclusion to optimise targetting & re-engage shoppers.

Why Simprosys Customer Match Lists?

Our Final Word

Customer Match is a game-changer for e-commerce merchants looking to make their advertising more personalised, effective, and data-driven. Whether you’re looking to re-engage existing customers, find new ones, or optimise your ad spend, it offers a versatile solution to achieve your marketing goals.

Overall, it empowers advertisers to go beyond broad targeting and engage with specific audiences across the advertising networks, which leads to more effective campaigns and better outcomes.

Start exploring the power of Customer Match today, and unlock new opportunities for smarter advertising!

FAQs: Quick Answers for You

What is the minimum audience size for a Customer Match list?
Google: A list must have at least 100 members added or updated within the last 540 days to stay eligible.

Microsoft: The list should have at least 300 active email users for targeting across the Microsoft Advertising Network.

Meta: The list should include at least 100 customers.

What’s the difference between Customer Match Lists and Remarketing Lists?

The key difference is the targeting method and data source. 

Customer Match uses your own customer data (like emails or phone numbers). Remarketing Lists target users based on website cookies, app user IDs, or Signals. Customer Match uses first-party data, whereas remarketing relies on tracking user behavior. 

Can I use Customer Match lists to exclude audiences?

Yes, one straightforward use case is excluding your customer match audience from campaigns that need to reach new customers, particularly for Display or YouTube campaigns. This helps make your advertising more efficient by avoiding serving ads to people who have already purchased a product.

What are the customer match list requirements?

Customer Match Lists requirements vary depending on the ad platform on which you are using. The requirements are different for Google, Meta, and Microsoft Advertising.

If you have further questions related to Customer Match Lists or regarding our app, please feel free to drop them in the comments below.