How to Use First-party Audiences on Facebook and Google

Are you getting started with first-party audiences? If you’re just starting to experiment, the best place to start is your Facebook and Google campaigns. Using your own audiences can be less expensive and convert more customers than Facebook or Google’s broader targeting. And you’ll begin to collect first-party data on multichannel customer journeys as your customers interact with your ads.

**This article assumes that you already have a unified first-party data infrastructure in place. This means you are collecting first-party customer data from the relevant sources available to you (your website, app, CRM, etc). And you have it integrated to make unified customer profiles. It also assumes that your first-party audience solution integrates with Facebook and Google. Otherwise activating these audiences would be a real pain. To read about how to collect first-party data, read this article.**

Here’s how to start implementing first-party audiences into your campaigns to maximize impact on your funnel.

Prospecting/New Customer Acquisition – Segment your seed lists for high-quality lookalikes

For reaching new customers, you may initially find it practical to use interest or demographic targeting. But once you have enough data, start using lookalike models to reach a more precise audience. Facebook’s minimum audience size for lookalikes is only 100. And it’s the same for Google. And the quality of the lookalike audience increases with the size of the source audience.

But don’t use your entire customer base as the source audience. Here are some ways to segment your customers to ensure high-quality customer acquisitions.

RFM Segments: Using RFM modeling, isolate those of your customers who have spent the most money on your products. Or those who have been the most loyal to your brand.

Product Category Segments: Segment customers according to their product categories so you can customize your messages.

<Related content: How to use First-Party Customer Data for Prospecting>


Conversion Optimization – Segment by likelihood to purchase

Once you’ve attracted new visitors through your lookalike audiences, you can start nurturing them into customers with tailored retargeting campaigns.

It’s easy to pass all your visitor data through a pixel and let Facebook and Google do the rest. Each platform has its own algorithm for optimizing those audiences, using the data they have on each of the people in that audience.

However, you get better results using audiences that are pre-segmented based on first-party intelligence. Facebook and Google don’t have your global customer purchase history or a record of your specific patterns of site browsing behavior. A sophisticated first-party audience solution can use your historical data to do its own optimization. It can analyze your most recent visitors browsing behavior and predict which ones are most likely to make a purchase.

The result is a hyper-focused segment that will draw more conversions for lower costs than anything Facebook or Google could give you. And you can break the segment down further into product categories for tailored messaging.

<Related Content: How to Calculate Cost Per Acquisition through Multiple Campaigns>

Retention – Segment by RFM scores and next purchase predictions

Retention is a many-layered endeavor. Whether you’re nurturing a second purchase or a tenth it all falls under the same umbrella. Even though your messaging to one customer might be very different from the other.

A great way to stratify your customers is to use RFM modeling (You can brush up on RFM modeling here). RFM models allow you to segment your customers by how recently they purchased, how frequently they make purchases, and how much money they spent. You might also add a fourth variable to your segments – longevity – to account for how long a customer has remained loyal to your brand.

When you have an audience solution with predictive capabilities and access to historical data, you can also generate segments of customers who are most likely to be in-market for their next purchase. This is a great feature because it lets you be relevant to your customer’s needs rather than trying to be constantly on their radar.

It’s not dependent on the longevity of the customer’s cookie. You can connect your predictive audience to Google and Facebook the same way you would connect a custom audience. And this audience will remain dynamic so you don’t have to export and re-upload a new list every day.

<Related Content: Reduce Churn Using Next Purchase Predictions>

Using these two audience strategies, you’ll win back repeat customers, and cultivate your pool of loyal brand champions. Then you can feed segment right back into your lookalike campaigns to keep the cycle going.

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