First-party data is the data that a company collects itself. It’s the data collected at acquisition from a web form or an event. It’s also the data collected when a customer makes a purchase or downloads a whitepaper. It can include company-specific data, customer-specific data, demographics, psychographics, and beyond, as long as the company itself is the one collecting. Another way to look at it: it’s the data that a marketing team works so hard to collect. You put in the hours upfront to build systems to capture information on users, but it’s easy to let the strategy end there. Instead, let’s get more juice from the collected data.

Target future best customers

Take everything you know about your current customer base, and segment out the best customers. Who is purchasing frequently? Who is highly engaged? Who has been loyal for years? This best customer segment serves as your foundation for who to target in other channels. For example, in social channels, you can use this audience to create lookalike audiences and target ads to prospects who have similar attributes to these best customers. Just like that, you’re using first-party data to acquire new best customers.

While looking at customer segments, you might notice a group of customers who lag in the engagement category. Instead of letting them plod along unengaged, you can use them as another group for targeting. Gather those that haven’t opened or clicked on an email over the past few months and maybe those that haven't purchased in a while. This unengaged customer segment gives you the short-list of those to reach on other channels. If they’re not engaged, test pausing them from receiving promotional emails, and turn to social again. Social channels are where you can target them with similar promotional messages, but also where they might pay more attention. And, just like that, you’ve improved your overall engagement rate.

Power up personalization

At a basic level, your first-party data powers simple yet important personalization. This gateway to personalization includes elements like adding a first name, category preferences, and other customer-focused attributes. Collecting these data points and using them throughout the journey lets the customer know that you know them, understand them, and are there to help them along the way. It also shows customers that the data they share with you is used in a meaningful way. As customers build stronger ties with a brand, their engagement will increase as well. Think more opens, more clicks, more conversions.

To take personalization to the next level, brands often layer in artificial intelligence (AI). AI makes it easier for customers to use the data they collect since it can help systematize the process cutting down on categorizing and collecting data.

It also helps marketers send personalized product recommendations, content recommendations, targeted communications, and beyond based on behavior and other company collected data points. This is where messages become much more 1:1. By layering in AI, brands are able to send one message but the products one customer sees are different than what another customer sees based on preferences, behavior, and other factors. In these cases, it’s the data that a brand collects that powers these recommendations. The more data a brand has on a customer, the more accurate these predictions and recommendations will be. The best AI-driven customer experiences originate from robust first-party data. 

If you already collect data, then you’re off to a good start. The next step is to return to the data you’ve worked hard to gather and use it for targeting and personalization. Here’s a checklist: 

• Have you targeted your best customers?

• Have you re-targeted the unengaged?

• How are you personalizing at a basic level?

• Are your various data sources supporting your AI?

Watch the video below to learn how to create a target audience based on AI-powered segments. And yes, you guessed it, all of it driven by your first-party data!