60% of consumers say they’ll become repeat customers after a personalized shopping experience. What does personalization mean in a cookie-less future? As we move toward more privacy laws protecting consumer data, brands should set their sights on first-party data strategies: namely, how to collect and capitalize on data that comes directly from consumers. Personalization based on first-party data is how to become one of the trusted brands your consumers love to engage with, by making them feel understood and showing them that sharing their data is worth it.

What does first-party data mean?

First-party data refers to data collected directly from consumers through owned channels, as opposed to being bought from third-party vendors. Some examples include: purchase history, browsing behavior, app user behavior, and social media engagement from owned accounts. 

There are already laws in place to protect consumers from third-party vendors, and Google plans to phase out cookies by 2024. Brands that are interested in creating 1:1 personalized shopping experiences should begin creating strategies to collect and act on first-party data from their consumers. Here are a few ways to get started.

Tips for a First-Party Data Strategy

Build a rapport with your customers. The consumer-brand relationship hinges upon trust. The first step to your first-party data strategy is to garner that trust with strong data governance and data transparency.  Make sure your consumers know how their data is going to be used, and that they can opt out of sharing if they want to. Opting out shouldn’t throw a wrench in your personalization plans, as you should have a plan in place to personalize the experience for anonymous consumers. Brands can personalize the experience based on seasonal and trending data to reach customers that might not otherwise share first-party data.

Offer value in exchange for first-party data. More so than learning about your brand, consumers love to learn about themselves. In order to entice them to share first-party information with your brand, create value that speaks to your consumer. This could be as simple as a quiz that gets to know their habits in order to recommend a product or regimen, or creating gated content or newsletters that inform your consumers about trends in your industry. Brands that do this well gain first-party data they need and the customer loyalty they desire without much lift on the front-end of these personalization efforts.

Evaluate what your CDP can do for you. Your customer data platform can store first-party data but when it comes to actually analyzing the insights and building campaigns, things get a little more complicated. Most brands are limited by headcount when it comes to analyzing data, and by bottlenecks when it comes to putting campaigns into place. Not to mention the fact that it’s hard to measure ROI when it comes to customer data platforms; there are so many extraneous steps between collecting the data, building the customer profiles, deploying the campaigns, and seeing results.

If your CDP is costing you more than it’s worth, consider an AI marketing tool that stores, analyzes, and acts on first-party data all in one breath. Artificial intelligence can replace and outrun a CDP and work in tandem with nimble marketing teams that want to scale 1:1 personalization. 

 

In a 2021 survey, AMA New York found that the acceptance rate for personalized ads was 54%, having increased from 35% in 2019. Now is the time to mobilize on this trend and begin personalizing your marketing at scale. Prioritizing first-party data will help brands thrive amidst privacy laws and enable personalization that feels natural to the consumer.

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