How to Leverage First-Party Data for Retail Personalization 

How to Leverage First-Party Data for Next-Level Retail Personalization 

May 9, 2024

Customers want personalization when they shop, but too much personalization can get creepy – especially when data privacy is at stake. While walking that line can be tricky, online retailers are in the best position to strike a healthy balance because loyal customers are their lifeblood. 

Retailers are already leveraging first-party insights to personalize the customer experience, and with the rise of commerce media, they now have the opportunity to apply customer data and contextual signals to a new revenue-generating initiative – advertising. When done right, it shouldn’t feel much like advertising at all, but rather an extension of the customer experience. 

Meeting Consumers Where They Shop

Forty-three percent of consumers believe it’s important that digital ads are personalized. Commerce media is providing new ways for retailers to deliver on this expectation. It allows retailers to tap into the wealth of customer information they have collected through past interactions, to reach consumers directly where they shop – within an online retail environment. 

According to a study from PwC, 34% of consumers worldwide turn to retailers’ websites to research products ahead of a purchase. As ecommerce websites grow as spaces for product search and discovery, retailers can leverage post-transaction ads, display banners, and sponsored product ads to meet consumers with tailored offers wherever they are in their purchase journey. 

Top Five Destinations for Researching Products Before Purchase

Harnessing the Power of First-Party Data

At the heart of effective personalization lies the strategic use of first-party data. While demographic data is common across platforms, retailers have unique insight into transaction history, behavioral data, and contextual signals. Some examples include:

  • Behavioral data: browsing history, website visits, products added to shopping carts, abandoned carts
  • Transaction history: purchases, average spend, price points, payment methods
  • Contextual data: web content and keywords found on the page a user is browsing

Together, these data points help retailers understand consumers’ past behavior and current mindset to determine the right ads to deliver at the right moment.

Types of Data for Personalization

Balancing Personalization and Data Privacy

Privacy must take center stage when discussing data-driven personalization. Today’s consumers are savvy – they know data fuels personalization and 66% are willing to share it in exchange for better retail experiences. 

Personalization should enhance customer satisfaction, not erode trust. When leveraging data for personalization, transparency is key. Retailers should be upfront about the data they plan to collect and how they plan to use it. They must also provide consumers with the choice to opt out of data sharing.

Retailers must also prioritize data security, complying with the latest privacy regulations to keep customer information safe. Innovative solutions like data clean rooms allow secure third-party collaboration without compromising privacy.

The Role of AI in Personalization 

The future of personalization in commerce media will be largely shaped by AI. According to a survey from Bolt, 72% of US digital retailers believe that AI-driven personalization is the ecommerce trend that will have the biggest impact on their business in 2024 – and with good reason. 

Retailers can leverage AI to segment customers into groups based on shared characteristics and behavioral patterns, personalizing ad messages to make them more relevant and impactful. AI can also help to drive:  

  • Dynamic Recommendations: AI can recommend products or services that complement a customer’s recent purchase. For instance, someone who buys a new camera might see ads for camera bags, memory cards, or editing software.
  • Real-Time Personalization: AI can personalize ads in real time based on a customer’s current behavior. For example, after browsing for hiking boots a consumer may see an ad for performance socks on a different website.
  • Creative Optimization: AI can analyze the effectiveness of different ad formats and creatives. This helps businesses identify what resonates best with each customer segment and optimize accordingly.
Learn more about AI-Driven Personalization from Fluent

Conclusion

As commerce media continues to grow, retailers will find new opportunities to leverage first-party data for personalization. By seamlessly integrating targeted offers and recommendations into the online retail experience, businesses can forge deeper connections with their customers, foster long-term loyalty, and unlock new avenues for growth.

Check out more resources to get fluent in:

Commerce Media | Retail MediaPost-Transaction Advertising | First-Party Data