In April 2021, Apple released its iOS 14.5 update, changing the internet privacy landscape almost overnight.
The introduction of the App Tracking Transparency (ATT) framework meant apps must ask for and receive permission from users before tracking them, bringing greater transparency to how apps collect and use data.
This, in turn, introduced new challenges for brands seeking to find audiences, connect with consumers and provide personalized shopping experiences. With less granular data available, advertisers and marketers began exploring alternative strategies, including placing a heavier emphasis on the collection of first-party data via brand.com websites.
Collecting first-party data is no mean feat however, as brands must provide a compelling reason for consumers to part with their data.
That’s where Retail Media Networks (RMNs) come into the picture. Spotting the need for high-quality data, many retailers have stepped into the void created by the evolving, privacy-focused landscape, offering up anonymized, privacy-compliant data sets to enhance a brand’s first-party data.
First-party data refers to the information that an organization collects directly from its own sources about its customers, users, or audience. This data is typically gathered through interactions with the company’s own websites, apps, products, or services.
As the data is collected directly from the brand’s own audience, it is typically highly relevant and accurate for their purposes. Furthermore, brands have full control over their first-party data, and it’s a simpler task to ensure that it complies with privacy laws and regulations, such as GDPR or CCPA.
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Data clean rooms play a crucial role in providing a secure and privacy-compliant environment for analyzing and sharing data. These platforms ensure that personally identifiable information is protected, aligning with regulations like GDPR and CCPA, by anonymizing and aggregating data. They allow for secure data sharing without the need to move raw data, facilitating collaboration between brands, advertisers, and publishers within a controlled environment.
By combining first-party data with second-party and third-party data, clean rooms offer richer insights and a holistic view of customer behavior. This integration enhances measurement and attribution accuracy, enabling marketers to understand cross-channel and multi-touchpoint customer journeys better.
The detailed performance metrics derived from these environments lead to more effective and efficient marketing campaigns, maximizing ROI through refined audience segments and highly personalized messages.
The competitive advantage gained through data-driven decisions and innovation in marketing strategies is significant. Clean rooms streamline data collaboration processes, reducing the need for complex agreements and infrastructure, which allows marketers to allocate resources more effectively.
A drawback for brands using a first-party-data-only strategy is that it limits targeting to existing customers. In order to grow, brands need to identify new and emerging audiences, which is why layering retail data over the top of a brand’s first-party data is becoming a valuable option.
A typical pen portrait for a brand’s audience might detail their age, salary, and location. But by layering retail data over this portrait, it’s possible to build a more detailed and nuanced picture of the same customer.
This could include attributes such as being vegan, having a specific allergy, or planning a party, each of which opens up thousands of potential connections between other products and shopping journeys.
Purchase data from retailers is incredibly useful in this context. A business selling an over-the-counter cholesterol control drug would naturally seek out anyone who needs to manage their cholesterol intake as a high value audience (HVA). Grocery stores can help pinpoint those individuals, creating an audience group that adds low cholesterol or cholesterol-friendly products to their baskets.
There are a plethora of Retail Media Networks and Non-Retail Media Networks (think Uber, Chase and PayPal) that exist across a range of verticals, covering grocery and pharmacy, beauty, fashion, food, and many more.
Brands can experiment with these data providers to discover previously unseen shopping missions and need-states for their products and services.
The benefit is a greater level of detail; retail data often includes extra context, insights about competitors, and various attributes that are useful for planning and strategy.
Many brands, especially those in a growth phase, underutilize this aspect of Retail Media. They may not realize that combining their data with retailer data can help them discover a whole new audience with specific needs.
Get in touch to discover how KINESSO Commerce’s Unified Retail Media Solution can help both endemic and non-endemic brands develop a data strategy that works.
For more information on Retail Media for Non-Endemic Brands, download our whitepaper below:
