Imagine scrolling through an online store and then clicking on a social media app to see who’s posted what. Suddenly, suggestions for products you liked on the online store pop up while on the app.

That’s the magic, in a nutshell, of a retail media network (and machine learning) – it turns your digital shopping habits into personalized recommendations.

Retail media networks (RMNs) have emerged as a powerful marketing tool transforming digital advertising. It is an advertising service run by a retailer that owns large digital properties like websites, storefronts or apps. RMNs allow brand marketers to purchase advertising space on these digital properties.

Born from the evolution of traditional advertising methods, RMNs are now pivotal for retailers and brand marketers. The growth of e-commerce is a factor in its emergence.

Let’s discuss the extensive data retailers capture, their challenges, and how RMNs strategically address these challenges, providing reasons for their pivotal role in retail and marketing.

Data collection: The foundation of retail insights

Retailers collect a wealth of data as the foundation for understanding consumer behavior. This data includes personal information, purchase history, demographic details, geographic data, online behavior, social media interactions, and more.

This vast amount of data helps retailers with insights into consumer preferences, helping them to tailor marketing efforts, enhance customer experiences and optimize inventory management. However, putting this data to practical use presents challenges.

Getting the most out of the data is challenging

With data, there are always challenges on what your conscience will allow you to do, what regulators will let you do, and what your technical abilities and financial means will allow you to do, so extracting value is difficult. Some of those challenges include:

  1. Ethical challenges: Balancing data monetization with customer privacy concerns is critical. Ultimately, we’d like to treat other people’s data as we would want others to treat our data, to preserve privacy and maintain respect. Moreover, monetizing data without proper consent or transparency can lead to ethical issues and damage trust.
  2. Regulatory challenges: Compliance with data protection regulations like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) can be complex and requires retailers to navigate a web of legal requirements. Violations can result in significant fines.
  3. Technical challenges: Handling and processing large volumes of customer data can strain internal resources. Retailers need sophisticated infrastructure for data management and security to protect against breaches, ensuring the integrity of customer information.
  4. Financial challenges: Developing a successful monetization strategy can be challenging, as retailers must determine how to extract value from data while balancing costs. Establishing the necessary infrastructure and expertise for data monetization can require a significant upfront investment.

How retail media networks are a platform for solving these challenges

Retail media networks were designed to help resolve these issues. The primary means RMNs resolve these issues is by providing a platform. The platform gives retailers confidence that ethical and regulatory challenges are identified and addressed. Additionally, technical challenges are minimized as the platform usually has provisions like API functionality that make it easy to set up the environment quickly instead of developing custom code. Here is how RMNs help retailers address these ethical, regulatory, technical and financial challenges:

  1. Privacy compliance and transparency: RMNs often have established practices and expertise in ensuring privacy compliance. With established practices and expertise, RMNs help retailers implement ethical data usage policies, creating customer trust.
  2. Compliance support and data governance: Legal teams within RMNs assist retailers in complying with data protection regulations. RMNs support retailers in establishing robust data governance practices, ensuring data usage aligns with regulatory requirements.
  3. Data integration and security measures: RMNs offer technical solutions for integrating and managing customer data, alleviating the burden on retailers. They often have the infrastructure and expertise for handling and processing large datasets. RMNs ease retailers' burden by providing infrastructure and expertise, helping them securely hold and process large datasets.
  4. Cost-effective monetization and reduced initial investment: RMNs provide a cost-effective way to monetize data. By relying on RMNs, retailers can generate revenue without substantial upfront investments. Additionally, RMNs bring advertising partnerships and monetization strategies, reducing the financial risk and complexities of developing these strategies internally.

Looking ahead to the future of retail media networks

In summary, retail media networks can play a pivotal role in helping retailers navigate and effectively address the ever-more-complicated ethical, regulatory, technical, and financial challenges of monetizing consumer data. By using RMNs, retailers can mitigate risks, ensure compliance, enhance data security, and generate revenue while maintaining ethical data practices and improving the customer experience.

Retailers that rely on best-in-class tools can focus on driving their business forward. The trend is for these challenges to increase in complexity, making RMNs more necessary as achieving that balance between addressing these challenges and reaping the benefits of data-driven insights and personalized customer experiences progressively trickier.

Ready to take advantage of the benefits of retail media to unlock new revenue streams whilst keeping operational costs down? Explore how SAS 360 Match for Retail Media can help.


About Author

Tom Galimanas

Customer Solutions Lead

I'm an analytics professional interested in empowering business through the use of data and analytics. I've held various positions in established as well as up-and-coming financial services firms where I've used data and analytics to drive growth and higher margins.

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