As retail media networks (RMNs) continue to gain prominence, they face a critical challenge: maximizing the value of their digital real estate. While some retailers have made significant progress, many are still in the early stages of monetization and need guidance on yield management to ensure their media networks are optimized. Looking at examples and strategies from publishers and media networks is a good place to start.
I remember in one of my roles, Fridays meant pulling numerous reports, consolidating them into Excel, applying some pivot table wizardry, and presenting the results to leadership and sales. That data was our window into whether we were on track -- or in trouble -- for our monthly and quarterly goals.
Fortunately, tools and data usage have advanced significantly since then. In this guide, we’ll explore how retailers can optimize their media networks using sophisticated yield management strategies and how Kevel's advanced tools can drive this transformation.
Yield management is critical in digital advertising. For retail media networks, it involves balancing revenue maximization from ad inventory with factors like pricing, inventory allocation, and ad placement. The goal is to sell all inventory at the highest possible prices, but -- with the exception of adding new ad formats or experiencing hyper growth -- this is complicated by fluctuating demand against relatively consistent total inventory.
RMNs face these unique yield management hurdles:
Drawing from publisher experiences, retailers can implement these strategies to achieve effective yield management:
1. Demand Forecasting: Accurately predicting available inventory across all channels is crucial for strategic allocation and pricing. Tools from tech partners, like Kevel’s Forecasting API, can enable precise prediction of available inventory across all channels, allowing for strategic allocation and pricing.
2. Dynamic Pricing: Adjusting CPMs in real-time based on demand, seasonality, and other factors helps maximize revenue. The rise of artificial intelligence has made this process simpler -- Kai can make real-time decisions on inventory allocation, pricing, and ad placement.
3. Inventory Segmentation: Dividing inventory into different segments (e.g., high-traffic pages, mobile app, email newsletters) and pricing them accordingly can help extract maximum value from each segment. Page context is also key, allowing retailers to understand the buying journey and build ad inventory accordingly.
4. Holistic Yield Management (HYM): This approach involves allowing inventory to flow between traditionally siloed channels based on where demand is highest. Kevel’s platform allows for all ad formats to be consolidated, providing unified access to inventory across all channels.
5. Programmatic Integration: Leveraging real-time bidding and programmatic direct deals can automate and optimize ad sales processes. Kevel's Retail Media Cloud™ supports integration with programmatic channels for comprehensive yield management.
To effectively manage yield, retailers must focus on several key metrics:
Effective yield management relies heavily on data and predictive analytics. Key strategies include:
1. Historical Data Analysis: Using past performance to forecast future demand and adjust strategies accordingly.
2. Real-Time Data Processing: Implementing systems that can make split-second decisions based on current market conditions is crucial for optimizing yield in a dynamic marketplace. The industry is seeing an uptick in AI providing this capability for RMNs.
3. Audience Segmentation: Leveraging first-party data to create valuable audience segments that command higher CPMs. Often retailers can’t use their most valuable loyalty data due to their ad server’s business model which can drive data leakage. But Kevel’s platform allows retailers to use their most valuable segments, without risking data leakage, in the way that suits them best.
4. Test And Learn: Continuously testing different ad formats, placements, and pricing strategies can help identify the most effective approaches. A good tech stack partner should offer tools that support comprehensive testing and optimization.
True holistic yield management can seem impossible to reach and retailers entering this space are facing significant challenges. Here’s how to tackle them:
The future of yield management in retail media is already being shaped by emerging trends. Advanced AI and machine learning algorithms are becoming increasingly essential for real-time decision making and predictive analytics. As third-party cookies phase out, the importance of leveraging first-party data for audience segmentation and targeting is growing.
Yield management strategies must also evolve to account for cross-channel consumer behaviors and attribution as shoppers interact with brands across multiple touchpoints. Additionally, with tightening privacy regulations, strategies must adapt to respect user privacy while still delivering effective targeted advertising. These trends are driving the development of more sophisticated, data-driven, and privacy-conscious network optimization approaches in retail media.
Mastering yield management is crucial for RMNs looking to maximize their revenue potential and advertiser value. By learning from the experiences of digital publishers and leveraging advanced tools like Kevel's Retail Media Cloud™, retailers can transform their digital properties into high-performing media networks.
The future of retail media belongs to those who can master the complex dance of inventory allocation, pricing strategy, and real-time optimization.
Ready to optimize your retail media network? Learn more about implementing advanced yield management strategies for your RMN with Kevel's Retail Media Cloud™ today.
