Navigating the Future of In-Store Retail Media: The Case for Audience-Based Programmatic Activation

As the digital age continues redefining advertising boundaries, a significant transformation is underway within Retail Media. This evolution, largely playing out in the online sphere, has successfully harnessed the power of real-time data analytics, audience targeting, and performance measurement, driving a monumental shift in advertising dollars toward retailers.

The bedrock of this digital triumph lies in leveraging retailer data, including online shopper profiles, loyalty programs, and checkout data, for unprecedented addressability and shopper engagement measurement. However, an oversight remains: the vast majority of shopping still happens in-store, a space where the innovations of online Retail Media have yet to fully permeate.

The reality is that simply transplanting digital screens into physical retail environments without integrating the core success factors of online Retail Media – real-time addressability, audience measurement, and data-driven performance analytics – is a mere facade of innovation. In other words, retailers won’t realize the same uplift in Retail Media revenue in-store as they’ve experienced on digital channels.

To truly revolutionize In-store Retail Media, a digital transformation that involves digitizing physical stores through advanced sensor technologies must occur. This will enable the generation of real-time audience data, which, when merged with existing retailer data, can replicate the online Retail Media success story within the brick-and-mortar context.

Understanding the Divergence in Managing Trade and Shopper Marketing Funds vs. Brand and Media Budgets

A pivotal realization in this journey is understanding the mechanisms through which trade and shopper marketing funds are captured compared to how brand and media budgets are managed.

Trade and shopper marketing funds are traditionally allocated through direct deals between retailers and suppliers, a process requiring meticulous planning, precise control, and customization to align with specific promotional calendars, product launches, and key shopping seasons.

With their reliance on automated bidding and middlemen, programmatic platforms fail to offer tangible advantages for these campaigns. Instead, they introduce potential inefficiencies and cost implications that could erode the critical margins and detailed coordination essential to the business models of both retailers and suppliers. This makes programmatic DOOH (pDOOH) an unnecessary and unsuitable option for managing trade and shopper marketing funds.

In contrast, brand and media funds are predominantly managed by media agencies. These entities require cross-channel, cross-network access to audiences to ensure comprehensive reach and effective use of shopper media value, especially at the upper funnel. This need for cross-network access underscores programmatic buying’s suitability for brand and media budgets, setting it apart from the direct deal mechanisms that characterize trade and shopper marketing fund transactions.

Programmatic DOOH and Digital Signage CMS Shortcomings

Programmatic DOOH (pDOOH) shines as an upper-funnel mass media channel, effectively broadening brand awareness and reach. However, historically, it has not embraced the use of real-time and evidence-based audience data.
This gap, particularly evident in the context of In-store Retail Media, manifests in several important ways:

• Audience Segmentation: pDOOH relies on static audience segments, estimated based on historical data pertinent to a screen’s location. This method does not account for the real-time composition of the actual audience in front of the screen.
• Impression Counting: Without real-time audience data, the true number of viewers for any ad play remains unknown. pDOOH compensates with static multipliers based on historical data, merely assuming how many people might see an ad during its play, leading to inaccurate counts of actual impressions.
• Evidence-based Bidding: The hypothetical nature of audience data in the traditional pDOOH bid stream means that media buyers often bid on – and pay for – an audience that may not have been present during the ad play.

Further, traditional Digital Signage CMSs exemplify a critical bottleneck in the transition towards a more dynamic and responsive In-store Retail Media landscape. To date, these systems have not been designed to efficiently handle or incorporate real-time audience data into the programmatic bidding process.

Latency in sending bid requests is a significant issue, usually occurring far too early before the actual ad play. For instance, some CMSs send the bid request when the previous spot starts, roughly 10 seconds before the biddable spot is scheduled to begin. Others might send it even earlier, 15 to 30 seconds in advance.

This delay means that even if real-time audience data is available, it’s already outdated when the ad is delivered and played. There’s a big disconnect between the bid data and the actual audience present during the ad playout.

Bridging the Gap: Audience-Based Programmatic Activation

The transformative leap towards seamlessly integrating the digital prowess of online retail media into the physical realm of in-store shopping hinges on a concept we call «audience-based programmatic activation.» This approach will be the only way to access upper-funnel media/brand budgets at scale and replicate the massive budget shifts witnessed in online Retail Media.

Bridging the gap between In-store Retail Media’s potential and reality requires meticulous integration of real-time, evidence-based audience data into the very fabric of the bid stream process. This integration empowers Digital Signage CMSs and the entire programmatic ecosystem, including Supply Side Platforms (SSPs) and Demand Side Platforms (DSPs), to operate with unprecedented dynamism and precision.

At the heart of audience-based programmatic activation is the strategic reengineering of the CMS architecture, incorporating real-time audience data into the bid request. This reengineering is critical to ensure that bid requests, now enhanced with audience data, are dispatched within an extraordinarily narrow timeframe – optimally within 0.5 to 1 second before the ad displays.

Such precise timing dramatically reduces the gap that has historically plagued the programmatic bidding process: the discrepancy between the audience data that informs bid decisions and the audience present at the time of the ad play.

By implementing this approach, we effectively synchronize the bid process with real-time audience dynamics, allowing media buyers to engage with the most relevant and current audience data available. This enhances ad spend efficiency and elevates ad relevance and impact, ensuring messages resonate more deeply with the target audience.

Through audience-based programmatic activation, In-store Retail Media is poised to reach the same level of sophistication and effectiveness that has long been online’s hallmark, setting a new standard for targeted programmatic advertising in physical retail environments.

Advanced Predictive Modeling for Audience-Based Programmatic Activation

At Advertima, we’ve leveraged advanced AI and predictive models to revolutionize the integration of real-time audience data into the programmatic bidding process. We can forecast the audience presence in front of the screen for upcoming ad plays with unprecedented accuracy.

By analyzing real-time data streams from sensor technology within the store, enhanced with walking path predictions and other predictive analytics, we can accurately estimate the number of shoppers who will be in front of the screen during the next ad play. The relevant shoppers are anonymously segmented based on visual, contextual, and affinity attributes, which are estimated by combining real-time sensor and retailer data.

This method is the best way to achieve in-store segmentation that closely mirrors online segmentation. That’s despite the usual lack of personally identifiable information (PII) in-store, which is in contrast to the online environment where user-approved PII is available.

We’re already partnering with CMS platforms like Cingerine, Grassfish, and many others to demonstrate not only the ability to predict audience presence and segment composition but also the expected number of impressions each ad play will generate. This nuanced understanding of in-store traffic and shopper engagement patterns allows us to provide highly accurate, predictive data to the programmatic ecosystem. Additionally, our collaboration with One Tech Group’s SSP1 and Splicky’s DSP exemplifies the pioneering integration of these predictive insights into the programmatic buying process.

By informing the programmatic ecosystem about these predictions, we ensure that bids for ad slots are based on anticipated real audience metrics, not merely on historical averages or static multipliers. It’s paving the way for a new era of In-store Retail Media that is dynamic and responsive.

The Road Ahead

In-store Retail Media’s evolution requires collaboration amongst CMS platforms, SSPs, DSPs, and retailers to embrace the principles of real-time audience segmentation, activation, and measurement that have propelled online Retail Media’s success. By developing capabilities to integrate real-time retailer data into programmatic auctions, the industry can address the current limitations of pDOOH and unlock In-store Retail Media’s full potential.

As Retail Media’s landscape continues to evolve, adopting audience-based programmatic activation is a crucial step towards achieving the same level of sophistication and effectiveness in-store as online.

The journey towards this future is not without its challenges, but the rewards promise to redefine the in-store shopping experience, marrying the richness of retailer data with the precision of programmatic technology.