The Future of DTC Retail Performance: How AI Can Fill the Gaps Left by Signal Loss

The landscape of direct-to-consumer (DTC) retail is rapidly shifting. Today's brands are grappling with challenges such as signal loss, reduced access to key data sources, and tighter privacy regulations that have rendered even first-party data insufficient in sustaining growth online.

Many brands are turning to walled gardens like Google, Facebook, and Amazon.com as potential solutions. These platforms have excelled in data-driven marketing without relying on cookies. However, their closed ecosystems come with significant drawbacks: limited cross-platform insights, restricted data ownership, and soaring cost-per-thousand impressions (CPMs).

As a result, many DTC brands find themselves at a performance plateau — a common barrier for growth marketers. However, few are considering the vast opportunities for growth that the open web presents. There is a prevalent assumption that navigating the open web is challenging, with inconsistent data, difficult platform management, and complex media measurement. However, this perception has changed. With the advent of artificial intelligence (AI), the open web has become accessible to retailers of all sizes, effectively addressing the signal loss issue and enabling advertisers to reach extensive audiences while consistently measuring success. This is the key to breaking through the performance plateau.

Breaking Through the Performance Plateau

The limitations of walled gardens, while effective within their own ecosystems, quickly become evident for retailers. The scale they provide is restricted by escalating media costs, making it challenging for retailers to achieve growth while managing customer acquisition expenses. Research indicates that advertisers should leverage multiple touchpoints to foster growth. To do this effectively, retailers are increasingly turning to open web channels such as TV, podcasts, radio and mobile.

Programmatic advertising emerges as the most effective and efficient approach to reach audiences; however, it has traditionally been perceived as complex and difficult to navigate. Issues like data loss, intricate platforms, and inconsistent measurement have rendered programmatic advertising cost-prohibitive for many DTC retailers.

Fortunately, the landscape is transforming with the emergence of a new generation of demand-side platforms (DSPs) that leverage extensive data and AI to engage audiences across the open web while consistently measuring campaign effectiveness. This innovation enables retailers to connect with consumers at moments when they're most open to advertising, maximizing their investments beyond the confines of walled gardens.

As a result, programmatic advertising empowers retailers to maintain control over their data, providing a more holistic understanding of their customers without being restricted to a single platform. It truly represents a game-changing opportunity for retailers.

The Role of AI in Closing Measurement Gaps

First-party data has become increasingly important, but it’s not immune to the effects of signal loss. As the availability of third-party cookies declines, even retailers with robust first-party data strategies face challenges in maintaining performance levels that were once easier to achieve. Measurement, a cornerstone of performance, is now more complex, requiring solutions that can work with less deterministic data. This is where AI truly shines.

Through machine learning, AI can analyze patterns and predict with remarkable accuracy the effectiveness of every ad you deliver, whether that's across a TV, a podcast or on a website. This holistic view not only enhances optimization but also provides valuable insights for marketing teams to create better content and refine their overall marketing strategy.

For example, Walmart uses AI to enhance its loyalty programs, enabling the retailer to make real-time decisions about customer preferences and optimize personalized offers even as the broader advertising ecosystem faces signal loss. By relying on AI’s predictive capabilities, Walmart continues to drive performance and maintain a competitive edge.

DTC retailers, which may lack the vast resources of larger competitors, are really benefiting from AI’s ability to bridge data gaps. These companies, once heavily reliant on third-party data, can now use their first-party data and AI to build audiences, personalize targeting strategies, and accurately measure return on investment. The Container Store, for instance, applied lookalike audience modeling to find consumers similar to users already visiting its website, resulting in 37 percent more purchases and 1.4x higher ROI in cookie-less environments.

Programmatic advertising enabled by AI allows retailers to compete in an increasingly challenging landscape. No longer limited to walled gardens, retailers can connect with consumers across channels and platforms along their individual purchase journeys. As research shows, it's far more effective to take a mixed media approach than to spend your entire budget on one channel: it more than doubles your brand impact and increases ROI by 35 percent to 65 percent.

The Future of DTC Retail Growth

Reflect on how your media consumption has evolved over the past two years. Personally, I've seen a significant shift. Today, I primarily see ads on television and hear them through podcasts, while two years ago, social media was the primary source. As media consumption transforms, your advertising strategy must evolve.

Programmatic advertising now provides a streamlined and effective means for DTC retailers to connect with their audiences across various devices, reaching them outside traditional platforms. Engaging with audiences when they're most receptive to your message can lead to remarkable results. Those who embrace this approach break through performance plateaus and achieve profitable growth for their businesses.

Amit Kotecha is chief marketing officer at Quantcast, a platform that simplifies digital advertising by connecting brands to their audiences using real-time data from over 100 million destinations.