AI-Powered Retail Media: How Shopsense Makes Content Shoppable

1. How is your organization exploring the integration of AI-driven commerce within content to create new monetization streams and deepen consumer engagement?

At Shopsense, we’re focused on transforming content into commerce in a way that feels seamless, scalable and deeply tied to consumer passion. That’s because fandom drives purchases; whether it’s tied to a talk show, drama or live sports, viewers are inspired by what they watch on-screen. We built our AI engine to ingest video, image and text-based content to identify contextually relevant products and automatically generate curated storefronts around that very content. In fact, we’ve already ingested over 1 billion SKUs from more than 1,250 retail partners, so our system can quickly surface product matches—including exact matches or items that are stylistically aligned—without requiring a ton of labor and manual effort. This capability is what allows us to unlock monetization opportunities wherever content lives, and gives publishers, networks and creators tools to activate their IP in new and meaningful ways.

2. How do you plan to maintain editorial integrity while embedding commerce solutions within native content experiences?

When it comes to content, we’re not the creators—we’re the enablers. Here’s one way to think about it: our technology uses existing content as a creative input and pairs it with shoppable experiences that are authentic and aligned. But of course it’s critical that the content partners maintain full control of the experience. We work closely with each partner to respect their brand, editorial and audience guidelines, which could mean weeding out certain retailers, filtering by price point, or blocking entire categories. For example, a publisher may want to exclude big-ticket luxury items from a mass-market piece, and so our models adapt accordingly. Because we’re not authoring the editorial, but rather enhancing it with intelligently surfaced commerce, we’re able to preserve integrity while still driving value.

3. What role does personalization and product relevance play in improving conversion rates and retaining audience attention in a saturated content market?

Our whole ethos is that product relevance is everything. When we’re able to surface the exact lipstick worn by a talk show host or the really cool blazer featured in a scripted series, we see conversion rates jump—as much as 4 times higher compared to more generic thematically aligned recommendations. Audiences are emotionally invested in the content they consume. If someone connects with a character or host, they want that exact same item because it’s a tangible extension of their emotional connection to the content. That’s where our AI-powered personalization engine really shines. We’re able to tap into fandom and emotional connection at scale, and bridge the gap between the screen you’re watching and the shopping that’s inspired by that screen. In fact, nearly 63% of consumers say they discover new brands or products through TV content, which shows just how powerful entertainment has become as a driver of commerce.

4. How are you rethinking your monetization model to capitalize on the convergence of storytelling and shopping, particularly among Gen Z and Millennial audiences?

This is exactly why we prioritize the second screen experience. Gen Z and Millennials are fully accustomed to consuming content with a phone in hand—it’s their default behavior. We’ve seen this play out: if a show is shoppable but the call-to-action isn’t clear or well timed, even the most eager viewers might miss it. But when we lean into that phone-in-hand behavior—surfacing real-time shoppable moments on mobile, aligning products with the content they’re already immersed in—engagement rates spike when we meet them in the moment on the device they’re already using. For younger audiences, content-integrated commerce isn’t disruptive when it’s done right; it’s an experience they expect these days. The key is to meet them in the moment without asking them to shift context.

5. As commerce integration expands across editorial, video, and social content, how are you preparing your organization to scale AI-driven commerce across multiple formats and channels?

Even though we launched last year with broadcasters in our sights, we built Shopsense from day one to be format-agnostic. Whether it’s text, video, stills or live content, our models can ingest and interpret it—identifying relevant products, creating storefronts and tagging shoppable moments across channels. Because our product library is already robust and our AI is contextually trained, we can easily plug into new formats with very little friction. We’ve already proven we can do this across digital articles, linear TV, CTV and social posts. So as content continues to fragment across platforms, which it inevitably will, we’re positioned to scale along with it, and to ensure commerce is embedded natively and intelligently wherever audiences choose to engage.

6. How is your company managing the balance between leveraging contextual data for commerce personalization and maintaining user trust and data privacy?

This is such a great question. We focus on contextual signals, not behavioral ones. Our approach to personalization is rooted in the content itself, rather than tracking individual users or hoovering up personal data. What that means is that we can deliver highly relevant product recommendations while keeping user trust intact. In other words, our technology is privacy-first by design, offering our partners a compliant way to unlock commerce-driven value without the thorny complexity of data collection. And for consumers, the experience feels seamless and secure and something they don’t have to second-guess. We believe the smartest personalization simply requires intelligent alignment between content and commerce.

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