This article was based on the interview with Mark Wagner, Sr. Director, Digital Strategy at Horizontal Digital by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
The distance between the brand voice meticulously crafted in a boardroom and the way it’s perceived in the wild can be vast and treacherous. Marketing leaders spend fortunes defining their brand promise, only to see it refracted, distorted, or sometimes completely ignored across a chaotic landscape of customer reviews, social media commentary, and support tickets. The core challenge isn’t a lack of data; it’s a deluge. We are drowning in feedback, yet thirsty for genuine insight. The traditional approach of periodic brand health studies and manual analysis of sentiment feels antiquated, like trying to navigate a Formula 1 circuit using a folded paper map. The lag between customer expression and strategic response is often measured in quarters, by which time minor dissonances can escalate into major brand erosion.
The conversation is shifting, however, from passive listening to active intelligence. The emergence of more sophisticated, agentic AI promises to close this gap, transforming the cacophony of customer feedback into a coherent, actionable signal. This isn’t about another dashboard with color-coded sentiment scores. It’s about creating an intelligent system that understands the nuance of your specific brand promise and can identify deviations in real-time. It’s about moving beyond simply monitoring the conversation to actively shaping it by turning raw intelligence directly into strategic action. During a recent conversation, I had the opportunity to explore a practical application of this concept with Mark Wagner, Senior Director of Strategy at Horizontal Digital. His team’s work developing an AI-powered “SenseAgent” for Pet Supplies Plus provides a compelling look at how to bridge the divide between brand intent and customer reality.
From Cumbersome Task to Strategic Advantage
For any large retail brand, especially one with a significant physical footprint, understanding the customer experience at a local level is a monumental task. The sheer volume of feedback, spread across countless platforms and locations, makes a comprehensive analysis both difficult and expensive. This was the foundational challenge that sparked the creation of the SenseAgent. It wasn’t about a lack of will, but a lack of a scalable mechanism to listen, understand, and, most importantly, act.
“The idea was really born out of a need to more quickly and easily collect and understand and act actually on what these customers are saying and doing at the physical retail level, as well as addressing things online. Things like addressing brand perception, the sentiment, deviation from what they want their brand to be perceived as in the marketplace in terms of how people are talking about it, and service issues. As you may know, this can be a very cumbersome and expensive task for retail brands.”
Wagner’s point cuts to the heart of a universal problem for enterprise marketers. The process he describes as “cumbersome and expensive” is a familiar pain point. It involves teams of analysts, disparate software tools, and endless spreadsheets, all trying to stitch together a coherent narrative from fragmented data. The result is often an insight that is delivered too late to be truly effective. By framing the problem this way, Wagner highlights the strategic imperative for AI: not as a technological novelty, but as a direct solution to an operational bottleneck that inhibits agility and responsiveness. The goal is to transform brand monitoring from a reactive, archaeological dig into a proactive, real-time intelligence function that serves the entire organization.
Beyond the Dashboard: Mobilizing Action with AI
The true value of any intelligence platform is not in the data it presents, but in the action it inspires. A dashboard that simply reports a dip in positive sentiment is little more than a high-tech anxiety generator. The next evolution of MarTech, as exemplified by agentic AI, is about completing the circuit from insight to execution. The system must not only identify a problem but also initiate the solution.
“The action really comes in when Sense mobilizes next steps for marketing. It can accelerate existing work tasks, and it can do what AI does well already, suggest and create content around marketing campaigns or strategic briefs that resonate with that perception and brand and help tune it… All this legwork has taken the pressure off of Teams’ mundane workflows…it can accelerate decision making, using more human creativity, judgment and strategy instead of tactical cognitive tasks that can be taken off of our plates.”
This is where the concept becomes truly powerful for marketing leaders. Wagner is describing an AI that acts as a strategic partner, not just a passive observer. When a deviation in brand perception is detected, the agent can kick-start the response: drafting a creative brief for a new campaign, suggesting messaging points for social media teams, or even creating a ticket in a service queue to address a recurring operational issue. This frees up senior talent from the “tactical cognitive tasks” of data sifting and initial drafting, allowing them to apply their expertise where it matters most—in refining the strategy, exercising human judgment, and making the final creative calls. It rebalances the workload, letting technology handle the legwork so humans can focus on the strategic heavy lifting.
Teaching AI Your Brand’s DNA
For this entire system to work, the AI must be more than a generic language model. A standard sentiment analysis tool might register a comment as “positive,” but it can’t tell you if that positive sentiment aligns with your core brand pillars of “innovation” and “sustainability.” To be truly effective, the AI must be trained on the unique DNA of your brand. It needs to be given a master key to your brand guidelines, a deep understanding of your intended voice and promise.
“Leveraging the Sitecore platform, we instruct that agent on proprietary brand content… We give it a direction on how a brand promise is supposed to be communicated and its intended expression. And that’s all proprietary. We give it examples of what this might be, what it might look like, how it might sound. And that helps build a corpus of understanding for that for the AI. And through the language model… we instructed to pick up on both those deviations from the intended brand promise, as well as signals where people may be defecting or churning.”
This is perhaps the most critical insight for any leader looking to leverage AI for brand intelligence. Your proprietary brand strategy is the secret sauce. As Wagner explains, the process involves feeding the AI your internal playbooks, your campaign history, your voice and tone guides—everything that defines how your brand should show up in the world. This creates a bespoke model that isn’t just looking for positive or negative keywords; it’s looking for alignment. It can detect the subtle but critical difference between a customer saying, “Their service is cheap and fast,” when your brand promise is built on “premium, white-glove support.” This level of nuance is what separates a generic tool from a true competitive advantage.
A Practical Path Forward: Get Messy, Get Iterative
The prospect of implementing a sophisticated AI strategy can feel daunting. It’s easy to get lost in conversations about infrastructure, data models, and long-term roadmaps, leading to analysis paralysis. However, the path to adoption doesn’t have to be a multi-year, nine-figure behemoth of a project. The key is to start small, stay focused, and embrace an iterative, agile mindset.
“Mobilize your brightest, most industrious, cross-functional team members… to solve for those challenges or those opportunities and do it lean startup style… spend time really defining that product market fit… And then get messy, get collaborative, get iterative, get ideas, lots of them out on the table fast… get the narrow solution in market and then track those outcomes, document those failures… Enhance what works, kill what doesn’t, internalize your learnings, and just keep going, one by one by one.”
Wagner’s advice is a refreshing dose of pragmatism. He demystifies the process, framing it not as a massive technological overhaul but as a lean, focused initiative. For marketing leaders, this is an empowering message. You don’t need a perfect, all-encompassing AI strategy from day one. Instead, identify a single, high-value problem—like understanding sentiment around a new product launch or tracking brand voice consistency in one specific channel. Assemble a small, cross-functional team and give them the freedom to “get messy” and experiment. This approach mitigates risk, demonstrates value quickly, and builds organizational momentum. Success is not about a single grand launch; it’s about a series of small, validated wins that compound over time.
The chasm between a brand’s intended message and its public perception has long been a source of frustration for marketing leaders. We’ve had the tools to broadcast our voice and the tools to listen to the echoes, but connecting the two in a meaningful, real-time feedback loop has remained elusive. The work being done with agentic AI demonstrates that we are on the cusp of finally closing that loop. By creating systems that are not only capable of listening at scale but are also deeply educated in the unique nuances of our own brand promise, we can move from reactive analysis to proactive course correction.
The journey, as Mark Wagner suggests, begins not with a grand technological vision but with a practical, focused effort to solve a real business problem. The future role of the marketing leader will be less about manually interpreting disparate data sets and more about conducting an intelligent system where human creativity and strategic judgment are amplified by AI. As he astutely noted, we will soon look back and wonder how we ever operated without this level of daily, integrated intelligence, much like we now struggle to recall a world without the web or mobile phones. The challenge ahead is not whether to adopt this technology, but how to wield it with the wisdom and focus required to build a more resonant, responsive, and resilient brand.
