The Digital Marketing Podcast

In this episode of The Digital Marketing Podcast, Daniel Rowles sits down with Kipp Bodnar, CMO of HubSpot, to discuss what may be the most disruptive year in marketing history. Kipp believes that 2026 could represent the biggest single wave of change our industry has ever seen. Weeks feel like months. Channels are fragmenting. Discovery is shifting. AI agents are entering workflows. And traditional attribution models are starting to break down. From Answer Engine Optimisation to AI agents, rising ad costs to workflow automation, this conversation explores how marketers can stay ahead when the pace of change is accelerating. In This Episode: Why 2026 may be the biggest year of change in marketing history Kipp explains why discovery, personalisation and team workflows are being reshaped simultaneously. Answer Engine Optimisation vs traditional SEO The shift from short keyword queries to ultra long-tail, conversational prompts of 40 to 60 words changes everything. Mentions vs citations in AI search Why brand visibility in ChatGPT, Gemini and Claude is more complex than link-based SEO ever was. The first mover advantage in AI discovery Early adopters can make exponential gains because competition is still low and optimisation is immature. Why AI agents are thriving in customer service but lagging in marketing Marketing problems are less formulaic and more complex, making agent adoption slower but highly promising. The practical AI workflow hack every marketer should try Record yourself completing a repetitive task, upload it to Google Gemini, and ask how to automate it. A simple but powerful shortcut to AI adoption Why attribution is becoming harder again The "golden age" of clean click-to-conversion tracking is fading as AI intermediates discovery. Rising ad costs and the need for new growth channels With paid media inflation increasing, marketers must adopt emerging channels such as AEO and AI-enabled creative optimisation. The importance of strategic conviction AEO cannot be treated as a side project. It must be embedded as a core capability. HubSpot's approach to AI and context Positioning HubSpot as the context layer for AI, enabling agents and assistants to work from real customer data. Key Takeaways: Discovery is changing faster than most organisations are adapting. Answer Engine Optimisation requires different content structures, including FAQs and machine-friendly formatting. Early adoption in AI search offers outsized returns. AI-assisted workflows are often more impactful than fully autonomous agents in marketing today. Marketing teams must bake experimentation and innovation into daily operations. The biggest risk is not AI itself, but failing to evolve working practices alongside it. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/the-hubspot-cmo-interview-kipp-bodnar-on-ai-answer-engine-optimisation-and-the-future-of-marketing

AI is accelerating change at a pace most organisations have never had to manage before. For marketers and business leaders, this is not just another wave of innovation. It is a fundamental shift from linear change to exponential change, where familiar planning cycles, transformation programmes, and long-term roadmaps start to break down. In this episode of The Digital Marketing Podcast, Daniel Rowles is joined by Geoff Tuff, Consulting Principal at Deloitte and co-author of Hone: How Purposeful Leaders Defy Drift. Together, they explore why traditional transformation initiatives fail so often, and what leaders can do instead to build organisations that continuously adapt without losing their sense of direction. Drawing on real-world examples, behavioural science, and lessons from Geofff's latest book, the conversation reframes change as an ongoing discipline rather than a one-off event, and offers a practical way to respond to the disruption created by AI and other exponential forces . In This Episode Why AI represents a shift from linear to exponential change, and why this makes traditional planning models fragile Why large-scale transformation programmes fail so frequently, and the hidden costs they create for organisations The concept of "drift" and how companies slowly move away from their original purpose without realising it The difference between sharpening and honing, and why constant realignment beats radical reinvention How leaders can "bake in" innovation so it becomes urgent, not just important Why behaviour, not technology, is the real engine of change inside organisations The role of management systems as the invisible drivers of culture and decision-making What Minimally Viable Moves are, and how they help organisations adapt without overcommitting Lessons from Amazon and Jeff Bezos on designing systems that reinforce the right behaviours How informal signals from senior leaders can unintentionally shape priorities and outcomes Key Takeaways Exponential change makes waiting for the perfect moment to transform a dangerous strategy Most organisations drift off course through accumulated small decisions, not dramatic failures Honing is about continuous, incremental alignment rather than destructive overhauls Leadership power lies less in vision statements and more in the systems that guide everyday behaviour Small, testable moves reduce risk and keep organisations responsive in uncertain environments What leaders praise, question, or ignore can matter more than formal strategy documents Staying aligned to purpose requires constant attention, not periodic transformation projects 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/dealing-with-exponential-change-leading-in-an-ai-driven-world

The generative AI landscape has shifted again, and at speed. In this update episode, Daniel Rowles breaks down a rapid sequence of releases from OpenAI and Google, explaining what has actually changed, what genuinely matters, and how marketers and business leaders should respond. Covering everything from ChatGPT 5.x and Gemini 3 through to image generation breakthroughs, AI-powered apps, and the rise of accessible 'vibe coding', this episode is a practical briefing rather than hype-driven commentary. Daniel focuses on real-world capability, usability, and where these tools are already changing how marketing teams work, build, and analyse. Rather than asking which model is "winning", the episode reframes the question around task-based selection. Different tools now excel at different jobs, from coding and image editing to workflow automation and reporting. Understanding those strengths is quickly becoming a competitive advantage In This Episode How the AI model race intensified between OpenAI and Google at the beginning of 2026 What actually changed with ChatGPT 5.1 and 5.2, beyond the headline claims Why Gemini 3 represents a major leap in reasoning and coding capability How image generation tools have crossed a new threshold in photorealism and editing What Nano Banana Pro means for branded, on-style visual creation Why ChatGPT connectors becoming "apps" is more important than it sounds How tools like Canva, Adobe, and Figma now integrate directly into AI workflows What vibe coding really is, and why it matters for non-technical marketers How canvas mode transforms the way code, content, and interfaces are created Why AI-powered browsers and agent modes could redefine reporting and analysis Key Takeaways No single AI model is best at everything, and choosing by task is now essential Image editing and brand-consistent visuals are becoming dramatically more accessible Marketers can now create interactive tools and content without traditional development AI-assisted coding is shifting from novelty to practical everyday use Workflow automation and reporting are emerging as some of the biggest wins Understanding interfaces and deployment matters as much as model intelligence 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/generative-ai-update-what-the-latest-model-wars-mean-for-marketers

Search is changing fast. With AI overviews now appearing in the majority of Google results, the rules of visibility are being rewritten in real time. In this episode, Daniel Rowles explores what answer engine optimisation actually means in practice, and how marketers can adapt without chasing myths, hacks, or constantly shifting theories. Drawing on real testing from Target Internet over the past year, this episode cuts through the noise around GEO, AEO, and SEO to focus on what genuinely works. The result is a practical framework for improving visibility both in traditional organic search and within AI-powered results, particularly Google's AI overviews. If you are worried about falling click-through rates, changing user behaviour, or how large language models decide what to reference, this episode provides clear, grounded guidance. Rather than treating AI search as a black box to be cracked, Daniel reframes it as a probability system influenced by clarity, credibility, and consistency. The five techniques covered here are designed to future-proof your content strategy while still delivering value to real users today. In This Episode Why the industry cannot agree on GEO vs AEO, and why the distinction matters less than you think What current data tells us about AI overviews, click-through rates, and changing search behaviour How question-led content aligns with the way people now search using AI Why inverted pyramid writing is suddenly more important than ever How digital PR and brand mentions influence entity reputation in AI systems The growing role of advocacy, reviews, and online sentiment in visibility Why multimodal content is becoming a core ranking signal, not a nice-to-have How schema markup removes ambiguity for search engines and large language models Where to focus your effort while Google's AI results are still evolving rapidly Key Takeaways Answer engine optimisation overlaps heavily with traditional SEO, so doubling down on fundamentals is still smart Clear, direct answers to specific questions improve your chances of being referenced by AI Brand visibility is no longer just about links, but about being mentioned in the right contexts Positive sentiment and third-party validation increasingly influence AI recommendations Publishing content in multiple formats strengthens your overall search footprint Structured data helps machines understand your content, and humans engage with it more easily 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/answer-engine-optimisation-aeo-how-to-optimise-for-google-ai-overviews

In this episode of The Digital Marketing Podcast, Daniel Rowles speaks with Phil Treagus-Evans, author of the new book Human First Marketing, to explore why now, in a world dominated by AI, automation, and synthetic content, marketers must rediscover their humanity. As generative AI reshapes how content is produced, and digital channels become flooded with bland, algorithmically generated material, brands risk losing the very thing that makes them relatable: their people. Phil offers a timely and practical guide for putting humans back at the heart of your marketing strategy, from customer research to team culture and executive presence. Drawing on his work at Giraffe Social, Phil breaks down a four-part framework for building trust, fostering connection, and standing out in a sea of sameness. If you've ever felt like your content is just noise, or you're posting because you're "supposed to", this episode will help you hit reset. In This Episode: Marketing isn't working like it used to Phil opens with a bold claim, and backs it up with data on ad saturation, trust erosion, and content homogenisation due to AI. What is Human First Marketing? A new approach that prioritises people over platforms, empathy over efficiency, and purpose over vanity metrics. The four pillars of Human First Marketing People: Deep customer understanding and employee advocacy Authenticity: Real voices and honest content Connection: Interactions over transactions Purpose: Strategy that means something — and gets results Why you should ditch customer avatars Phil introduces his EMPATH framework for audience research that avoids reductive stereotypes and leans into emotional understanding, patterns of behaviour, and real team insight. The power of visibility and vulnerability From CEOs posting on LinkedIn to sharing the full journey of writing his book, Phil explains how authenticity builds trust, and drives results. Why trust is the new marketing currency In an era of deepfakes and automated outreach, being seen as real, consistent and trustworthy is the ultimate competitive edge. AI isn't the enemy, lazy AI is Phil and Daniel agree: AI is a fantastic tool, but it's the human decisions around how, when and why we use it that matter most. How Human First Marketing improves SEO As Google leans into E-E-A-T (Experience, Expertise, Authoritativeness, Trust), human-centred content becomes not just ethical, but algorithmically rewarded. Key Takeaways: Human content performs better - Whether it's lo-fi video or founder-led storytelling, people trust people more than brands. Leaders must be visible - Exec comms and internal advocacy aren't optional anymore, they're how culture scales and trust grows. Culture comes first - You can't fake authenticity. If your team doesn't believe in what you do, neither will your audience. Strategy before content - Don't just post because you should. Post with intent, empathy, and impact. There's power in transparency - Sharing your struggles, your processes, and your people builds emotional equity. Use AI as a creative partner - Not a content machine. Challenge your thinking, spark ideas, don't outsource your voice. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/human-first-marketing-why-trust-purpose-and-people-matter-more-than-ever