The Digital Marketing Podcast

How is AI changing the way customers discover brands, and what does that mean for SEO, paid search, influencer marketing and digital PR? In this episode of The Digital Marketing Podcast, Daniel Rowles and Ciaran Rogers explore one of the biggest shifts in digital marketing: the move from traditional keyword searches towards AI-powered conversations, recommendations and personalised discovery. For years, marketers have relied on identifying high-value keywords, ranking for them organically or bidding on them through Google Ads. But the way people research products and make purchasing decisions is changing. Consumers are increasingly turning to ChatGPT, Claude, Google AI Mode and other AI tools to research their options, compare products and make decisions before they ever visit a website. This creates a fundamental challenge for marketers. If customers are making decisions earlier in their buying journey, how do brands influence those decisions? And if AI systems are drawing on recommendations from creators, publishers, podcasts and other trusted sources, are we seeing the return of something that looks suspiciously like the old practice of paying for links? Drawing on Ciaran's experience at a recent Google event, alongside practical examples from live advertising campaigns, Daniel and Ciaran discuss how marketers need to rethink search, advertising, content partnerships and measurement. In this episode Why AI is transforming how customers discover brands Traditional search often started with a handful of keywords. AI-powered discovery is much more conversational, allowing people to explain their requirements, explore alternatives and receive personalised recommendations. Daniel and Ciaran discuss why customers may now arrive on your website much further along the buying journey. The decline of traditional keyword targeting Ciaran shares how some of his paid search campaigns have experienced significant reductions in traffic and why relying exclusively on exact-match and phrase-match keywords is becoming increasingly risky. They explore how conversational search creates a much larger range of possible queries and customer journeys. Google AI Max, Performance Max and the changing role of paid search Following conversations with Google's advertising specialists, Ciaran explains why he is experimenting more extensively with AI Max, Performance Max and Demand Gen campaigns. The discussion explores how Google's advertising systems are moving towards predicting customer intent rather than simply matching advertisements to keywords. Why first-party data and conversion signals matter more than ever One of the most practical lessons from the episode is the importance of giving advertising algorithms clear signals about what success looks like. Ciaran explains how CRM data, offline conversions and meaningful customer actions can help guide campaign optimisation, and why too many competing conversion signals can create confusion. The growing importance of YouTube and creator partnerships As AI influences purchasing decisions earlier in the customer journey, creators are becoming increasingly important. Daniel and Ciaran explore how YouTube videos, industry experts and other trusted content sources can influence purchasing decisions long before someone conducts a traditional commercial search. Are we seeing the return of cash for links? The discussion considers whether paid creator partnerships could become the new equivalent of traditional link-building. If mentions and recommendations influence AI-generated answers, brands may be tempted to pay for exposure. But Daniel and Ciaran argue that credible, useful and genuinely interesting content partnerships offer a more sustainable approach. Why digital PR is becoming more valuable Influence is not limited to YouTubers and social media personalities. Industry publications, specialist blogs, podcasts and independent experts can all help shape how brands are perceived and discovered. Daniel explains why identifying the trusted voices within your market should become an important part of your AI discovery strategy. Creating more effective video advertising with the ABCD framework Ciaran shares Google's ABCD framework for video advertising: Attention, Branding, Connection and Direction. They discuss how marketers can use this approach to develop advertising that captures attention, builds an emotional connection and provides a clear next step. Why advertising needs to answer customers' questions Rather than focusing exclusively on promotional messages, marketers should consider the problems customers are trying to solve. Helpful content and advertising can build trust and influence decisions at the moments when potential customers are researching their options. The growing challenge of marketing attribution AI-powered research, creator content and conversations across multiple platforms are making customer journeys increasingly difficult to measure. Daniel and Ciaran question whether increasingly complicated attribution models can really capture what influences a purchasing decision. Why asking customers how they discovered you matters again Sometimes the simplest measurement techniques are the most useful. The episode explores why asking customers how they first heard about your brand, alongside monitoring branded searches and wider performance trends, can reveal insights that conventional attribution reporting misses. Key takeaways Search behaviour is changing fundamentally. Customers are increasingly using AI to research and evaluate options before visiting websites, shifting brand influence earlier in the buying journey. Traditional paid search strategies need reviewing. Keyword-focused campaigns remain useful, but marketers should experiment with newer AI-driven advertising formats rather than relying exclusively on established approaches. Better conversion signals can improve advertising performance. Focus on meaningful business outcomes, use appropriate first-party data and ensure conversion tracking is accurate. Creator partnerships can influence both people and AI discovery. Relevant industry experts, publishers and content creators may help brands become part of the conversations that shape purchasing decisions. Digital PR and brand mentions deserve renewed attention. Being discussed by credible third parties is increasingly important when consumers use AI systems to research brands. Useful content is more sustainable than buying exposure. Instead of simply paying creators for mentions, develop partnerships that deliver genuine value to their audiences. Advertising should help people make decisions. Answer questions, solve problems and demonstrate expertise rather than relying solely on promotional messaging. Attribution needs a broader perspective. Combine platform reporting with branded search trends, customer feedback and direct questions about brand discovery. A new approach to digital marketing strategy One of the central themes of this conversation is that marketers need to reconsider where influence happens. Historically, search marketing focused heavily on capturing demand when someone entered a commercially valuable keyword. But increasingly, the decision about which brand to choose may happen much earlier, during an AI conversation, while watching a YouTube video or after encountering advice from a trusted industry expert. That means SEO, paid media, digital PR, content marketing and creator partnerships can no longer be treated as entirely separate activities. Brands need to understand which sources influence their customers, where AI systems are finding information and how to become part of those conversations. There is also an important warning about measurement. When customers move between AI assistants, social platforms, videos, websites and offline conversations, no single attribution model can provide a complete picture of what influenced a purchase. Daniel and Ciaran suggest combining better first-party data, more intelligent advertising signals and a renewed focus on speaking directly to customers. Perhaps the most important lesson is also the simplest: don't chase AI algorithms at the expense of your audience. Focus on creating genuinely useful content, building trusted relationships and helping customers make better decisions.

In this episode of The Digital Marketing Podcast, Daniel Rowles explores how artificial intelligence is making it possible to automate entire marketing workflows, and why this could fundamentally change the way we structure marketing teams. We're moving beyond simply using AI to write content, generate ideas or analyse data. With the combination of AI agents, Skills, Model Context Protocol (MCP) and new AI work environments, marketers can now connect their tools, automate complex processes and build systems that carry out multiple tasks with minimal manual intervention. But does this mean we no longer need marketing executives? Not quite. Daniel explains why the real opportunity isn't about replacing marketers with AI. It's about reimagining marketing roles, removing repetitive administrative tasks and freeing up time for the things humans do best: creativity, strategy, empathy and understanding what really motivates an audience. Drawing on practical examples from Target Internet's most popular AI masterclass, Daniel demonstrates how a single prompt can connect analytics, research, content creation, publishing and social media scheduling into one automated workflow. In This Episode: Can you really replace a marketing executive with three prompts? Daniel revisits a controversial LinkedIn post that sparked a huge debate about AI and marketing jobs. He explains why the point isn't to eliminate marketing roles, but to rethink which tasks genuinely require human expertise. Building an automated marketing workflow with one prompt Discover how Daniel connected Google Analytics, Google Search Console, a content management system and social media scheduling tools to research, create, publish and promote an article. The demonstration shows how AI can handle much of the operational work traditionally carried out by marketing teams. Understanding Model Context Protocol (MCP) MCP is one of the most important developments in practical AI adoption. Daniel explains how it acts like a universal connector between AI and business software, allowing AI systems to retrieve information and, where permitted, take action across different platforms. The tools making AI automation possible Learn how tools including Windsor.ai, Metricool and content management systems can be connected to AI. Daniel also explores how platforms such as Copilot Studio can trigger automated workflows based on events, rather than waiting for someone to enter a prompt. Why AI Skills are essential for consistent marketing AI Skills provide reusable instructions for carrying out tasks in a particular way. Daniel demonstrates how a Target Internet brand skill can ensure that AI-generated articles, diagrams and social media content follow established brand guidelines, and how those instructions can be improved over time. The five stages of AI maturity Daniel introduces a practical maturity model to help organisations understand where they are in their AI adoption journey. From ad hoc experimentation and standardised processes through to connected systems, automation and fully AI-assisted teams, the model provides a roadmap for developing more sophisticated AI capabilities. A practical framework for deciding what to automate Not every marketing task should be automated. Daniel introduces a simple four-quadrant framework that evaluates activities based on how frequently they occur and the level of judgement or risk involved. It helps marketers identify which tasks to automate completely, which need human approval and which should remain human-led. Why human oversight still matters Just because AI can create and publish content doesn't mean it should do so without review. Daniel explores the importance of checking accuracy, maintaining quality, understanding data sources and ensuring that humans remain accountable for important decisions. Rethinking the structure of marketing departments As AI takes on more routine work, traditional channel-based roles may begin to evolve. Daniel considers how marketing teams could increasingly organise themselves around strategy, judgement, automation design and creative value rather than simply managing individual channels. The four technologies driving the next wave of AI adoption AI agents, reusable Skills, MCP connections and AI work environments are coming together to make increasingly sophisticated automation possible. Daniel explains why this combination represents a significant turning point for marketing productivity and innovation. Key Takeaways: Automate tasks, not necessarily jobs. The greatest opportunity is to remove repetitive work while preserving the human expertise that makes marketing effective. MCP changes what's possible. Connecting AI directly to analytics, content management, CRM and social media platforms enables complete workflows rather than isolated tasks. Skills make automation repeatable. Documenting brand guidelines, processes and quality standards allows AI to deliver more consistent results. Start with high-frequency, low-risk activities. Regular reporting, data collection, image resizing and other repetitive tasks are sensible starting points for automation. Keep humans involved where judgement matters. Campaign strategy, positioning, sensitive communications and important business decisions still require human expertise and accountability. AI adoption is a maturity journey. Organisations should progress from experimentation to connected and automated workflows in a structured, iterative way. Use the time saved to create more value. The objective shouldn't simply be to produce more content faster. It should be to conduct better research, develop more creative campaigns and explore opportunities that weren't previously practical. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/creating-an-ai-automated-marketing-department

How to Fix AI Slop: Better Context, Stronger Brands and the Return of Human Judgement What happens when AI makes it easier to produce marketing content, but that content all starts to look and sound the same? In this episode of The Digital Marketing Podcast, Ciaran Rogers speaks to Evan Greally, founder and CTO of Pacey AI, about avoiding AI slop and getting back to the work that matters: understanding customers, developing ideas and building a distinctive brand. Introduced by Daniel Rowles, the conversation draws on Evan's experience as Head of Creative Tech and Innovation at Droga5 Dublin, part of Accenture Song, and more than 15 years working where creativity and technology meet. What begins with an AI-powered mint plant becomes a wider discussion about data overload, creative control and whether AI can develop something resembling taste. Along the way, Evan explains the thinking behind Pacey, with lessons that extend well beyond any single platform. In This Episode From a talking mint plant to a conversation with nature: Evan shares the story behind The Talking Tree, a project that combined environmental sensors, plant responses and AI-generated conversation. It is an unusual starting point with a serious creative question behind it: could technology encourage people to reconnect with the world around them, rather than spend more time staring at a screen? Why marketing needs to ask "so what?": Customer reviews, social comments, competitor activity and dashboards can all contain useful information. But what should a marketer actually do with it? Ciaran and Evan explore the gap between collecting data and making decisions, and why adding another tool can make that gap wider rather than close it. The value of "honest silence": Evan introduces Pacey's principle of surfacing what matters without manufacturing urgency. He describes a system that looks for support from three or more sources before highlighting an issue, but can also tell a team there is nothing significant to worry about that day. The aim is to focus attention, not create another stream of notifications. Can AI really have taste? Evan argues that AI can develop a useful form of brand-specific taste, while distinguishing it from the personal experience and judgement that shape human taste. He explains how approved copy and visuals help build a brand's taste profile, and why evaluating work from an audience member's perspective may be more revealing than asking a model to give it a numerical score. Would someone actually stop scrolling? Turning a daily briefing into useful action: From a short, podcast-style morning update to content creation, scheduling and performance feedback, Evan outlines how Pacey connects market signals with marketing activity. The discussion explores what changes when a team can move from understanding an opportunity to developing a response without repeatedly copying information between disconnected tools. Why editable creative matters: Ciaran highlights the importance of layered design files rather than finished images that are difficult to change. Evan explains how this approach supports human editing, reusable templates, a brand's own photography and different identities across multiple outlets. He also previews an editable video workflow using customers' own footage, rather than relying entirely on generated visuals. An orchestra, not another isolated instrument: Could marketers build something similar by connecting their own AI tools? Evan acknowledges the potential for prototypes, but explains why filtering data, maintaining context, applying design constraints and continually evaluating results are harder to reproduce. The conversation uses an orchestra analogy to explore how different models and specialist agents can work towards the same creative goal. Building trust before speeding things up: Evan shares a product-development lesson: giving people a login is not the same as helping them adopt a new way of working. Slower onboarding, visible sources and clear explanations of how conclusions were reached became central to building confidence. Throughout the discussion, people remain responsible for deciding what is right for the brand and approving what gets published. Key Takeaways Start with the marketing decision, not the dashboard. Before collecting another metric or adding another tool, ask what it will help you understand, change or prioritise. Give AI direction, not just information. Relevant customer signals, a clear brand perspective and a defined purpose matter more than handing a model an undifferentiated pile of data. Treat creative approval as a learning opportunity. Human choices about copy and design can help establish what good work looks like for a particular brand. That judgement should shape the process, not disappear from it. Keep the work editable and the reasoning visible. Teams need to be able to refine creative assets and inspect the evidence behind recommendations, rather than simply accept whatever a system produces. Use automation to make room for better thinking. The ambition discussed here is not to fill every channel with more posts. It is to give marketers more time to understand their audience, develop ideas and deliver the right message at the right moment. Can AI learn a brand's preferences well enough to demonstrate taste, or does that word belong to human creativity? Listen to the conversation and share your perspective with the team. As Daniel explains in the introduction, The Digital Marketing Podcast has no commercial connection to Pacey AI. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/how-to-fix-ai-slop

AI tools are evolving fast. One of the biggest shifts is the move from one-off prompts to reusable AI skills. Instead of rewriting the same instructions every time you use ChatGPT, Claude or Copilot, you can package your best workflows into portable skills that deliver consistent, repeatable results. In this special episode, recorded as the Digital Marketing Podcast celebrates its 16th anniversary, Daniel Rowles and Ciaran Rogers explore why AI skills could fundamentally change the way marketers work. They explain how skills fit alongside projects, agents and prompts, why they are becoming an emerging standard across the major AI platforms, and how to start building your own library of reusable expertise. Along the way, they also reflect on sixteen years of podcasting, discuss the rapid pace of AI adoption within organisations, and share practical advice for creating skills that become more valuable every time you use them. In This Episode How AI skills differ from prompts, projects and agents. Why reusable skills help create consistent marketing outputs across teams. How to build a brand skill that captures tone of voice, design principles and coding standards. Using skills to create websites, dashboards, articles and creative assets that stay on brand. Why updating a skill after every use makes it progressively more accurate. How skills can be shared between team members and even moved between AI platforms. The relationship between ChatGPT Agents, Claude Projects, Gemini Gems and Microsoft Copilot. How to turn your best prompts into reusable skills. Why marketers should organise AI conversations more deliberately as AI memory improves. Practical advice for creating libraries of reusable marketing workflows. Key Takeaways: Develop your best prompts first, then convert them into reusable skills. Treat skills as repeatable processes rather than one-off conversations. Build separate skills for different purposes, such as branding, content creation, web development or analysis. Use multiple skills together to combine different areas of expertise within a single task. Continuously refine your skills by asking AI to update them after each iteration. Think carefully about when to use a prompt, project, skill or agent depending on the task. Organise your AI workspace to avoid confusion as conversations and memories accumulate. Create shared skills that help maintain quality and consistency across your entire marketing team. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/how-to-create-ai-skills

Why do so many beautifully designed websites, ads and digital experiences still fail to convert? In this episode of The Digital Marketing Podcast, Daniel Rowles is joined by Kramer Reeves, CEO of EyeQuant, alongside neuroscientist Professor Peter König, one of the company's founders and a leading expert in visual attention and cognitive science. Together, they explore how neuroscience and AI are reshaping the way marketers, designers and brands understand attention. The conversation dives into the hidden mechanics behind how people actually experience digital content. From subconscious processing and visual saliency through to cognitive overload and design clarity, this episode challenges many of the assumptions marketers make about what users notice, understand and act on. The discussion also explores how AI-powered predictive attention modelling can help teams test creative assets before launch, reducing guesswork and improving performance across websites, ads, landing pages and social content. If you work in UX, creative, digital marketing or conversion optimisation, this episode offers a fascinating blend of neuroscience theory and highly practical design advice. In This Episode Why the human brain is poorly adapted to navigating modern web experiences What happens cognitively in the first few seconds after landing on a webpage Why designers often view their own work very differently from first-time users How "system one" thinking drives most user behaviour online What visual saliency means, and why it matters for conversion How cluttered creative and overloaded messaging dilute attention Why visual hierarchy, contrast and scale shape user behaviour The importance of creating a clear visual storyline through a page or ad How AI models can predict where users are most likely to look Why neuroscience is becoming increasingly important in modern marketing and UX How EyeQuant uses predictive attention modelling to help brands optimise creative before launch Why objective testing is becoming essential in an AI-generated content landscape Key Takeaways Attention is highly selective. You cannot make everything on a page the top priority simultaneously The brain processes visual information subconsciously long before conscious reasoning begins First impressions are heavily influenced by saliency and visual contrast Designers are often too familiar with their own creative to judge it objectively Reducing visual noise can significantly improve clarity and conversion potential Motion, scale and contrast naturally attract human attention because of evolutionary wiring Effective design is not just about aesthetics. It is about guiding behaviour AI-driven predictive testing can dramatically speed up optimisation workflows Clear intent and defined outcomes are becoming increasingly important inputs for creative analysis Objective attention data helps teams move beyond subjective design debates 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/design-that-sticks-applying-neuroscience-to-predict-attention

What happens when a global brand hands over its creative control to unfiltered customer feedback? In this episode of The Digital Marketing Podcast, Daniel Rowles speaks with Emily Barfoot, Head of Dove Beauty at Unilever, about a bold and unconventional campaign built on Reddit conversations. At a time when trust in polished marketing is eroding and AI is reshaping how content is discovered, Dove leaned into one of the internet's most unpredictable platforms. By amplifying genuine, unedited user reviews, both positive and negative, the brand not only drove awareness but also delivered measurable commercial impact. This episode explores how marketers can rethink control, embrace transparency, and tap into community-driven credibility. In This Episode How Dove identified an organic Reddit conversation and turned it into a multi-channel campaign Why Reddit's "unpolished" nature makes it a powerful platform for trust and insight The strategy behind publishing the first 50 real user reviews without editing or filtering How Dove balanced positive and negative sentiment to build credibility The role of social listening in shaping campaign direction and optimisation How Reddit content was extended into out-of-home, influencer, and experiential marketing Why transparency and respecting platform culture were critical to success How the campaign delivered over 260 million impressions and triple-digit growth in the product category The importance of many-to-many marketing in modern brand building How Reddit insights fed directly into product innovation and development Key Takeaways Authenticity is not a tactic. It is a strategic commitment that requires letting go of control User-generated content can outperform traditional creative when it reflects real experiences Reddit is not just a media channel. It is a rich source of customer insight and product feedback Brands must respect platform norms and community expectations to earn participation Balanced sentiment, including negative feedback, increases trust and credibility Social listening should be continuous and actionable, not just observational Experiential marketing can amplify digital engagement when it creates shareable moments AI-driven discovery makes community-led content more valuable than ever Strong products and existing brand trust are essential before taking transparency risks Marketing success increasingly depends on enabling conversations, not controlling them 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/reddit-marketing-case-study-with-dove-turning-real-reviews-into-real-growth

As AI rapidly reshapes how customers discover, evaluate, and engage with brands, marketers are being forced to rethink the fundamentals of the customer journey. In this episode of The Digital Marketing Podcast, Daniel Rowles speaks with Rachel Thornton, CMO of Adobe Enterprise, to explore what this shift really means in practice. Recorded just ahead of Adobe Summit, Rachel shares exclusive insights into Adobe's latest thinking, product direction, and how enterprise marketers should adapt to an increasingly AI-driven landscape. From evolving user expectations to the rise of AI as the primary interface, this conversation goes beyond the hype to examine the real implications for strategy, data, and customer experience. In This Episode How AI is transforming the traditional linear customer journey into something far more dynamic and unpredictable Why discovery and consideration are being reshaped by AI-powered interfaces and assistants What Adobe is announcing at Summit and how it reflects broader industry shifts How CMOs should rethink customer engagement in an environment where AI intermediates interactions The growing importance of first-party data and real-time personalisation How enterprise organisations are adapting their tech stacks to support AI-led experiences The challenges of maintaining brand consistency when AI is part of the customer interface What marketers often misunderstand about AI and where to focus instead How internal teams and workflows need to evolve to keep pace with change Key Takeaways The customer journey is no longer linear. It is fluid, fragmented, and increasingly influenced by AI-driven touchpoints AI is becoming the primary interface between brands and customers, which changes how influence and trust are built Marketers need to prioritise high-quality, structured data to enable effective AI-driven personalisation Speed and adaptability are now critical competitive advantages in digital marketing Organisations must rethink not just tools, but also teams, processes, and skills There is a growing need to balance automation with authentic brand voice and human oversight Experimentation is essential. Waiting for certainty in AI adoption is likely to result in falling behind 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/the-changing-customer-journey-in-an-ai-first-world-insights-from-adobe-cmo

In this episode of The Digital Marketing Podcast, Daniel Rowles is joined by Kendall Breitman from Riverside for a practical conversation about how marketers can use video without needing a full production team, a huge budget or a complicated workflow. Together, they explore why video has become so central to modern marketing, how brands can use it to strengthen SEO and answer engine optimisation, and why authentic, human-led content is outperforming overly polished corporate production. The discussion also dives into practical ways to build a video strategy from webinars, podcasts, customer conversations and expert interviews, then repurpose that long-form content into clips, blog posts, newsletters and more. It is a useful episode for any marketer looking to make video simpler, smarter and more sustainable. In This Episode Why video is becoming essential for SEO, AI overviews and discoverability across search and social platforms How authentic, human-centred video is replacing overly scripted and expensive marketing production Why social media works better when brands behave more like people than polished corporate entities How marketers can use customer interviews and user conversations as both research and content Why webinars, podcasts and expert interviews can become the foundation of an entire month of content How long-form content can be repurposed into medium-form YouTube videos, short-form social clips, blogs, newsletters and gated assets Why medium-form video is often overlooked, despite being highly effective for search visibility and website engagement The most common mistake brands make with video: failing to record valuable conversations and insights in the first place How video testimonials and advocacy content can support trust, social proof and brand visibility Where AI is genuinely helping video production, from transcripts and clips to editing support and audio clean-up Key Takeaways Video works best when it feels useful and human, not overly produced. A single long-form recording can power a much broader content strategy than a series of disconnected short-form posts. Customer conversations are valuable twice over. They generate insight for the business and content for the brand. Video strategy should be tied to business goals, whether that is awareness, education, trust or loyalty. Searchable, practical content such as straight-to-camera answers and product walkthroughs can deliver strong SEO and AEO value. AI should support storytellers, not replace them. The best use of AI is reducing friction so people can create more authentic content. Brands that build confidence in video now will be better placed as the format becomes even more central to digital marketing. The future of video is likely to be more accessible, more efficient and more human, not less. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/practical-video-marketing

What happens when you combine practical digital marketing experience with behavioural science? In this episode, Daniel Rowles is joined by Phil Agnew, host of the Nudge podcast and a specialist in behavioural science, to explore eight psychology experiments and principles that can help marketers create more effective campaigns, stronger customer experiences and more persuasive messaging. Phil shares the original studies behind concepts such as social proof, loss aversion, anchoring and the peak-end rule, then shows how they can be applied in real marketing scenarios, from Reddit ads and SaaS websites to loyalty programmes, pricing pages and customer journeys. The result is a highly practical episode for marketers who want to sharpen their thinking and make better decisions in a world full of noise, automation and increasingly generic content. In This Episode Social proof: why it still works, why specificity matters, and why implying popularity can be more powerful than simply claiming it Loyalty and endowed progress: how giving customers a sense of momentum can make them more likely to complete a journey and stay engaged Loss aversion: why messages framed around what people stand to lose can outperform those focused only on gains The pratfall effect: how showing a flaw, when paired with clear competence, can make a brand or person more likeable Distinctiveness: why standing out matters even more in an AI-saturated content landscape Anchoring: how the first number, comparison or frame people see can radically shape how they judge value The peak-end rule: why customers often remember the emotional high point and the ending of an experience more than everything in between Visible effort: why people value products, services and content more when they can see the work behind them Real examples from digital marketing: including Reddit ad testing, website messaging, social proof banners, pricing psychology and travel search UX Key Takeaways Behavioural science is most useful when it is translated into practical tests, not treated as abstract theory Social proof works best when it feels natural and contextual, rather than overly promotional Small shifts in wording can have a major effect on click-throughs, conversions and retention Customers do not always judge experiences rationally. They remember moments, contrasts and endings Showing some humanity or imperfection can make brands feel more credible and relatable Distinctive positioning is becoming more valuable as AI makes average content easier to produce at scale Helping customers feel progress, momentum or visibility into effort can improve engagement and loyalty Marketers should revisit core psychological principles before chasing every new platform or tool 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/8-psychology-experiments-for-marketers

What happens when clicks get harder to earn, paid media gets more expensive, and audiences spend less time engaging with static content? In this episode of The Digital Marketing Podcast, Daniel Rowles explores why gamification is moving from a nice-to-have tactic to a serious strategic opportunity for marketers. This episode is split into two parts. First, Daniel sets out the business case for gamification in today's digital landscape, where AI overviews, rising cost per click and declining organic reach are all putting pressure on traditional marketing performance. Then he is joined by Luke Santamaria from PlaySpark, a specialist in branded interactive games, to look at how brands are using mini-games, playable ads and reward mechanics to build attention, loyalty and conversion. In This Episode: Why gamification is becoming more relevant as search, social and paid media become less predictable How owned engagement can become a stronger asset than rented attention What gamification really means in a marketing context, beyond simply making things fun How progress tracking, reward loops, challenge and achievement create stronger audience engagement Why quizzes, assessments, calculators, onboarding journeys and email programmes can all benefit from gamified thinking How interactive content can outperform static pages on engagement, return visits and conversion Why the rise of AI tools and vibe coding has made it far easier to create interactive experiences at lower cost How branded mini-games can support both loyalty and acquisition strategies What Luke Santamaria from PlaySpark has learned from building interactive campaigns for retailers, hospitality brands and loyalty programmes Why prizes and rewards can dramatically increase participation and completion rates How playable ads work across platforms such as Meta and mobile gaming environments What marketers should measure when testing gamified campaigns, from play rate and completion rate through to redemption and sales How personalisation could shape the next phase of gamified marketing experiences Key Takeaways: Gamification is not just about entertainment. It is a structured way to design more engaging marketing experiences. As AI overviews and no-click behaviour reshape digital marketing, brands need to offer experiences that search engines and summaries cannot replicate. Interactive content can help improve conversion efficiency, especially when traffic is harder or more expensive to acquire. Simple mechanics such as progress bars, unlockable content, rewards and challenges can strengthen repeat engagement. Gamification can work across B2C and B2B environments, particularly when the incentive is meaningful to the audience. Mini-games and playable ads can hold attention for longer than traditional ad formats and create more active brand involvement. Measurement matters. Success should be judged using both game metrics and commercial outcomes. New AI-assisted creation tools are lowering the barrier to entry, making experimentation far more accessible for marketing teams. The biggest opportunity may be in combining gamification with owned channels such as email, apps, learning platforms and loyalty programmes. Brands that start experimenting now may benefit from a genuine early-mover advantage. 📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/gamification-for-digital-marketing