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.

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

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

In this episode of The Digital Marketing Podcast, Daniel Rowles is joined by Emma Tronson, Deputy Director of Marketing at Aston University, for a practical, honest and refreshingly structured look at how to move beyond AI experimentation and into real organisational adoption.

Many teams are stuck in what Daniel calls "pilot purgatory". Everyone is testing tools. Everyone is experimenting. But very few organisations have truly embedded AI into day-to-day operations. Workloads have not reduced. If anything, they have increased.

This episode explores what it actually takes to embed AI into a complex organisation with multiple stakeholders, legacy systems, risk concerns and competing priorities

Emma shares her step-by-step journey of launching an AI task force, securing leadership buy-in, aligning with institutional strategy, and creating a structured framework for adoption that delivered tangible outcomes within a year.In This Episode:

From career setback to AI champion
Emma explains how missing out on a promotion led her to proactively position herself as indispensable by embracing AI learning

Mission AI Impossible
How she pitched a structured AI task force aligned to Aston University's 2030 strategy and secured budget, time and executive support.

Why time matters more than money
Resource allocation and protected "lab time" proved more critical than financial investment.

The six focus areas model
Data and analytics, general work support, copywriting, visual and creative, SEO and web, and social and community. Each task force member owned one domain.

Start small and build confidence
Select staff were upskilled first before launching more widely across the department.

Align AI to real use cases
Experimentation was always tied to live marketing and admissions challenges rather than abstract testing.

Governance before scale
Clear internal guidance helped build confidence in responsible AI usage.

The system integration challenge
Legacy systems and risk aversion slowed deeper embedding, a common challenge across many organisations.

Cohort Two and scaling adoption
Expansion into wider teams with three new priority workstreams: personalisation, data, and custom builds.

Why AI will not replace marketing teams
Instead, it will reward those who actively upskill and adapt.

AI adoption requires structure.

Align initiatives to business strategy from the outset.

Start with a focused pilot group, then scale.

Protected experimentation time is essential.

Bring sceptics into the process rather than excluding them.

System integration and governance are often the biggest blockers.

Innovation must be baked into everyday work, not treated as a side project.

📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/how-to-drive-ai-adoption

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.

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.

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