We recently had the pleasure of attending a DMA event where key insights from the Customer Engagement Future Trends Report were shared, along with compelling case studies and thought-provoking discussions. One particular debate, sparked by Ian Gibbs, Insight and Planner Director at DMA, really grabbed our attention; how exactly is AI being used in the digital marketing industry – beyond just buzzwords? Because we know everybody’s talking about it. But what are they actually doing with it? 

 

1. AI – Efficiency vs Effectiveness 

The DMA’s trend report highlights that 70% of marketers are already using AI consciously in their roles. However, much of this usage falls into the category of efficiency-driving applications – content generation, social media management, and chatbots being some of the most common. It makes sense; after all, time is the one thing we’re all trying to optimize, and AI is an excellent tool for saving time. 

However, effectiveness-driving applications – like using AI to enhance creative, and inform predictive modelling, and machine learning – are much less of a focus. According to the report, there are still numerous barriers preventing deeper AI adoption for effectiveness. Barriers like customer wariness, the risks of repetitive content, legal concerns around AI-generated material, and the evolving skillsets required to leverage AI fully. 

In this context, it’s no surprise that efficiency remains the primary focus. 

The Case for Effectiveness: Learning from LNER 

A particularly insightful follow-up to this debate came from Lauren and Omar at LNER, whose case study demonstrated two key points: 

1. Collaboration across skill sets and departments fosters innovative solutions.
2. Investing in AI for effectiveness – not just efficiency – can drive meaningful impact, from improving KPIs to enhancing customer experience.

Their case study outlined the transition from high-volume, broad-based email sends to a model rooted in customer propensity scoring. At any given time, only 5% of LNER’s audience were ‘in-market’ for travel, yet they were engaging far more broadly. Through a rapid proof-of-concept phase, LNER developed propensity models to predict when customers were likely to be in-market, allowing them to tailor communications accordingly – or even choose not to send a message at all. 

Early results strongly support the effectiveness of this approach. The team at LNER are now embarking on a test-and-learn process to scale the model and refine its impact. 

  

2. AI and Scale: The Real Challenge 

LNER’s approach aligns closely with our own. Our data science team consistently champions the importance of propensity modelling and personalised lifecycle strategies. It’s how we created the DMA Gold-winning McDonald’s Lifecycle Programme. However, the challenge for many brands is one of scale – not just knowing who to target, but having the capability to deliver relevant, high-quality content across multiple audience segments. It can quickly evolve into a mammoth task. 

I asked Lauren the question, ‘How do you create enough segmented content without overwhelming your teams?‘  

Her response was spot on. First, utilise all available data feeds – pricing data, customer search behaviour, local events – to ensure messaging remains dynamic and relevant. Then, leverage AI-powered tools to streamline content curation and personalisation. 

 

3. AI: Essential but not the starting point 

AI can sometimes feel paradoxical: both an urgent necessity and a distant, complex investment. But the fundamental principles remain the same: 

• Start with a clear customer or business problem.
• Identify what data and processes can address it.

 Only then, explore how AI might enhance the solution. 

AI is a powerful enabler, but it needs the right input and context to deliver value. Simply adopting AI without aligning it to clear business objectives will lead to underwhelming results. The real opportunity lies in balancing efficiency and effectiveness, ensuring AI doesn’t just save time, but also improves customer experience and benefits businesses.