Why personalisation is so difficult.

Personalisation requires more than good intentions and technology investments. Here are key reasons why many companies struggle:

Measurement challenges: Identifying the right success metrics and avoiding false positives is a persistent challenge.

Disconnected tech stacks: Many organisations have powerful tools—CRMs, marketing clouds, and data platforms—but fail to integrate them effectively.

Content complexity: Personalisation exponentially increases the need for tailored content across various segments, channels, and contexts.

Change management: Personalisation demands cultural and operational shifts, which can be difficult to implement across teams and stakeholders.

The four layers of personalisation.

To get personalisation right, companies must focus on four fundamental layers:

1. Who.
   Define your segmentation and cohort strategy. Are you targeting based on demographics, preferences, or behaviours?
2. When.
   Decide whether to personalise at planned moments (like a product launch) or triggered moments (based on real-time actions).
3. Where.
   Determine which channels or touchpoints will deliver personalised experiences, from email campaigns to in-store interactions.
4. What.
   Identify what you’re personalising—content, offers, product recommendations, or messaging tone.

Mastering these layers requires aligning technology, data, and creative processes to ensure consistency and relevance across the customer journey.

The content challenge: frameworks and automation.

One of the most daunting aspects of personalisation is content production. As brands move from one-to-many to one-to-few and one-to-one communication, the demand for highly specific content grows exponentially. To overcome this, enterprise marketers must:

• Develop clear frameworks: Establish guidelines for messaging, imagery, and tone that align with personalisation goals.
• Leverage automation: Use AI-powered tools to scale content production and delivery while maintaining quality.

Automation not only reduces the manual workload but also enables marketers to focus on strategy and optimisation rather than execution.

Success metrics: measuring what matters.

Personalisation efforts should be guided by a clear hierarchy of success metrics. Here’s how to approach it:

• Avoid false positives: Misinterpreting data—such as assuming first-name usage is ineffective—can lead to flawed strategies.
• Incentivisation of KPIs: Focus on metrics that reflect the broader business goals rather than just immediate performance (e.g., open rates).
• Brand impact: Balance performance-driven metrics with qualitative measures that reflect how personalisation enhances brand perception.

Ultimately, personalisation should create value for the customer and the brand, driving engagement and loyalty in the long term.

The future of personalisation: optimisation and federation.

As personalisation technology evolves, the next frontier lies in optimisation and federated data models. Imagine seamlessly integrating first-party data, neural networks, and predictive analytics to deliver hyper-relevant experiences in real time. This approach requires:

Dynamic feedback loops: Use real-time feedback from users to refine personalisation strategies and remove friction from their experiences.

One key takeaway.

Good personalisation is equal parts art and science. You need the right technology, robust processes, and engaging creative – all built on a deep understanding of who your customers are as real, individual people with unique needs. And while no single brand has brought it all together yet, the journey toward better personalisation is worth taking. 

By aligning customer data, strategy, content, and automation, enterprise marketers can move beyond fragmented and frustrating engagement efforts to deliver on personalisation’s full potential – with transformative experiences that are both relevant and remarkable.