Five Key Findings

^{Five Key Findings from the Report}

01 | Personalisation has evolved from a marketing tactic into a business capability

Effective personalisation now reaches far beyond targeted campaigns or product recommendations. It requires coordinated investment in customer data, journey orchestration, AI, privacy, governance, and measurement – a cross-functional capability spanning marketing, CRM, digital, data, and technology teams.

02 | AI has solved scale; it has not solved trust

AI has dramatically accelerated organisations' ability to personalise at scale. But the question has shifted from whether brands can personalise to whether they should. The organisations pulling ahead are placing as much emphasis on governance and transparency as on automation and efficiency.

03 | First-party data is becoming the foundation of competitive advantage

As third-party cookies decline and privacy expectations rise, customer data platforms, consent management, segmentation, and journey orchestration are no longer standalone initiatives. They are becoming the essential infrastructure of personalisation itself.

^{Five Key Findings from the Report}

04 | Customer expectations continue to climb

Consumers compare every digital experience against the best one they have ever had, anywhere. Relevance, consistency, speed, and convenience are expected at every touchpoint. Generic messaging is ignored – and poorly executed personalisation erodes trust as quickly as good personalisation builds it.

05 | Success will be defined by organisational maturity, not technology alone

The organisations making the greatest progress are not simply buying more tools. They are building the capability to combine customer insight, responsible data practice, AI, and commercial strategy into one coherent approach to customer engagement.

Questions Every Marketing Leader Should Be Asking

Does our organisation have a shared definition of personalisation?
Are we creating experiences customers genuinely value, or just increasing the volume of personalised messages?
Can we clearly explain to customers how and why we use their data?
Are we measuring the commercial impact of personalisation, or only campaign performance?
Is our first-party data strategy capable of supporting long-term growth?
Are our AI initiatives improving customer experience, or simply increasing operational efficiency?
As customers increasingly interact through AI assistants, how should our personalisation strategy evolve?