Back in 2015 – pretty much the dark ages in terms of digital – I stood up at Social Media Week in Copenhagen and made a prediction: that in a few years, every time we as customers interacted with a brand, it’d be on a highly personalised level, informed by transactional, behavioural, attitudinal, contextual, and all sorts of other data.
(I had a whole riff on digital being able to deliver the same sort of comforting familiarity as a local Danish shopkeeper – to the mostly bemused looks of the audience.)
The personalisation promise unfulfilled
Anyway, while my predictions at the time were informed by the advances in data engineering and the increasing sophistication of DXPs such as Optimizely, clearly I got it catastrophically wrong. Because ten years later, while data engineering and the sophistication of DXPs have indeed massively advanced, brands still aren’t really delivering on the promise of personalisation.
Think about it: how often does an interaction with a brand feel genuinely personal – not the sledgehammer of segmentation, but something unique and valuable to you?
So, why this collective failure?
Why ambition alone isn't enough
To begin with, it’s not due to a lack of ambition. Two years after my doomed Social Media Week presentation, Keith Weed, CMO of Unilever at the time, said this, “At Unilever we have an ambition to have a billion one-to-one relationships.”
What he meant was that with a supercomputer (i.e. a smartphone) in everyone’s pocket, customer behaviour is driven by micro-moments of need. If a brand can anticipate and assist with those needs with personal, relevant content, it becomes incredibly powerful.
The demand is clear
The demand is also there: according to this McKinsey report, 71 per cent of online customers expect personalisation, and 76 per cent are frustrated when it isn’t delivered.
The challenge is that brands were typically built for the masses and this shift to the personal is a huge one for them: culturally, philosophically, organisationally. And it’s difficult – aligning massive, disparate data sets into a single customer view and being able to leverage insights into relevant personal experiences for customers is no small task.
Moreover, poor data quality and the sheer complexity of integrating emerging technologies further impede accurate and scalable personalisation efforts.
Overcoming the hurdles
How do brands overcome these hurdles, and crucially, where should they start? Here are some pointers:
- Start with unified customer data: Creating a robust 'single customer view' (SCV) is the foundational first step. This means consolidating data from all channels into a central Customer Data Platform (CDP), prioritising first-party and zero-party data for richer, more reliable insights.
- Define clear strategic goals: Personalisation must be tied directly to strategic business objectives and quantifiable revenue metrics, not just vanity metrics.
- Begin small and iterate: Instead of attempting a 'big bang,' start with a specific segment or a single touchpoint in the customer journey, test, learn, and then scale.
- Embrace AI and automation: Let AI do the heavy lifting for segmentation, recommendations, and content creation, freeing up human marketers for strategic tasks.
- Foster cross-functional collaboration: Break down internal silos. Marketing, sales, and IT teams must work from the same data and insights to ensure consistent, personalised experiences across all channels.
- Prioritise privacy and trust: Be transparent about data usage and empower customers with control over their data preferences.
So, how can developments in the Optimizely DXP specifically help? Optimizely, now recognised as a leader in both Gartner’s 2025 Magic Quadrant for DXP and for Personalisation Engines, is at the forefront of enabling this shift.
- AI-Powered Digital Experiences (OPAL AI): Optimizely’s Opal AI is central to its 2025 strategy, bringing advanced automation to content creation, personalisation, and experimentation. It automates repetitive tasks, generates brand-aligned content, and offers AI-driven insights to optimise engagement. Features like Personalization Advisor and Opal Chat assist marketers in real-time, even summarising A/B test results in plain language.
- Unified Data & Personalisation: Optimizely Data Platform (ODP) is crucial here, unifying first-party customer data into single profiles and enabling real-time segment activation for hyper-personalisation across channels. The DXP leverages real-time segments to create highly personalised experiences.
- Advanced Experimentation: Optimizely’s deep roots in experimentation are now fully integrated across the DXP. Its Web Experimentation platform, enhanced with warehouse-native analytics, allows for seamless testing and optimisation, connecting experiment results directly to business metrics without data duplication. This empowers continuous UX improvement.
- Content Management Evolution & Visual Builder: The Optimizely CMS, with its SaaS and PaaS options, has evolved significantly. The new Visual Builder empowers marketers to create dynamic content with drag-and-drop simplicity and interactive previews, removing technical barriers and accelerating content creation. This enables rapid content iteration for personalisation campaigns.
- Optimizely One: This unified platform combines content management, commerce, experimentation, and AI-driven personalisation into a single, AI-accelerated workflow. It’s the operating system for marketers, offering composable flexibility to integrate with existing stacks while powering every stage of the marketing lifecycle.
The missing piece, then, is not the capability of personalisation, but the brave and strategic embrace of unified data, AI-powered tools, and cross-functional collaboration to deliver genuinely personal experiences at scale.
The promise is finally within reach for marketers.
