Transforming the 5 common types of personalisation with ‘Private Personalisation’
Marketing has hailed Personalisation (or Personalization if you’re in the US 😉) as ‘the future of Marketing’ for decades now. It promises to enable businesses to develop intimate, one-to-one connections with their consumers, enhancing their experience, and driving loyalty.
Central to personalisation is its reliance on personal information. This is problematic as consumers grow concerned about abuses. As a result personal data regulations are multiplying, while Big Tech clamps down on cookies and tracking outside of their own silos. Therefore, we have a paradox; while people expect more and better personalisation, the human data required to provide it is hard to access and increasingly risky to handle.
However, with advances in technology, a new possibility has emerged: Private Personalisation. It’s a solution that leverages personal data stores, zero party data, and personal AI (Artificial Intelligence).
The powerful combination of these three elements addresses the challenges inherent to traditional of personalisation. These types of personalisation can be classified as ‘Privately Personal’: segmentation-based; behavioural; contextual; collaborative; and journey-based personalisation.
The Core of Private Personalisation
Before diving more deeply into how Private Personalisation addresses these five classic types of personalisation, it’s crucial to understand its three components:
- Personal Data Stores (PDS): These are secure digital spaces where consumers can store, manage, and share their personal data. The individual maintains control, giving them the power to share what they choose with whom they choose. Importantly, the data must be stored in the individual’s own domain, such as on their own smartphone, and backed up in a private ‘personal cloud’. At DataSapien we use a combination of in app wallets, data vaults and personal cloud storage.
- Zero Party Data: This is information that a customer willingly and proactively shares with a brand. Unlike first-party data collected from behaviour or interactions, zero party data comes directly and explicitly from the consumer. Until now this has been limited to surveys, feedback forms, or preference settings. Now, with an individual’s Personal Data Store in place, it flows powerfully and directly from an individual’s own vault of 360º life data. Their digital wallet provides proofs and receipts. This enables digital participation through private sharing, in real time and with full control and consent.
- Personal AI: Personal AI involves using a number of tools (rules engines, algorithmic models, machine learning algorithms and GPTs) to learn individual preferences, behaviours, and needs. It’s AI that is personalised to the individual, which can then be used to curate highly personalised experiences. True, private, personal AI requires the algorithm to be deployed locally with an individual’s personal data (rather than forcing all the sensitive, vulnerable, and fragile human life data to travel to a centralised AI). Local intelligence remains always-on, everywhere, regardless of any connectivity issues.
Private Personalisation is a catalyst that upgrades traditional methods of personalisation. Five examples follow:
1. Empowering Segmentation-Based personalisation
Private personalisation can enhance segmentation-based personalisation by offering far more accurate data points. Traditional segmentation is based on self-reported answers to survey ‘golden questions’ and narrow behaviours. As users share information through personal data stores and zero party data, marketers gain a more precise understanding of their customers, allowing them to create more effective, dynamic and well targeted segments. These may even be extended to form contextual segments, changing based on the in-the-moment need state of the customer.
2. Reinventing Behavioural personalisation
Through the lens of Private Personalisation, behavioural personalisation evolves into a more transparent and consumer-friendly process. Personal AI can learn from consumer behaviour in real-time, while personal data stores and zero party data provide context and depth, offering a holistic view of each customer’s preferences, behaviours, and needs. What jobs does the customer regularly need the brands help to solve for. Which jobs are most important, most urgent, and most valuable?
3. Contextual personalisation with an Edge
Private Personalisation provides a deeper layer of context. Alongside device type or location, personal AI can factor in individual preferences and real-time behaviour to provide relevant content, products, or services, while on device zero party data ensures that the context is updated with the most recent customer insights. Deploying on the ‘edge’ (on people’s own devices) means that data is collected, and insights are created, as close as possible to real, lived behaviours that then drive personalisation. Local processing also makes it far easier to do so in a way that is confidential and private to the customer, instilling trust.
4. Revolutionising Collaborative personalisation
The integration of Private Personalisation in a collaborative context means businesses can provide “customers who bought this also bought…” recommendations, but with an added layer of individual specificity. The predictions are based not just on what similar customers did, but on the specific customer’s shared preferences or behaviours, in context.
5. Journey-Based personalisation Reimagined
Finally, journey-based personalisation can be greatly improved by personal AI, as it can continuously learn and adapt to the evolving customer journey. Personal data stores with owned zero party data, on the other hand, ensure that customer insights used to personalise the journey are always updated and accurate.
With its emphasis on transparency, customer control, and individual insights, Private Personalisation marks a new era in customer engagement. It promises not just to improve but to revolutionise the existing types of personalisation. It provides businesses with an advanced tool to better serve their customers, and granting customers the control they desire over their personal data.
As we move further into the digital age, it is becoming clear that Private Personalisation is the future of customer engagement. It will finally unlock the potential of hyper-personalisation and micro-personalisation to create what we call Omni-Personal Marketing. This is marketing that is entirely human-centric that creates better outcomes for customers and the businesses that successfully serve them.
The DataSapien platform is a modular platform that combines Personal Data Stores, Zero Party Data and Personal AI in an advanced Human Data ecosystem that augments a business’s existing customer data stack.
