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Writer's pictureTeresa Sperti

Next-gen personalisation; the big trends that will change personalisation as we know it

Personalisation: everyone talks about it but few are doing it well. Even though personalisation has been high on the agenda ever since Amazon introduced recommended products all those decades ago and Netflix revolutionised entertainment as we know it, many brands are still struggling to progress past more basic forms of personalisation.  But the industry waits for no one, and the next decade will usher in a new wave of personalisation driven by technological advancement and consumer expectations. Facial recognition, voice, genAI and extended reality are just some of the technological advances that will reshape personalisation, but brands will need to balance their ambitions with consumers' desire for privacy. 


So, what can we expect on the personalisation front over the next decade, we explore the big trends that will usher in what we are calling next-gen personalisation which will require brands to grapple with a whole new set of challenges to deliver to the needs and desires of customers and provide unique opportunities for brands to innovate and differentiate to stand out in increasingly cluttered markets.

 

Hyper-personalisation is all the rage


Any discussion about the future of personalisation cannot be had without exploring hyper-personalisation and the role AI and genAI are playing to enable it.  For many brands, the complexity and cost of delivering one-to-one or one-to-few personalisation has historically been stifled by technological constraints, however, genAI has paved the way, making hyper-personalisation possible. Hyper-personalization leverages traditional AI and genAI to create a one-to-one experience as unique as every customer, by analysing data, leveraging context and developing highly personalised content and assets in real-time to create relevancy for the customer in the moment. 


For brands deploying it, the ability to deliver one-to-one will be a journey as brands move from a broad segment-based approach to many segments and eventually to one-to-one as illustrated by this Telco case study.


A European telecommunications company used gen AI to shift from highly manual, blunt customer outreach messaging to messaging that would more effectively engage with specific segments. Previously, this telco deployed messages to just four macrosegments. With a lean operation, it was constrained by its ability to create copy and creative in a scalable way. The telco built a gen-AI-based engine to create hyper-personalized messaging for 150 specific segments. The engine trained on non-personally identifiable information data to tailor communications to each segment’s demographic, region, dialect, and other attributes. The information was passed to GPT-4 and Dall-E to create copy and imagery, which were then ported into the email service provider via API and prepared for deployment. So in this example, as we can see whilst it is not true one-to-one, the brand has been able to dramatically shift its approach to communication with its customers in a scalable way without the need to scale resources to manage creative execution.

 

Hyper personalisation extends far beyond marketing campaigns


Whilst much of personalisation historically has been focused on improving marketing programs, hyper-personalisation will be deployed as part of customer service interactions and across the journey to treat customers like an individual based on their needs, preferences, tastes and challenges. In fact, according to a recent study, it is anticipated that genAI will most heavily influence how customer support is delivered.  And whilst some may not see this as personalisation, the way it will be executed at an individual level, finally sees personalisation become more embedded in the total customer experience as opposed to residing within marketing communications only.

 

genai delivering hyper personalisation

 

Vodaphone in the UK is one such brand deploying genAI to deliver highly personalised and contextual customer service to best serve their younger demographic.  VOXI’s LLM generative AI chatbot has been developed as part of a wider initiative to accelerate generative AI technologies across both VOXI, Vodafone UK’s mobile offering for people aged 25 and under, and Vodafone. This is enabling Vodafone to go beyond keyword search terms to best serve their customers.  Whilst it seems simple, it delivers a fundamentally different experience for the end user as accuracy and relevance improve.

 


personalisation in chat bots

 

Biometrics powering new forms of personalisation


One of the more controversial shifts we are seeing in the personalisation space is the adoption of biometrics tech and data to enable personalisation.  Biometrics technology, which includes facial recognition, fingerprinting, voice and more is proving to be the most accurate way to identify and authenticate consumers and remove most or all of the friction from within the experience. From healthcare to beauty and fashion through to the travel industry, biometrics tech is ushering in unparalleled one-to-one personalisation through payments, truly one-to-one recommendations, zero friction experiences and more.  Whilst this is not a completely new trend, the adoption of technology like facial recognition and more is becoming mainstream and we are likely to see its deployment become a prominent fixture of experience delivery over the next decade to enable not only security but to personalise the experience in new ways. 


In many Asian countries, facial recognition is already a common way to pay in stores. Yet, “smile to pay” systems have yet to take off in the West, as people are concerned about customer privacy and the risk of identity theft or misuse.  The adoption of facial recognition is said to be deployed already within hundreds of Walgreens and Macy’s stores to experiment and trial with personalised and contextual advertising allowing retailers to monitor shoppers and analyze their emotions so that stores can deliver personalized adverts on screens inside the store. In the travel industry, we are seeing the adoption of facial recognition and other biometrics to create seamless check-in and check-out experiences, provide customised recommendations and more.


Despite the huge advantages however of biometrics, consumers are increasingly wary of this very personal information being captured and stored. According to GetApp’s 2024 Biometric Technologies Survey of 1,000 US consumers, comfort levels with the technology has dropped considerably when sharing:


  • Fingerprints (from 63% in 2022 to 50% in 2024)

  • Face scans (from 44% in 2022 to 33% in 2024)

  • Voice scans (from 34% in 2022 to 20% in 2024)


This is in part as a result of security concerns if that data were to get into the wrong hands, as it is fast becoming the way to verify and authenticate consumers across an array of brand experiences and devices.


biometrics to deliver personalisation

 


The rise of the personalised instore experience


Personalisation is synonymous with retail – however much of the personalisation which within the online and eComm environment as opposed to the physical store where 80%+ of transactions are occurring. The rise and advent of digital screens within an array of retail outlets, the adoption of kiosks and the emergence of VR & AR will all usher in the next wave of innovation to transform the retail and instore experience, all of which create new ways and opportunities to personalise the experience for the shopper and that personalisation often extends right through to the product.


In South Korea, shoppers can now visit a Nike store and personalise their products by exploring an array of physical and digital design elements to customise their products, allowing individuals to create their own products based on their tastes and preferences. However, that is limited to 100 customers a day to manage demand.



Brands are also experimenting with technology to enable better product choices in-store than ever before.  We are seeing technology being deployed to allow customers to select the right make-up based on their skin tone and type, those shopping fashion can see if clothing is right for their body shape and size through virtual try-ons in-store and more.  


Fast forward to 2030 and these and many other one-to-one in-store experiences will be commonplace. In the wellness space, we are likely to see consumers being able to customise their own gym environment enabled via AR & VR; one-to-one menus within restaurants and QSR environments that understand a customer's taste, preferences and mood will be commonplace, and biometrics will enable a user to be recognised and relevant recommendations based on their past behaviours surfaced and much more.

 

Empathy led personalisation


To date, so much of the personalisation consumers receive and interact with is delivered based on transactional or behavioural engagement data. But what happens when we understand how the customer is feeling in the moment of interaction?  The rise and adoption of customer journey mapping and human-centred design has come from the need to build and create more empathy for customers and by doing so enable the delivery of more customer-centric experiences. However much of our personalisation efforts today ignore the emotional side of a customer's journey. Biometrics, voice technologies and conversational engagements through chatbots (where language can be analysed) and others help the brand to better understand the customer's mood in the moment and adopt personalisation that meets them where they are.

 


ai virtual assistant to deliver personalisation

Through the launch of its new AI-powered Mercedes Assist, the Mercedes brand is looking to adopt a more personalised experience for its drivers over time. Ola Källenius, Mercedes-Benz’s CEO, hinted that the AI-powered virtual assistant will "reinvent the digital passenger experience" and that it "includes empathetic characteristics that sync with your driving style and mood," suggesting that the voice assistant can change personality depending on the driving mode selected.


Whilst there are very few brands experimenting in this space, it is one to keep an eye on as technology evolves and makes the impossible possible.

 

 

Privacy centric personalisation


As privacy concerns grow and governments across the globe tighten regulation, both are giving rise to an era of more transparent and user-controlled personalisation. As the tech leaders of Apple, Google and others move towards privacy-protectant approaches and experience delivery, brands will follow suit empowering consumers to be able to better manage their own data and allow them to decide how and when data is utilised. With options to adjust privacy settings and personalize experiences while maintaining privacy, there will be much innovation in the space of privacy-centric personalisation as brands adopt new and more technology to manage consumer privacy and brands grapple with the tension of delivering personalisation and managing privacy.  And that will extend to the utilisation of biometrics data as well. China - a leader in biometrics tracking and facial recognition - has been one of the first to create some boundaries and limit facial recognition technology altogether.


On August 8 2023, via the Cyberspace Administration of China (CAC), China released draft regulations to govern the country’s facial recognition technology, including prohibitions on its use to analyze race or ethnicity. The purpose is to “regulate the application of face recognition technology, protect the rights and interests of personal information, other personal and property rights, maintain social order, and public safety”, as outlined by a combination of data security, personal information, and network law.


 

Arktic Fox is partnering with an array of brands to build and define a strong personalisation strategy. Find out more about how we can partner with you to help you thrive in the digital landscape.

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