Hyper-personalisation to benefit the user

Personalisation in UX is nothing new and is placed front and centre in many digital experiences, from Daily Mixes on Spotify to geo-targeting adverts. So, why am I choosing to write about it now?

Advances in artificial intelligence (AI), machine learning and real-time data are gradually paving the way for hyper-personalisation, which places a greater focus on the behaviours and preferences of individuals, leading to highly tailored experiences. As we start to see more of this, I decided to delve deeper into whether personalised experiences always benefit the user, or if in some cases, the drawbacks outweigh the advantages.

Reduced workload vs. Limited discovery

Personalisation can mean increased convenience and efficiency for the user, as content of interest is prioritised resulting in less navigation with higher reward. Sometimes users can be presented with choice overload (a feeling I’m sure many of us have experienced), which makes it difficult to make decisions and results in feelings including overwhelm, disengagement, or regret.

Offering navigation that is tailored to a user’s affinity and preferences streamlines the work involved to discover content, as it is located higher in the information architecture – think the ‘Because you watched Stranger Things’ row on Netflix. Yet, offering the right degree of navigational personalisation in different contexts can be tricky, as you risk placing users in a bubble with little opportunity for discovery.

When users are only shown content from a niche area of interest, there is ultimately less variety to explore and excite them. As a result, they are likely to become fatigued, leading to decreased engagement with the service, as they seek a more meaningful experience elsewhere. Pretty detrimental for the provider! To prevent over-personalisation in an experience, the curation of content should be carefully balanced against user needs identified through research.

Surprise and delight vs. Privacy concerns

A tailored user experience demonstrates that a business understands each of their customers as an individual, therefore making them feel appreciated and special. This sense of identity helps to drive loyalty by forming what feels like a personal relationship, much like going into a restaurant and receiving your favourite drink without asking (probably a rarity for most of us). However, it wouldn’t feel so special if that happened every time, right?

Hyper-personalisation offers the opportunity for businesses to put more thought into subtle surprise and delight moments for customers. This can be achieved by considering individual motivations and actions, as well as thinking outside the box. For example, spare appointments for a specific service (e.g. haircut) could be discounted for customers whose previous behaviour aligns with the appointment time, location and provider (e.g. stylist), but who have not engaged with the service for a while. This could be achieved using algorithms within the booking system.

On the other hand, these types of experiences are likely to rely on highly individual data which may raise privacy concerns. Whilst we all know that companies record and share data, it can still be unnerving when you get the feeling someone has been listening in on your conversations or tracking where you’ve been. For the current generation this is only human, and there are still boundaries that should be respected when attempting to surprise and delight customers. The easiest way to identify these boundaries is to engage with your users, whilst always providing transparent information about how data will be used.

Omnichannel experience vs. Inaccurate assumptions

In most cases, a user’s journey with a brand or service is likely to span across multiple channels, be it on an app, in store, or with digital advertising. Omnichannel personalisation is focused on understanding user behaviours and providing a consistent, bespoke experience across all touchpoints. This relies on data being recorded and consolidated in a centralised location, where it can provide a 360-degree view of each individual.

Implementing an omnichannel approach allows a customer to fluidly transition between touchpoints, knowing that relevant content and support will be offered in each context, in line with their preferences. For example, when walking into a shop face recognition could be used to direct you to recommended products, perhaps using digital signage, based on your interactions online. This would take away the hassle of remembering and locating products of interest.

As great as it sounds, combining and interpreting data from different touchpoints is a challenge, and most businesses still have a way to go – I’m sure I’m not alone in being shown adverts for products that I have already bought or even sent back! Inaccurate assumptions can be caused by using out-of-date information, siloed data, or failing to record or consider previous interactions altogether, and are likely to lead to a negative user experience. To prevent this, it is essential to build a robust real-time dataset, before developing and testing personalised solutions with users.

Conclusion

Whilst personalisation is now an expectation rather than a nice to have, hyper-personalisation needs further grounding in user research and analytics to ensure that it benefits both businesses and their customers. Here’s a few tips to get you started…

1. Identify user needs: Carry out user research to determine the level of personalisation that supports users with their goals. Sometimes, less is more, and dependent on the context, natural discovery may be an important part of the user experience too!
2. Be authentic: Try to get close to each customer and their preferences on an individual level, rather than relying on analytics from large market segments. Meanwhile, stay mindful of user boundaries and concerns, using research insight to inform areas to avoid.
3. Integrate effortlessly: Slot personalisation into existing experiences so that it optimises the current user journey, rather than appearing like an add-on. It should be there when needed by the customer, but invisible when it isn’t.
4. Learn from ongoing interactions: Recognise when a personalised experience isn’t working and attempt to understand why. This insight can be used to optimise back-end algorithms to improve future interactions.