In the past decade, the rise of individualisation has marked a significant trend in modern society. This movement toward tailoring products to the unique tastes and needs of individuals has driven growth across many industries.

The demand for personalised experiences in retail, services, empowerment, autonomy, and flexible work arrangements spurred by the pandemic has heightened expectations for products and services. People yearn to stand out, be unique, be different, and be treated as such.

The one-size-fits-all selling approach epitomised by Henry Ford and the Model T — available in any colour you like, as long as it is black — is obsolete. Today, cars offer myriad customisation options, and a buyer can put together a product with an online configurator.

Harnessing digital technology for personalisation

Digital technologies have actively enabled this trend, allowing for intricate customisations across various sectors.

Two drivers are:

1. Digital technologies in production processes that can handle complex configurations and variations.
2. Online systems, where people can configure and visualise the product exactly how they want it by drag and drop. Online configurators for furniture, apparel, footwear, eyewear, kitchen appliances, and even hamburgers enable people to tailor products to their specific preferences and needs. Three-dimensional printing even lets people build their own products at home.

This trend of individualisation not only reshapes retail and other industries but also has an impact on news media, demanding innovative approaches to content delivery.

The state of news media personalisation

Considering this backdrop, how have news media companies embraced this trend?

Most news media companies offer some level of personalisation on digital platforms. People can choose their favourite topics to create their own content feeds. They can also choose a preferred location and sign up for newsletters of interest. “Smart” algorithms provide recommendations for articles from the content pool in a “further reads” section too.

People can also adjust aesthetic preferences like font size or night mode. Some platforms allow people to read articles aloud, and some media houses present a different selection or prioritisation of content based on subscription status.

Personalisation often ends there. It is mainly focused on what is presented. News media continute to offer the same story format to all readers (which is still mainly text) in the same journalistic form (report, analysis, interview, etc.), at the same length, and using the same story structure in the same language and language style.

But there are many other parameters of personalisation that can be used to create an even more personalised experience for each reader, especially considering the why and the how. Imagine customising a newsfeed for a reader not just by topic but based on the situation he or she is at in the moment of the visit or by the kind of day he or she is having.

Motivation and life situation

People have different reasons for consuming content, and this motivation perhaps changes during the day or during different situations in their daily lives.

Sometimes people just want to be quickly informed or updated on events or developments. Sometimes people want things explained, to be educated or inspired, or to find solutions for solving a problem. They may want to be entertained or surprised.

The concept of “user needs,” popularised by the BBC, is increasingly adopted by many news media companies around the world. The BBC’s user needs revolve around tailoring content based on specific audience requirements, which have been identified through extensive research into how people consume media.

It categorises these needs into four main areas:

1. Keeping the audience informed.
2. Providing deeper understanding.
3. Offering new perspectives and stimulating creativity.
4. Providing relaxation and enjoyment.

It attempts to create and manage content accordingly.

For example, the same story about an event can be told as a bullet point list, fact sheet, summary or table, image, or audio bulletin. This could fulfil the need to keep the audience informed.

For provide deeper understanding, the same story can be presented differently. It could take the form of an 800-word article, podcast, or video, for example.

The key is to understand the personal needs at any given moment of the visit and personalise the how, and not only the what. Generative AI (GenAI) and large language models (LLMs) can quickly and cost-effectively create different versions.

Mood management

Another potential new parameter to use for personalisation relates to mood management.

The mood management theory is a concept in media psychology primarily concerned with how individuals use media to influence or regulate their moods. The theory suggests people often seek media that produces a mood opposite to their current negative state (e.g., watching a comedy when sad).

However, it also mentions the concept of semantic affinity, where individuals might select media congruent with their current mood, especially if the mood is positive or when they want to savour certain emotions.

This might seem contradictory, but it reflects the complexity of human emotions and the varying strategies individuals use for mood regulation. Because of this, mood management is more complicated when it comes to personalisation.

Being aware of the different moods a person can have, and adapting the content to reflect these moods and emotional states, can contribute to a more personalised experience.

Simple examples in social media are the option to switch off the visibility of posts with sensitive content on X, hiding offensive words and phrases on Instagram, or using the profanity filter for comments on Facebook.

Going one step further, GenAI and LLMs can help to adapt content quickly and easily in style, language, and wordings to suit an emotional state of a reader, without changing the message of a story. The reader has the choice, and can, for instance, create a “safe space” for him or herself, without resorting to cat videos to avoid distress and missing important news completely.

The challenge of knowing

However, the challenge is to know or recognise what user need to fulfill at any specific time and get the right option in front them at that moment.

This data can be obtained by certain assumptions. For example, in the morning, more informational content and formats might be appropriate, whereas in the evening perhaps more inspirational or educational formats might be better. 

Additionally, direct feedback from readers to a story and signals to the readers that they can influence the experience could be powerful. For example, Tinder-like swiping to express “well done, you met my need” or “nope, did not work,” or any other interaction that can feed the algorithm.

Even if personalisation based on the theory of mood management is complex, the fundamental idea to develop personalisation beyond “suggested reads,” topics, and geography is an important and interesting area to explore.

Next-level personalisation is not optional

Sophisticated personalisation hinges not just on deep empathy for customers and insight into their needs, situations, and moods, but also on a strong data strategy and infrastructure. These systems must seamlessly manage everything from collecting crucial data points to processing and controlling delivery mechanisms nearly in real-time.

While challenges like technological limitations in data processing and algorithm accuracy remain, overcoming them is essential. Advancing toward more personalised news consumption is not optional; it’s imperative.

Embracing innovation in AI will help to align with changing reader expectations. Achieving this balance means the fusion of advanced AI with empathetic design won’t just improve the user experience; it can fundamentally transform the essence of news consumption.

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