Today’s consumers expect their content experiences to be relevant to them. In practice, that often means some degree of personalisation or customisation. In our recent study, Next Gen News, Kirsten Eddy (a member of our Advisory Board) explained that “What really draws people to TikTok is its algorithm. Even if the users don't understand it, there is very clearly a desire to be a part of an environment that knows them so well and that will automatically predict what they like.”
Such a statement suggests that the algorithmic selection offered by social platforms is what gives them such utility. To date, few content businesses (perhaps aside from Netflix and a handful of others) have been able to compete with the curated experiences offered by companies such as Instagram or TikTok. However, audiences are not unanimously in favour of algorithmic personalisation – especially when it comes to news and information. During a recent focus group, we heard how audiences want content to ‘open their mind, not send them down another rabbit hole’.
So how do news and information providers create relevant experiences without creating echo chambers?
From our perspective, it is first important to draw a line between the two different forms of tailored experience:
- Customisation: where audiences take control of their experience by defining what they want, whether that’s specific topics, genres, formats or goods. This will often involve either voluntarily sharing information (e.g. topics of interest) or actively changing settings/parameters to create something that matches their tastes (e.g. building your own custom feed on Bluesky).
- Algorithmic Personalisation: where organisations take control of personalising the experience on the user's behalf. This will typically involve using a wide variety of data collected either via forms (e.g. age, gender, location), analytics tools (e.g. consumption habits and devices) or inferred (e.g. interests).
In this blog series, we will explore both, starting with customisation, and discuss what they might mean for news and information producers. We will also examine how Generative AI is changing the ease with which these organisations can offer tailored experiences.
Topic Selection
The first example of customised content experiences is topic selection. A notable example of topic selection is myFT from the Financial Times. This tool allows users to follow topics that interest them. Based on the selection, readers can access a tailored area of the FT and receive an automated email digest based on their selected topics. Our findings show that MyFT is one of the FT’s strongest engagement drivers. Although topic selection is not new, it is an extremely valuable and proven customisation tool for audiences.
Chatbots
The emergence of Gen AI interfaces (commonly referred to as Chatbots) has offered a more flexible way for audiences to express their intent and content preferences. Rather than users providing data at a single point in time (e.g. at sign-up), they can continually interact with an interface that provides more bespoke recommendations and answers over time. In addition, responses are not static; additional prompting can allow users to define an answer's length, tone and format.
In our experience, many media organisations are experimenting with chatbots that address a specific user need or topic vertical (as opposed to being general use), for example:
- TIME magazine recently launched an AI-powered chatbot designed to answer questions about TIME’s Person of the Year. In addition to using the chatbot, readers can also summarise the article, listen to the audio version, and engage in voice conversations.
- The Washington Post's chatbot answers queries regarding climate issues, personalising certain questions and responses and leveraging its article archive to help address these needs. The Post also utilises the tool to collect user data, learn trends and understand the most common topics of interest that were able to help editorial reshape their content.
Format adaptation
AI is also transforming format experiences for audiences. In many ways, we are seeing a transition from the format being determined by the content producer to being decided by the audience member. For example, AI has been used by news organisations to offer up articles in audio format using Natural Readers. These tools create a dynamic and unique experience, helping younger audiences embrace news in a format they feel is more relatable and approachable.
A related example is BILD, a German news publisher, that uses AI-powered text-to-speech technology to create personalised podcasts. Readers can choose to listen to the news in an AI-generated option in different tones and languages, including English.
Another notable example outside the news landscape comes from the latest version of NotebookLM, where uploaded documents can be transformed into engaging audio discussions with a single click. It will be interesting to see whether content businesses could develop this format adaptation themselves or rely on third-party vendors.
So what?
There are a few important takeaways from this article:
- Personalisation and customisation are not the same thing – many newsrooms and audiences are understandably concerned with algorithmic personalisation. We often have to manage such resistance for change on our project projects. However, that shouldn’t mean that all tailored experiences are off the table, and in fact, customisation seems to be an important direction of travel to keep audiences happy.
- Tailored experiences are a necessity – there is too much content online and audiences expect filtering tools and relevance. Not everyone will use them, but that doesn’t make them less important.
- Generative AI is handing over control to audiences – they will increasingly be able to determine how they want their content presented to them – both in terms of length, tone as well as format. As Jeremy Gilbert said recently, we are at an inflection point of “living” stories that adapt and recreate themselves – “When a reader selects a story, the length, depth, format or complexity can be changed as they read it. New information is instantly incorporated.”
At FT Strategies, we understand the power of AI, technology & data for future-proofing your business. Our specialist team of consultants have years of experience implementing data models and refining tech stacks to help organisations grow. To find out more about our services, please get in touch with us today.
About the authors
George Montagu, Head of Insights
George is Head of Insights and Senior Manager at FT Strategies. Before this, he spent the last four years guiding the FT’s data strategy as it balances revenue and risk. Most recently, he founded and continues to lead a cross-departmental FT team focused on the future of marketing & advertising in the context of restrictions on online tracking.
Jhanein Geronimo, Insights Associate Consultant
Jhanein is an Insights Consulting Project Associate at FT Strategies that supports the ongoing development of media and subscription expertise. She studied BSBA Corporate Management (Summa Cum Laude) from Assumption College, San Lorenzo.
