Once upon a time, businesses targeted broad messages at broad audiences, aiming for “everyone” as their target. Today, customers do not care about generic outreach. They expect more. Today, brands are no longer targeting segments; they’re targeting individuals.
That shift didn’t happen overnight, but it has arrived. The key idea is that when a business embeds the quality of one-to-one customer experience, it taps into greater connections and loyalty, and can grow faster in the process.
The Move From Mass Marketing to Precision Business Models
There was a time when businesses used generic messages, hoping they would reach the right people. It’s 2025, and that scattershot approach no longer works. Every search, click, and subscription reveals individual habits, allowing companies to provide tailor-made experiences. Across industries, hyper-personalization has become the foundation of more innovative and responsive business models.
In retail, brands such as Nike and Sephora use the browsing history and wish-list activity to make customised product suggestions. Streaming platforms like Netflix react to what viewers started, skipped, or finished their content in real-time, and learn more from each action.
The gambling industry follows a similar path. Platforms analyze player interactions, the bonuses claimed, and which games are kept for the longest period of time. For example, through PokerScout Insights, users are directed to the most reliable gambling sites based on their actual preferences. The platform reviews factors such as bonuses, software, payouts, and the range of real money fish table games, where players compete to shoot fish, crabs, and other sea creatures to rack up points and cash rewards.
Finance and healthcare exhibit similar trends. Digital banks, such as Revolut, use transaction data to create personalised financial advice, while online clinics use a patient’s past medical history to create a wellbeing plan.
What unites these sectors is a common understanding of the role that personal data plays: no longer is it a record of behavior, but personal data is the roadmap to creating relevance. Businesses that can adapt to what people really search for, use, and enjoy are the ones building long-term connections in a market where precision, not noise, is rewarded.
The Economic Sense of Hyper-Personalisation
Here’s the bottom line: Hyper-personalisation drives business value. When you make experiences meaningful in a way tailored to customers, they respond. For example:
- Around 80 percent of consumers report that they are more likely to purchase from companies that provide customized experiences.
- The global hyper-personalization marketis projected to grow at an annual rate of 18 percent, from approximately US$21.8 billion in 2024 to US$25.7 billion in 2025.
- Although there is a significant investment in personalisation among businesses, only around 35% of them are providing fully personalised experiences across all channels. The gap presents an important opportunity.
Bottom line, if done right, hyper-personalization will be a growth engine, not just a marketing add-on.
The Technology Stack Behind Powering It
To create personalised experiences, businesses require more than goodwill; they need technology. Key components:
- AI / Machine Learning: algorithms for parsing behaviour, predicting next moves, and serving dynamic content. For example, brands that employ an AI-powered recommendation engine experience major uplifts.
- Unified Data Platforms / CDPs: to tie together mobile, web, in-store, app behaviours such that each customer is a “profile” rather than a silo.
- Real-Time Contextualisation: providing the right message at the right time, right place, right time of day, recently done. Without this, personalisation is stale.
In short, technology is the scaffolding that enables the transformation of personalisation from promise to performance.
From Data Collection to Interpretation of Data
Capturing data is easy. Making it work is the tricky part. In fact, by 2025, the most innovative businesses will have shifted from “we have data” to “we interpret data.” They ask the question: What does this customer want next? What pain point do they have? And how can we respond before they have even asked?
Some key shifts:
- Zero-party data (customers telling you willingly what they like and don’t like) becomes greater as cookie-based tracking dies.
- Transparency and trust are no longer optional: consumers want to know if you’re using their data with care.
When you interpret instead of simply collecting, you transform data into insight, and insight into involvement.
Customer Experience Flywheel
Hyper-personalisation is not a one-off tactic. It becomes a self-reinforcing cycle:
- You provide an experience that is specific to the person →
- They engage more, stay longer, and provide you with more data →
- You use that extra data to serve even better experiences →
The cycle repeats, adding on cumulative value.
For businesses that use this flywheel, growth is organic. You’re not chasing customers; they’re gravitating to you.
Challenges & Tensions of Ethics
We need to appreciate the flip side of this. The risk associated with hyper-personalisation:
- Data privacy concerns: Customers may feel uncomfortable if they believe a brand knows too much about them. A balance is essential.
- Execution complexity: Only a minority of businesses deliver complete personalisation across channels; many are still behind.
- Algorithmic bias: Assuming the accuracy of an input-skewed dataset, you can provide skewed recommendations or even offend.
Actual growth occurs when personalization is done responsibly, with trust, ethics, and transparency being integral to the process.
