Hyper-personalisation – Part 1
Welcome to the first of our THINK-IN Vol. 1 outputs.
On March 24th, we gathered at the Visa Innovation Centre in London for THINK-IN Vol. 1 – Mobility Payments, an exclusive, invite-only event hosted by Attenda in partnership with Visa, Worldpay, and Connected Kerb.
But this wasn’t your typical industry panel or keynote affair.
THINK-IN was designed to break away from the polished presentations and get straight to the raw, unfiltered conversations that matter most. We brought together disruptors, visionaries, and creatives from across the mobility and payments space to rethink what’s next—and more importantly, how we get there.
To push boundaries even further, we enlisted the help of AI as a creative partner, using it to generate and refine insights across four key focus areas:
Hyper-personalisation – How can we deliver seamless, personalised experiences without crossing the line on privacy and ethics?
Vehicle-to-Grid (V2G) – Can EVs become a two-way energy asset, not just a transport solution?
Synced Services – What does it take to truly integrate payments, transport, and digital services into one cohesive user experience?
Mobility & Convenience Hubs – How do we design real-world spaces that match the flexibility and intelligence of digital infrastructure?
Each theme was explored in collaborative breakout sessions, with AI helping to shape provocations, summarise group ideas.
Starting today with Hyper-personalisation, we’ll be sharing a series of posts unpacking each of these topics.
Let’s get into it.
Hyper-personalisation Group 1
What is the biggest problem with hyper personalisation? Hyper-personalisation is a powerful tool, but it comes with some critical challenges. Here are the three biggest problems:
Privacy & Data Ethics
Hyper-personalization relies on vast amounts of user data, often collected through various digital touchpoints. The problem? Users are becoming increasingly aware of data privacy concerns. Regulations like GDPR and CCPA restrict how companies can collect and use this data. If personalisation feels invasive—like when an ad appears right after a private conversation—users might feel uncomfortable or even violated.
🔹 Strategic Fix: Shift towards privacy-first personalisation using zero-party data (data willingly shared by users) and AI-driven anonymisation to enhance relevance without overstepping boundaries.
The “Filter Bubble” Effect
When personalization is too extreme, it can trap users in a self-reinforcing loop—showing them only what aligns with past behavior, limiting exposure to new products, services, or ideas. This reduces discovery, innovation, and engagement over time.
🔹 Strategic Fix: Introduce controlled randomness in recommendations, A/B test serendipity, and allow users to fine-tune their personalisation settings, giving them control over how much personalization they actually want.
Scalability & Cost vs. ROI
The deeper the personalization, the more expensive and complex it gets—especially for companies with limited resources. Maintaining AI models, real-time data processing, and personalisation algorithms requires significant investment. But if personalization doesn’t convert into higher revenue, the ROI might not justify the cost.
🔹 Strategic Fix: Use AI-driven automation to scale personalization efficiently and focus on high-impact personalisation areas (e.g., payments and checkout experience in mobility services) rather than over-personalising everything.
Which challenge do you think is the most critical? Let’s turn one of these insights into a compelling LinkedIn post. 🚀
Here’s a LinkedIn post tackling the privacy & data ethics challenge in hyper-personalisation.
Are we crossing the line with hyper-personalisation?
Personalisation should feel like a helpful concierge, not a digital stalker. But let’s be real—many brands are overstepping.
🚨 Users don’t want to feel watched.
🚨 They want relevance, not surveillance.
🚨 And regulators are tightening the screws.
Hyper-personalisation is built on data. But when does “helpful” turn into creepy? When an ad pops up seconds after a private conversation? When a mobility app tracks every move to suggest rides?
🔹 Data privacy is not an afterthought—it’s the battleground.
🔹 GDPR, CCPA, and AI regulations are here to change the game.
🔹 The future? Zero-party data, AI-driven anonymisation, and transparency.
💡 The brands that win will be those who get personal without being invasive.
Where’s the balance between relevance and respect? Let’s discuss. 👇
#mobilitypayments #hyperpersonalisation #privacy #AI
(This post was AI-generated.)
Now, let’s create a visual to match:
A grayscale futuristic cityscape with neon orange/yellow highlights, symbolizing digital data. A person walking, with subtle glowing “data trails” following them—representing data tracking.
