Why Brands Struggle with Hyper-Personalisation (And How to Get It Right)

In a world where your coffee app knows your Monday mood better than your therapist, and your favorite clothing brand seems to predict your seasonal fashion crisis before you do, it’s easy to believe we’ve nailed hyper-personalisation. But behind your name in bold in all those push notifications, the truth remains that brands are still struggling with the personalisation game—some might say they are shooting in the dark.

Despite AI advancements and an overload of data, hyper-personalisation seems like a far-fetched goal. From campaigns that are way too personal (and on the border to creepy) to data silos that hinder a 360 degree unified view of the customer, brands are realising hyper-personalisation to be a tougher nut to crack than they thought it would be. 

So what is getting in the way? 

Why Hyper-Personalisation Isn’t Living Up to the Hype

Brands are investing heavily—financially, technologically, and creatively—to tailor experiences with laser precision. Yet, more often than not, the results fall flat, veering into the generic, the awkward, or worse, the downright intrusive. There is ambition well-laid out but the execution seems to be failing. 

The key to success lies not just in having mountains of data or the latest tech—but in knowing how to actually use them. Here’s a breakdown of the most common pitfalls and how smart brands are navigating around them:

Data Silos, Fragmented Experiences

Data buckets coming in from multiple sources like offline channels, email platforms, CRM dashboards, and social media, are siloed in nature and don’t interact with each other. This makes a fragmented view of the customer (opposed to a unified view which is required), making seamless personalisation impossible.

The solution is to invest in unified customer data platforms (CDPs) that consolidate information from multiple touchpoints. Businesses must also foster cross-functional teams that ensure insights are shared—and acted on—in real time.

Privacy Laws and Trust 

Consumers are increasingly aware of their rights over information, and with privacy regulations like GDPR in place, personalisation has become a tricky business. On one side is relevance and customisation, while on the other is intrusiveness that feels creepy. Even the slightest of detours to the wrong side can lead to a loss in customer trust. 

The most efficient and proven way to resolve this challenge is to enable complete transparency with your customers—use opt-ins and consent forms to let your customers know where and how you will use their data. Shifting from a ‘data grab’ approach to a “value exchange” approach will make your customers feel at ease about sharing their personal data. 

Overload of Technology, Inefficient Planning

New technology is bombarding marketers everyday, making it a puzzle to pick what works for their business. In the fear of losing out, or in an attempt to leverage everything, marketers end up adding a number of new tech to their martech stacks but fail at efficient integration. Such a martech stack offers less value and generates more martech waste. 

Innovation isn’t about how much tech you have—it’s about how smartly you use it. Marketers must streamline their tech ecosystem, focus on interoperability, and choose platforms that play well together.

Metrics that Don’t Work

Many brands still measure success with outdated KPIs like last-click attribution or generic open rates that don’t reflect the nuance of personalised journeys. This one-size-fits-all approach doesn’t work for measuring the degree of personalisation.

The solution is to adopt more granular metrics like customer lifetime value, engagement depth, or micro-conversion rates, that align with personalised experiences. For personalisation to be measured effectively, analytics must match.

Content Bottlenecks

Content is the root that holds personalisation together. For a single personalised experience, brands must provide tons of content. This could include visuals, language, tone, etc., all in different formats for different channels. Managing all of this content can be overwhelming.

For marketers to not get lost in the content maze, they can opt for modular content strategies and dynamic content assembly, supported by AI-driven tools that can help automate and scale personalisation without burning out your creative team.

Closing the Gap Between Promise and Practice

The brands that succeed with hyper-personalisation aren’t necessarily the ones with the biggest budgets or the flashiest tech—they’re the ones that rethink their approach, break down internal walls, and keep the customer (not just the data) at the centre of their strategy.