Before you automate, ask yourself: is your brand ready for relevance at scale?  From value propositions to content maturity and data hygiene, there are four critical gaps that derail even the best-laid personalisation plans.

Personalisation is one of the biggest buzzwords and has been for years. It’s the silver bullet everyone wants to fire. So it’s no surprise if your CEO drops the classic line:
“How far are we with it?”

While the question is fair, it should immediately spark a series of follow-ups:
What kind of personalisation? For what purpose? In which channels?
In Hello $Firstname, we argue that there’s no one-size-fits-all answer – personalisation must be designed with intent, not just urgency.

Reports like McKinsey’s Next in Personalisation (2021) claim a 20–30% revenue uplift is within reach if done right. But like any gold rush, it’s easy to forget what can go wrong. And trust me – I’ve seen plenty of projects fail. Through my work as a consultant, CXO at Agillic, and author of Make it All About Me and Hello $Firstname, I’ve come to recognise the recurring culprits.

Let’s explore the four most common pitfalls that should be addressed before you double down.

1. Broken Value Proposition? No Amount of Personalisation Will Fix That

It doesn’t matter how slick your segmentation or dynamic content is – if your product–market fit is weak, personalisation becomes lipstick on a pig. If you’re sourcing the wrong products, pricing them too high, or targeting the wrong audience, personalisation might help a little… but not enough. You can’t decorate a failing business model with 1:1 messages and expect magic.

Make sure the basics are solid: Do customers love what you offer? Is there organic demand? Are your reviews and referrals telling a good story?

2. No Brand Demand? Start by Talking About Yourself

Personalisation only works when there’s something to personalise from – like traffic, clicks, or customer signals. But if your brand isn’t known, you won’t have that. No awareness means no demand. And no demand means no data.

At this stage, it’s too early to focus on the customer. You’re still earning the right to be on their radar. That means shifting the focus to yourself – to your value proposition. What do you stand for? What problem do you solve? Why should anyone care?

Before you start tailoring messages, you need people to see them. This is the time to go broad, not narrow. Run brand campaigns. Get your story out there. Make noise. Once people start engaging, that’s when the data starts flowing – and that’s when it starts making sense.

3. No Customer Data? Start With What You Can Collect

If you don’t yet have enough customer data, start with zero-party data collection. Invite your customers to share preferences, needs, and intentions directly – through quizzes, gamified experiences, loyalty programmes, or preference centres. It’s transparent, permission-based, and immediately usable.

At the same time, remember that building up meaningful first-party data takes time. And if you already have some, chances are it’s messy. Clean it. Stitch it. Build trust in the data you do have. Over time, behavioural patterns will emerge, permission pools will grow, and signals will become clearer.

If you’re in an indirect model like FMCG, consider adding a direct-to-consumer layer. Not to replace your core business, but to build a representative dataset you can extrapolate from – and to ensure your resellers don’t end up knowing your customers better than you do.

4. Is Generative AI a Prerequisite?

Technically? No. You don’t need genAI in place to start personalising. But that’s not the real question. The real question is: What kind of personalisation are you aiming for?

Many organisations believe that once they’ve fixed their data – stitched IDs, cleaned records, built segments – they’re ready to personalise. What often follows is a string of templated, transactional, and uninspired messages: what we might call stupid channel execution. Everything’s automated, but nothing feels personal.

What’s missing is the content. Not just volume, but quality. Engaging, helpful, and sometimes even entertaining messages that move people – emotionally and behaviourally. That’s where many personalisation projects fall short.

And that’s where generative AI comes in. GenAI helps teams create the kinds of messages that make personalisation actually feel personal – across segments, formats, languages, and moments. When paired with a trained Brand LLM, it safeguards tone-of-voice, brand identity, and message relevance at scale.

So no – you don’t need GenAI on day one. But if your personalisation efforts are being led primarily by data people, be aware of the danger: they might get you the who, the when, and the where – but without GenAI and content maturity, you’ll miss the what and the why. And that’s where personalisation loses its power.

Conclusion: Personalisation Is the Right Move – But Only When the Time Is Right

Personalisation isn’t something to avoid – it’s something to time right. When done well, it becomes one of the most powerful tools for driving relevance, loyalty, and long-term customer value.

But the key is readiness. Personalisation only works when it’s built on a solid foundation. If your value proposition isn’t clear, if no one knows who you are, if you don’t have the data or content to deliver meaningful experiences – then doubling down on personalisation too early will likely disappoint.

Instead of rushing in, use this article as a readiness checklist. Make sure the essentials are in place:

• A strong and relevant value proposition
• A recognised brand with growing demand
• A clean and growing dataset
• A content supply chain that can support scale – ideally supercharged with GenAI

Once those boxes are ticked, personalisation can go from buzzword to business driver – and take your CX to the next level.

ALSO READ: CX Dialogues: Scott Lee Holloway, Head of CX at APS Bank