How to leverage the power of AI in personalised marketing

Here are more ways you can train your team effectively:

• Host monthly hands-on workshops focused on specific tools or tasks.
• Assign tool champions who stay updated and help others on the team.
• Create AI playbooks with real workflows your team can test and adapt.
• Use poll makers to quickly uncover which AI tools or tasks your team finds most confusing, then tailor training around those gaps.
• Give short quizzes after each training session to reinforce key concepts and track how well your team understands the AI tools.

2. Localise Content With AI

Localisation is more than about translating words; it is about adapting the message to match the mindset. When you use AI to localise content, you show people you get them, no matter where they are.

The result of that kind of effort?

• Makes your ad targeting sharper
• Strengthens customer relationships
• Helps your future campaigns perform better across markets

AI spots patterns in user behaviour and turns that into dynamic website content that speaks the local language, literally and culturally.

What To Do

Here are ways you can use AI to localise your content:

• Adjust CTAs based on cultural norms and expectations.
• Translate at scale with context-aware language models.
• Adapt tone and formality based on local communication styles.
• Auto-generate region-based email variations with AI copy tools.
• Use AI to rewrite headlines that resonate better with local markets.
• Detect user location and deliver region-specific product info or prices.
• Analyse engagement by region to refine content for stronger connections.

3. Blend AI With Human Oversight

AI gets you speed, scale, and insights, but without human input, it can miss the mark.

On the other hand, blending AI with real people helps fix blind spots and shape content that feels human. It helps you humanise AI content, catch off-tone messages, and notice what data alone cannot, like cultural fit, emotional timing, or the deeper meaning behind your performance metrics.

This best practice is one of the smartest ways to overcome AI personalisation challenges while keeping your messaging clear, empathetic, and useful. With the right balance, you boost operational efficiency without losing the human touch.

What To Do

• Add human QA to AI decision trees to reduce automation errors.
• Collect and apply direct customer feedback to train better AI models.
• Analyse AI-generated reports manually to spot insights that algorithms miss.
• Let humans handle sensitive user interactions that need empathy or nuance.
• Use human editors to polish AI blog drafts and guarantee brand consistency.
• Review AI-generated emails or headlines before launch for tone and accuracy.
• Set up clear content guidelines so your team knows when to trust AI and when to step in.

4. Set Clear Personalisation Rules

Define exactly how and when AI adjusts content, offers, or messaging based on user data. When you set those rules upfront, you build consistency and trust across every interaction.

Plus, clear rules help you:

• Improve marketing efficiency and reduce noise.
• Guarantee content personalisation feels intentional, not random.
• Align personalisation strategies with your goals and brand voice.
• Avoid AI going rogue with awkward subject lines or mismatched recommendations.

With structure in place, AI becomes an extension of your strategy, not just another tool reacting to consumer behaviour in real time.

What To Do

• Document your rules so the whole team stays on the same page.
• Set boundaries for tone and language based on your brand voice.
• Create if-this-then-that scenarios for content placement and timing.
• Review rule performance monthly and adjust based on real results.
• Define which data triggers each personalisation, like clicks or purchase history.
• Use rule-based logic in your email marketing platform for predictable content swaps.

5. No Silos, Just Smarter Syncing

A customer’s browsing history, email clicks, purchase patterns, and even their unstructured data from chat, only mean something when you connect them all.

Syncing consistently gives your AI the full story, so your content feels cohesive, timely, and relevant. You avoid disconnects like promoting a webinar someone already attended or sending a welcome discount to a long-time customer.

With this, you can also protect your data quality and let AI deliver personal experiences that make sense.

What To Do

• Monitor for sync failures and fix them quickly.
• Use APIs to connect tools that do not natively integrate.
• Tag all data sources clearly so AI knows where it came from.
• Set regular sync intervals across platforms (e.g., hourly, daily, or real-time).
• Use a centralised customer data platform (CDP) to collect and organise everything.

3 AI Challenges That Disrupt Personalised Marketing

Scan the list below to spot the AI issues holding you back. Then, use the actionable points here to fix them fast and sharpen your personalised customer experiences where it matters most.

i. Too Much Data, Too Little Permission

AI thrives on data, but if you are feeding it information gathered without permission, you create a bigger problem. Your AI starts making decisions based on inputs it should not be using, and suddenly, your personalisation efforts feel invasive instead of helpful.

That is when data privacy concerns start to build, and trust starts to fall apart. Even the smartest algorithms cannot fix broken customer relationships. If people feel you are crossing the line, they stop engaging, no matter how “personalised” your message looks.

Here are ways to avoid this:

• Ask for permission clearly and early.
• Give users control over their data settings.
• Collect only what you need for each touchpoint.
• Explain how you use the data in plain language.

To get you started, here’s what should be in your data privacy policy: