Customers increasingly expect brands to understand their needs. Generic messages that ignore past purchases, interests or location often feel irrelevant. Personalisation means tailoring content, offers and experiences to individuals or groups based on what you know about them. Done thoughtfully, it makes marketing more helpful and effective. Done carelessly, it can feel intrusive or creepy.
This guide explains how to personalise marketing across channels while respecting privacy and building trust.
Levels of Personalisation
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| Basic | Using a subscriber’s first name in emails |
| Segment-based | Different emails for customers vs prospects |
| Behaviour-based | Recommendations based on products viewed |
| Lifecycle-based | Messages tailored to new, active or lapsed customers |
| Real-time | Website content changing based on current session |
Most small businesses can achieve strong results with segment-based and behaviour-based personalisation.
Sources of Personalisation Data
- Zero-party data: information customers intentionally share, such as preferences in a quiz or sign-up form
- First-party data: your own data from purchases, website behaviour and email engagement
- Contextual data: location, device, time of day and referral source
Zero-party and first-party data are generally the most reliable and privacy-friendly sources.
Personalisation by Channel
- Segment by interests, purchase history and engagement
- Send product recommendations related to past purchases
- Trigger emails based on behaviour, such as browsing or abandoned carts
- Adjust send times by time zone
Website
- Show returning visitors recently viewed products
- Display location-relevant information, such as nearest store or delivery times
- Customise banners for different traffic sources or campaigns
- Recommend related articles based on what a visitor reads
Ads
- Retarget visitors with products they viewed
- Show different creatives to new and existing customers
- Exclude recent buyers from acquisition campaigns
Messaging apps and SMS
- Send order updates and reminders relevant to individual purchases
- Offer recommendations based on previous orders, with consent
Step-by-Step Approach
- Start with goals: decide what personalisation should improve, such as repeat purchases or email clicks
- Collect useful data: ask simple preference questions and track key behaviours
- Create segments: group customers by meaningful differences
- Tailor content: adjust messages, offers and recommendations for each segment
- Test and measure: compare personalised content against generic versions
- Expand gradually: add more advanced personalisation as you learn
Privacy and Trust
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A useful test: would the customer be surprised or uncomfortable that you know this? If so, rethink the approach.
Measuring Personalisation
Compare personalised campaigns with control groups. Track click-through rates, conversion rates, average order value, repeat purchases and unsubscribe rates.
Common Mistakes
- Relying only on first-name personalisation
- Using outdated data, such as recommending products already bought
- Over-personalising in ways that feel intrusive
- Creating too many segments to manage
- Not testing whether personalisation improves results
Real-World Example
An online bookstore added a short quiz asking new subscribers which genres they enjoyed. Instead of one weekly newsletter, it sent genre-specific recommendations and new releases. Website visitors saw recently viewed books and “readers also liked” suggestions. Email click rates improved and repeat purchases increased, while unsubscribe rates fell.
Frequently Asked Questions
Is personalisation only for large companies?
No. Small businesses can personalise using email segments, simple website features and purchase history.
What is zero-party data?
Information customers intentionally share with you, such as preferences or interests.
Can personalisation hurt trust?
Yes, if it feels intrusive or uses unexpected data. Be transparent and respectful.
Do I need AI for personalisation?
Not necessarily. Rule-based segments and triggers deliver strong results; AI can help at larger scale.
How do I personalise without much data?
Ask simple preference questions and use basic behaviour like links clicked or products viewed.
Does personalisation work for B2B?
Yes. Tailor content by industry, role and stage in the buying process.
Conclusion
Personalisation makes marketing more relevant and valuable when based on data customers knowingly share and behaviour they expect you to use. Start with simple segments and triggers, tailor messages across channels, respect privacy and measure the impact. Relevant experiences build stronger relationships and better results.
