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Translated from German; if the versions differ, the German version applies.

Not legal advice: Legal content on this page appears only as verbatim quotations from statutes, court rulings or authority papers, with their source; quotations from German texts are our working translations. We do not assess them ourselves, and no lawyer has reviewed this page. It is no substitute for legal advice in your individual case.

Personalisation

In short: In email marketing, personalisation means that not all recipients get the same message: parts of the email – from the greeting to whole articles – are put together for each person based on the data stored about them.

Levels of personalisation

The term ranges from a small detail to a major intervention. It helps to distinguish by where the data come from:

  1. Information from the person themselves. Name, chosen topics, language, place – what someone entered when signing up or in their settings. Technically, the sending platform replaces placeholders with these values.
  2. Data from the relationship. Member or customer, date of sign-up, booked course. This produces, for example, notices that only concern members.
  3. Data from behaviour. Clicks in earlier newsletters, purchases, visits to the website. Recommendations such as “Matching your last course” are based on this.

The further down this list, the more data are analysed and the more likely an email is to feel to readers not helpful but watchful.

How it differs

  • Personalisation and segmentation: Segmentation divides the list into groups; each group gets its own version. Personalisation works at the level of the individual person. In practice, the two are often combined.
  • Personalisation and profiling: Personalisation is a word from practice, “profiling” a term defined by the GDPR in Art. 4(4). The full wording and the practical cases of the German data protection authorities are shown on the page Segmentation and personalisation. Whether a particular personalisation falls under it is not something we assess.
  • Personalisation and automation: A trigger email is triggered by an event. It can be personalised, but does not have to be.

What the GDPR says about objection

For advertising based on personal data, the EU General Data Protection Regulation (GDPR) provides: “Where personal data are processed for direct marketing purposes, the data subject shall have the right to object at any time to processing of personal data concerning him or her for such marketing, which includes profiling to the extent that it is related to such direct marketing.” (Art. 21(2) GDPR) We give no legal assessment of our own as to which form of personalisation needs which legal basis.

Easily confused

  • A greeting with a name is not “personal”. A “Hello Anna” above a text that everyone receives is the simplest level. Readers notice the difference.
  • Opens as a trigger: With “Protect Mail Activity”, Apple Mail loads remote content in the background as soon as an email arrives. A rule such as “whoever opened gets version B” then also hits people who never read it.
  • Placeholder without a fallback: If the first name is missing from the data, “Hello {firstname}” turns into “Hello ,”. That is why every placeholder needs a fallback.

Example

An adult education centre newsletter with placeholders and a fallback. The notation of placeholders differs between sending platforms; here it is simplified:

Hello {firstname | "everyone"},

{if topic = "Languages"}
  New in spring: Spanish for beginners, from 3 March.
{else}
  New in spring: our complete course programme.
{end}

Without a stored first name, it says “Hello everyone” instead of “Hello ,”. The block below uses the topic the person chose when signing up – level 1, without analysing behaviour.

Frequently asked questions

What is personalisation in simple terms? The email adapts to the person reading it: with their name, with topics they have chosen, or with content that suits them.

Is personalisation worthwhile for small lists? The first level almost always is: letting people choose topics themselves costs little and saves guesswork. Analysing behavioural data only pays off once there are enough data.

How do I test personalised emails? With test records that contain special cases: empty first name, very long name, umlauts, no topic chosen. Send each variant once to a mailbox of your own.

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