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The decision is where to put the effort: content, data or code. Programmes that disappoint have usually skipped a layer. A recommendation block fed by an incomplete order history puts the wrong product in front of a loyal customer, and that email does more damage than a generic one would.

Personalisation strings are the floor, and they run on clean data

Personalisation strings insert a subscriber attribute, such as a first name or a city, into the subject line, preheader or body of an email in Marketing Cloud Engagement, the Salesforce product for email and mobile messaging. They are quick to set up. Because they reach the inbox before the email is opened, the subject line is where they are most visible.

The risk sits in the data. A missing or badly formatted field turns a friendly greeting into an empty comma in front of every subscriber who lacks that value. Our campaigns reach two million recipients, and at that volume even a small share of empty fields means thousands of broken emails. Every string needs a default value, and every field it reads from needs an owner.

Dynamic content scales relevance without extra emails

Dynamic content shows different content blocks to different subscribers inside one email, based on rules you set on subscriber data such as previous orders, preferred store or language. One email replaces what would otherwise be five or six versions, so production effort stays flat while relevance goes up. For pan-European programmes, language and country rules alone often justify the setup.

The cost moves to rule management. Every rule is a promise that the underlying data exists and stays current. Rules also interact: a subscriber can match several blocks, and the priority order decides which one they see. Keep the rules in a register with an owner. Teams moving to the platform-native product will rebuild these rules on its own data model, which Marketing Cloud Next and its editions explains in more detail.

AMPscript is for one-to-one content, and it needs a developer

AMPscript is the scripting language of Marketing Cloud Engagement, used in emails, landing pages, SMS and push messages. It can look up related data at send time, such as recent orders or a loyalty balance, and format it into a message for one person. That is the step from segments to individuals.

It is also code. Each script has to be written, tested and maintained by someone who knows the language and your data extensions, the tables where Marketing Cloud stores subscriber and related data. A marketing team without that skill in-house depends on a partner for every change. Ask who will fix a broken script the evening before a campaign launch. Use AMPscript where the content genuinely differs per person, such as an order summary or a points statement, and use dynamic content everywhere else.

Kevin Van der Straeten

Managing Partner

Einstein features decide what and when, based on behaviour

Einstein, the set of predictive features in Marketing Cloud Engagement, adds personalisation that no marketer writes by hand. Einstein Engagement Scoring predicts how likely each subscriber is to open, click or unsubscribe. Einstein Send Time Optimization picks the moment each person tends to engage. Einstein Content Selection and product recommendations choose images, offers or products per subscriber when the email opens. All of them learn from engagement and behavioural data, so their value depends on how much of that data you hold.

The trade-off is transparency. A marketer can explain a dynamic content rule to a compliance officer in one sentence. A predictive score is harder to explain, and some organisations need that explanation before a model may choose content. Einstein features are the right next layer when your volumes are high enough for the models to learn and your team accepts decisions it did not write.

Interactive email moves the action into the inbox

Interactive email lets subscribers fill in a form, leave a product review or update their preferences without leaving the inbox, and the answers land straight in Marketing Cloud. That turns personalisation into an exchange: every submitted form improves the data the next email uses. Build choices and mail client support are a subject of their own, covered in our guide to interactive email.

Choosing the next layer of email personalisation

Pick the next layer by what your programme lacks today. These points show whether the foundation is ready:

Every field a personalisation string reads from has an owner and a default value.
Dynamic content rules sit in one register, with a priority order someone reviews.
Someone in your team or at your partner can write and maintain AMPscript.
Order and loyalty data reach Marketing Cloud, directly or through Data Cloud (Data 360), the Salesforce product that unifies customer data.

Measure each layer against a result the business already reports, such as repeat orders or revenue per email, and compare it with the layer below. For changes to timing and sequence, testing journey paths with Path Optimizer gives you that comparison inside a live journey.

Our marketing automation team builds personalised journeys on behavioural data, and the work that decides the outcome happens before the first send: agreeing which data feeds which layer, and who owns it after launch. We stay on after go-live and track the KPIs set at the start, so the next layer is added when the numbers support it.

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About the Author

Kevin Van der Straeten

Managing Partner

Workmail