Personalisation beyond the first name

Less than most teams assume. Two useful signals, what someone browsed and what they bought, already support recommendations, reactivation and content selection. The trap is waiting for a complete customer view before starting. We usually begin with one journey where the data is strongest, prove the lift, then widen it.

Roughly here: use what a customer would expect you to know from doing business with you, and be careful with anything they would be surprised you noticed. Referring to a product someone viewed is fine. Referring to how long they hesitated is not. We write these rules down at the start of a project so the decision is not made ad hoc by whoever builds the campaign.

For email, your automation platform can usually do more than your team currently uses. Dynamic content, conditional blocks and behavioural triggers are standard. A dedicated tool earns its licence when you want on-site personalisation, product recommendations at scale, or experimentation across channels. We audit what you own before recommending anything new.

Against a holdout. A share of your audience keeps getting the generic version, and the difference between the two is the actual effect. Click-through alone will flatter you. We look at conversion, order value and repeat purchase, and we run tests long enough to survive a good week and a bad one.

That is the point, and it is where most setups break. Browsing on the site should change what the next email shows, and clicking in an email should change what the site shows on return. It needs a shared profile and a working connection between the two systems. We build that link, and we tell you early if your current stack cannot support it.