What is conditional content?

You're emailing both US customers (eligible for a seasonal promotion) and UK customers (who aren't). Building two separate campaigns works, but now you've got double the versions to test, maintain, and track. Conditional content handles this in a single template: the US block and the UK block live in the same email, and each subscriber only sees what applies to them.

Conditional content is a section of HTML that your ESP evaluates against subscriber data when the email sends. You define a condition (“if country equals US”) and wrap a content block around it. Subscribers who match the condition see that block; everyone else sees a fallback or nothing. Unlike personalization tokens, which swap out a single value, conditional content can show or hide entire sections: different images, different CTAs, different offers, different languages.

The syntax varies by platform. Mailchimp uses merge tag conditionals, Klaviyo uses Jinja-style logic blocks, and Salesforce Marketing Cloud uses AMPscript. The core logic is the same everywhere, but the way you write it isn't. Before building a conditional template, check your ESP's documentation to confirm whether conditions are evaluated at send time or click time. Most evaluate at send, which means the content is locked in when the message goes out, not when someone opens it.

Testing is the step most senders skip. A conditional block that renders correctly on desktop can break on mobile if hidden content still affects layout. Test every state: the block showing, the block hidden, and the fallback when no condition matches. If your ESP has inbox preview tools, check all three states across clients before sending to a large segment. One malformed conditional can make an entire section disappear for subscribers who should have seen it.

If you're new to conditional logic, start with a single binary condition on a segment you already have clean data for: a geographic split, a customer-vs-prospect flag, or a product-interest preference. Confirm it works end-to-end before adding more conditions. A/B testing the conditional variant against a non-conditional version is the fastest way to confirm the complexity is actually improving results.