The 24 most commonly misunderstood marketing data terms

Imagine you’re a marketer planning a win-back campaign and you ask your data team for a list of “inactive customers.” You’re expecting people who haven’t bought anything in 90 days. The list comes back based on users who haven’t opened your app in 30 days, because that’s how “inactive” is defined in the data. 

Or you ask for “real-time” audience updates to avoid sending “we miss you” to someone who just placed an order. You’re picturing a list that refreshes every 15 minutes. The data team hears “updates within seconds” and comes back with questions about new infrastructure, ongoing costs, and a longer timeline.

These differences affect what gets built, how much it costs, and when marketing can use it. Agreeing early on what a “customer” means, what makes an audience ready, and how fresh a signal needs to be can prevent misunderstandings from becoming campaign rework.

This guide covers 24 terms that marketing and data engineering often interpret differently, organized around five practical questions about campaign execution. Use the paired definitions as conversation starters: surface assumptions, clarify what each side needs, and agree on meanings that fit your business before work begins.

1. Where does the campaign data come from?