How do Croct audiences differ from segments synced from our CDP?
We already maintain batch-computed segments in a CDP, refreshed nightly, and I am trying to understand whether Croct audiences duplicate that work or do something structurally different.
Concretely: for a first-session visitor who has never appeared in our CDP, what does "real-time" evaluation actually change? And do we need to pipe our CDP segments into Croct for targeting to be useful, or can conditions be built entirely on data Croct collects itself?
2 answers
The structural difference is when the membership decision happens. A CDP segment is computed from historical data and syncs on a delay, so by design it describes what already happened. A Croct audience is a CQL condition evaluated in real time on every interaction, so membership can change mid-session.
Your first-session visitor is the clearest case: they will never be in a nightly CDP segment during that visit, but a condition like
session's stats' pageviews > 3starts matching them on their fourth pageview, minutes into their first session. That is the concrete difference: you can act on behavior while it is happening rather than the next day.
On your second question: no CDP pipe is required. Conditions are built on signals Croct collects directly, and there are 100+ of them across Events, Location, Marketing, Session, Shopping, User, Web, and Technology categories, plus any custom attributes you set yourself.
In practice we kept our CDP for downstream things (email, warehouse modeling) and build on-site targeting purely on Croct signals. The two overlap less than you would expect: the batch segments answer "who is this user historically", the real-time conditions answer "what is this visitor doing right now", and personalization mostly needs the latter.