A 95% confidence interval comes from a procedure that captures the true value in 95% of repeated samples. For the interval you actually computed, the true value is either inside it or it is not. The 95% describes the method's long-run hit rate, not your one interval.
What it does not mean: there is no 95% probability that the parameter sits between your bounds. It is not a range containing 95% of users. It is also not a promise that 95% of future results will land inside it.
The practical read is the width. An interval of [-0.1%, +4.3%] on conversion says the change might be nothing, so you need more data before betting on it. A tight interval hugging zero is a genuinely different answer. It says the effect, if any exists, is too small to care about.
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