Moving average versus exponential forecast, which is better for predicting respondents?

Occasional Contributor


My dataset includes monthly data of about 12 months that shows a funnel including, number of respondents, number of people who showed up at the event, and number of people who signed up to join for future events. I would like to set up a forecast so that we can set a target of let's say 80 new joiners and it would show us how many people we would need to achieve this target at each stage based on previous data.

Currently, I've gone with taking the last two months running average to get these numbers. But as I'm not too familiar with the forecast functions, I'm not sure if that is a better method for such data. I just want to make sure I'm following best practices. Please advise if I can do this in a better way.

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