Suitability of Causal Impact (R package) for a ‘plug and play’ style user interface for measuring causal inference related to marketing where the user loads in a dataset and sets things up on UI. If this is not suitable can it be adapted or are there other methods with similar accuracy level?

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I am a final year undergraduate student who has been tasked with making a causal impact/inference model for a digital marketing agency as part of my final year project at university. The company has asked for a simple user interface that allows for data tables to be uploaded, a few settings adjusted (suitable for ‘semi-layman’) , and then outputs a metric for the impact of some marketing activity on a KPI.

I found something that looks like it gives a good output, which is the Causal Impact package within R. However my research so far show that this is quite hands on as it requires adding 10 -20 control variables to deal with bias etc, although the result would be great the company may not be happy with this method as its not plug and play.

Can anyone offer advice on if this kind of method can be adapted to fit the above criteria? or if there are alternative methods that fit the criteria? I have posted similar things about this in the past and people have commented saying the offer services that do the above, but I am specifically looking to do it myself and get quite hands on in putting it all together as its for a project.

Any advice would be very much appreciated! Thanks

submitted by /u/Flewizzle
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