Is this a Recommender system problem?

I have a list of reward campaigns. They are to be advertised to the best customers who didn’t meet the transaction criteria for each campaign; for example Transfer and win. Customers who have done 5x transfers in a week, the recommender system is supposed to figure out the customers who didn’t meet the criteria of the Transfer and Win campaign but are more likely to heed to the campaign and advertise to them. I already pulled out the data for each case but I don’t know how to build the recommender system. I looked it up on google and saw articles on CF and content-based filtering and I don’t think they are right for what I am doing. I also feel like this is a clustering problem but I am not exactly too sure. Can someone please help?

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