trying to plot submitted leads based on hours / 24 hours for

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Hi All,

I have started a digital marketing campaign where the conversion is a landing page where users submit their names and phone number to register for the event.

The Ad is running 24 hours a day for the last 1 month. and users are submitting on different times.

the form export .csv format and time as below format:

2022-04-15T09:12:22Z

I have 2500 leads so far and I want to find the next times or most times (highest frequency) where users submitted the form from the 24h Ad.

My problem is that I couldn't plot using time not dates as below code:

> ninga = read.csv("ninga13.csv")
> ninga$ï..Submission.Time <- as.POSIXct(ninga$ï..Submission.Time,format= "%Y-%m-%dT%H:%M:%SZ" , timezone = "UTC")
> str(ninga)
'data.frame':	2004 obs. of  4 variables:
 $ ï..Submission.Time: POSIXct, format: "2022-04-15 09:12:22" "2022-04-14 12:17:59" "2022-03-22 20:16:34" "2022-04-16 13:01:46" ...
 $ phone.number      : chr  "790274593" "780773137" "'+9627903262" "799204194" ...
 $ name              : chr  "آيات ÙŠÙ\210سÙ\201" "ÙƒÙ\210كب  احمد الرÙ\201اعي" "Ù\210سيم" "رهÙ\201 سمير" ...
 $ Network           : chr  "79" "78" "'+" "79" ...
> class(ninga$ï..Submission.Time)
[1] "POSIXct" "POSIXt"

What can I do to visualize most frequent times users submitted the form? If I managed to find that then I can direct my ad in specific times where users are most probably will submit and then I will be able to save ad cost in not promoting in times where users wont interact.

your help is much appreciated

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