Marketing Campaign Analysis | Saturation, Distribution, and Probability

In this episode you are going to learn how to evaluate if we are overleveraging on a particular channel, understand the saturation when our campaign has lost its initial effectiveness and provide the probability of our marketing campaign conversions.
Agenda
1:01 Management Request
1:10 Dataset Exploration
2:50 Pivot Table of Traffic and Conversions
8:46 Campaign Saturation Analysis
15:45 Visualization of Saturation
18:01 Visualization of Slope
23:01 Distribution of Conversions
26:04 Probability
28:16 ECDF Plot for Probability
32:13 Data Story
Get the dataset here:
absentdata.com...
#data
#digitalmarketing
#datanalytics
#dataanalysis
#datascience
#excel

[@NamPham15019]

This video is a hidden gem on KZbin as you didn't prioritize too much on tools like R or Python but really to focus on the business problem by asking the right questions, and crafting insightful narratives. Truly love how you can use simple math in this video to answer the business problem. That is just so impressive. Please do more videos like this on marketing/ revenue 😄. Oh btw, i have one question, how the probability can be calculated when you divide the index number to the conversion rate? what is the logic behind it and is it the effective way to approach when it come to probability?

[@absentdata]

Thanks for the compliment. Probability can be seen as relative frequency of values. Dividing by the index gives you the relative frequency. Look up empirical cumulative distribution for more info

[@blinquedu2]

@@absentdata you also could've used normal distribution to reach that percentage, right?

[@absentdata]

@@blinquedu2 You are assuming that the data is normally distributed which is not typical for marketing data. So the normal distribution wouldnt apply here

[@blinquedu2]

@@absentdata I get that but one of the empirical distribution limitations is the lack of effectiviness comparing to other distributions so what is the reason for using such distribution and if it is commonly used in the DA daily basis in a company.... thanks

[@wewung2]

Thanks for the walkthrough. Really insightful.

[@absentdata]

Glad you found it valuable!

[@method341]

Thanks for using only what you need (Excel) instead of overcomplicating it with languages like R and Python (not that I don't love these). Sometimes I am guilty of firing up RStudio when the analysis/task could be done in Excel in like 5 minutes.

[@absentdata]

Yeah I was also guilty of running to Python instead of easily doing things in Excel also :) Great comment!

[@leonardopoveromo8611]

@@absentdata is it possible to have a digital marketing analysis in Python too! Great stuff keep doing that! much love

[@absentdata]

@@leonardopoveromo8611 Definitely!

[@youtubeuser4878]

Awesome tutorial as always. Can you recommend any resources (courses, boot camps, books etc) for someone with a data analysis background looking to level up in marketing analytics?

[@simonoganga5956]

Good stuff

[@absentdata]

Glad you enjoyed

[@_Anorasmusic]

Thank YOUUUUUUUUUUUUUUUUUUU

[@absentdata]

Your WELLLLLLLCOME!