Data Science Project - RFM model

[@daviduno2024]

Lovely project. Hopefully you could expand more on how to deal with the outliers

[@karinadatascientist]

Sure, good idea!

[@VenkatesanVenkat-fd4hg]

Awesome share as always....

[@karinadatascientist]

Thank you so much for watching!

[@tarekhusam]

you are awesome, keep those videos I'm a big fan now!

[@karinadatascientist]

Thank you, I appreciate it

[@mapletech_22]

Insightful information 👏

[@karinadatascientist]

Thank you. Glad to hear that

[@jhonfir2235]

Nice to Learn from another New Project........!!

[@karinadatascientist]

Glad you liked it!

[@AbouAli01006300091]

Very well explained @Karina, However I am wondering in both steps: RFM_Segment_Label -->> The Low-Value, Medium-Value, High-Value and later RFM_Customer_Segments --> The Potential Loyal, At Risk Customers, VIP/Loyal, Lost, and Can't Lose How to choose the ranges properly?. Does it have any relation to the quantity of customers found in each RFM_Score? or how ? Thanks a lot!.

[@MagysEnglishEduClubbl3rby]

Perfect! More videos please:)

[@karinadatascientist]

Thank you for your support!

[@Emadamx]

You earned a new subscriber 😊, I really enjoyed your video 🤗

[@karinadatascientist]

Yay! Glad you liked you and thank you for subscribing

[@abdiwelly5606]

The materials has been very informative for me , try to put your picture on the top left side of the videos

[@karinadatascientist]

@@abdiwelly5606 I’ll try that! I am still learning how to edit my videos 😊

[@shivamtiwari1766]

I think very important video for us currently I want to make a project so please create more videos

[@karinadatascientist]

Thank you for feedback. More projects to come!

[@siddharth4873]

Can you please do a video on churn and churn prediction?

[@karinadatascientist]

That's a great idea, thank you

[@DeveloaSS]

I really like your videos. for when a video for beginners from 0?

[@karinadatascientist]

Thank you. I didn't know there was an interest in videos for beginners. I have a masterclass "Data Analysis with Python", it is for complete beginners - karinadatascientist.com/ .

[@sachintyagi2003]

! like ur videos! Thnkss!

[@karinadatascientist]

Thank you for watching!

[@HariPandalai]

Karina This is very helpful. Your video's have all been extremely educative. Where could I get the Jupyter Notebook. Thanks.

[@karinadatascientist]

Thank you. If you mean Jupyter Notebook as a software, you can download it here jupyter.org/. If you mean RFM model - you can create it yourself by following the tutorial in this video

[@MommysAndHuggysShow]

How can we add segmentation values ​​and rfm values ​​to the same file next to each customer? Can you write an output formula?

[@karinadatascientist]

you need to save the dataframe, after all those columns were added. All you need to do is: rfm.to_csv('/Users/INDICATE_WHERE_TO_SAVE_FILE/rfm_model.csv', index=False) name_of_what_you_are_saving.to_csv('Path_to_your_file/filename.csv', index = False) You can also save it to excel with rfm.to_excel('filename.xlsx', index=False)

[@galinaorlova4236]

Мне тоже плотли нравится 😅

[@shajidaameer565]

How to write a short description about this project in resume

[@karinadatascientist]

Developed an RFM (Recency, Frequency, Monetary) model in Python to analyze customer behavior and segment the customer base for targeted marketing strategies. Utilized the pandas library for data manipulation, and plotly for data visualization. The model successfully identified key customer segments and provided actionable insights to improve customer retention and increase revenue.

[@hrshtmlng]

Why dont you use pyforest!!?

[@karinadatascientist]

Don't know, a habit? In my videos I want to show people how libraries work, and how to apply this knowledge to other projects. Don't get me wrong, I like that pyforest removes the need of installing libraries one by one. I sometimes use it for my personal quick analysis, but not for tutorials. I think it is great for personal use, not when you work with a team or building a portfolio

[@galinaorlova4236]

Здрасти 😀👋

[@karinadatascientist]

Привет 👋