Forum Discussion
HarishRathore
6 years agoHelper II
Dynamic Classification with two criteria
Hi, I want to classify towns based on their volume in different segment. Following is the example dataset: Town Name Brand Name Category Segment Volume Jaipur ABC Shampoo Deluxe Shampo...
- 6 years ago
Hi az38 , Thanks for your effort. The criteria to classify towns is as follows ;
- we are applying 80/20 formula here in segments, so when we are cumulating volume contribution% then top 80% ( in descending order) data will look like this
- so segment will always be in slicer. you can see that i have sorted data in descending order to get top % volume contributed towns. now we need to classify towns as per below criteria :
- If volume contribution is till 80% and market share of "My Company" in the town is >= "My Company's Total Share" in the segment then "Stronghold"
- If volume contribution is till 80% and market share of "My Company" in the town is < "My Company's Total Share" in the segment then "Headroom"
- If volume contribution is till remaining 20% and market share of "My Company" in the town is >= "My Company's Total Share" in the segment then "Emerging"
- If volume contribution is till remaining 20% and market share of "My Company" in the town is < "My Company's Total Share" in the segment then "Small"
- its like 0% to 80% then 81% to 100% (since we have already sorted data in top to bottom). I want to approach this by using "DESC" formula so that it would always be dynamic whenever i am selecting any other segment. I have 15 million rows data hence request for dynamic measures.
- I have tried my best to explain the situation. Sorry for any bad grammer or spelling mistake.
Regards
Harish
P.S. - I tried to use your link but it not working. Also in my excel link there a sheet called "Criteria". you can also go through there.
- 6 years ago
Hi,
You may download my Excel solution workbook from here. I have written DAX measures to solve the problem. This can very easily be imported into PowerBI Desktop but before you do so, please check the results thoroughly.
Hope this helps.
- 6 years ago
HarishRathore
6 years agoHelper II
Can someone please help me? I need help regarding this. Please
- Anonymous6 years agoNot applicableSorry, mate, but your description is completely incomprehensible to me. If I could clearly understand, what you want... I might be able to help you.
Best
D- HarishRathore6 years agoHelper III need to classify towns based on volume in particular segment and based on my company's market share in that particular brand. For example My company's brands are ABC and MNO. Rest are competition brands. I am sorry that I completely missed out putting company columns in the post. Now I need to classify.. for example total market share of my company of ABC brand in deluxe shampoo is 24.6%. now when you sort deluxe shampoo's volume in descending order then you would get Jodhpur at the top and jaipur at the bottom.
So when you pull salience or contribution of these town then you would get Jodhpur 30%, Ajmer 24%, Udaipur 23% and Jaipur 22%.
Now we need to segregate town between 2 parts based on top 80% and rest which is 20%. In 80% volume contributed towns, you would get Jodhpur, Ajmer, Udaipur.
Now jodhpur's ABC market share is 5.7% which is less than total market share of ABC which is 24.6%. hence we will classify Jodhpur town as Headroom town. (As I have mentioned in my post, rest towns are to be classified as per parameters).
I really hope that I have put my required comprehensively.
Please do help me as it would help me a lot in my analysis. Right now everything is manual. Regards- Ashish_Mathur6 years agoSuper User
Hi,
Share the final dataset with the Company column and for the sample data that you share, show the exact expected result.
- Anonymous6 years agoNot applicableBy the way... Can you not create a model in which you'd be able to show us what you want? YOu could then clearly demonstrate what numbers you want to see, even if you don't know the measure's formula right now. You could show us what the numbers should be in such a picture... A picture is worth a thousand words.
Best
D