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TheGodFather
New Member

Need Help with Visualizing Customer Service Choices (PowerBi) – Seeking Advice!

I'm facing a challenge in creating a visualization using PowerBi  for the services each customer has signed up for in my dataset named "01 Churn-Dataset." The table includes various columns such as customerID, gender, SeniorCitizen, Partner, Dependents, tenure, PhoneService, MultipleLines, InternetService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, Contract, PaperlessBilling, PaymentMethod, MonthlyCharges, TotalCharges, numAdminTickets, numTechTickets, and Churn.

I've attempted different methods, including creating a bar chart. However, when I include the services (phone, multiple lines, internet, online security, online backup, device protection, tech support, streaming TV, and movies), the chart displays combinations of "Yes," "No," "No internet service," and another "No," "Yes," etc., which doesn't convey meaningful information.

I also tried creating a new table focused only on the services, with two columns for "Yes" and "No." Using DAX formulas, I calculated the count of "Yes" and "No" for each service. However, I struggled with establishing the relationship between the new table and the original one.

I'm seeking guidance on the most effective approach to visualize the services each customer has signed up for, and any assistance in resolving the challenges I've encountered would be greatly appreciated. Thank you!

here is an example of my data table : 

customerIDgenderSeniorCitizenPartnerDependentstenurePhoneServiceMultipleLinesInternetServiceOnlineSecurityOnlineBackupDeviceProtectionTechSupportStreamingTVStreamingMoviesContractPaperlessBillingPaymentMethodMonthlyChargesTotalChargesnumAdminTicketsnumTechTicketsChurn
7590-VHVEGFemale0YesNo1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthYesElectronic check29,8529,8500No
5575-GNVDEMale0NoNo34YesNoDSLYesNoYesNoNoNoOne yearNoMailed check56,951889,500No
3668-QPYBKMale0NoNo2YesNoDSLYesYesNoNoNoNoMonth-to-monthYesMailed check53,85108,1500Yes
7795-CFOCWMale0NoNo45NoNo phone serviceDSLYesNoYesYesNoNoOne yearNoBank transfer (automatic)42,31840,7503No
9237-HQITUFemale0NoNo2YesNoFiber opticNoNoNoNoNoNoMonth-to-monthYesElectronic check70,7151,6500Yes
9305-CDSKCFemale0NoNo8YesYesFiber opticNoNoYesNoYesYesMonth-to-monthYesElectronic check99,65820,500Yes
1452-KIOVKMale0NoYes22YesYesFiber opticNoYesNoNoYesNoMonth-to-monthYesCredit card (automatic)89,11949,400No
6713-OKOMCFemale0NoNo10NoNo phone serviceDSLYesNoNoNoNoNoMonth-to-monthNoMailed check29,75301,900No
7892-POOKPFemale0YesNo28YesYesFiber opticNoNoYesYesYesYesMonth-to-monthYesElectronic check104,83046,0502Yes
6388-TABGUMale0NoYes62YesNoDSLYesYesNoNoNoNoOne yearNoBank transfer (automatic)56,153487,9500No
9763-GRSKDMale0YesYes13YesNoDSLYesNoNoNoNoNoMonth-to-monthYesMailed check49,95587,4510No
7469-LKBCIMale0NoNo16YesNoNoNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceTwo yearNoCredit card (automatic)18,95326,800No
8091-TTVAXMale0YesNo58YesYesFiber opticNoNoYesNoYesYesOne yearNoCredit card (automatic)100,355681,100No
0280-XJGEXMale0NoNo49YesYesFiber opticNoYesYesNoYesYesMonth-to-monthYesBank transfer (automatic)103,75036,354Yes
5129-JLPISMale0NoNo25YesNoFiber opticYesNoYesYesYesYesMonth-to-monthYesElectronic check105,52686,0500No
3655-SNQYZFemale0YesYes69YesYesFiber opticYesYesYesYesYesYesTwo yearNoCredit card (automatic)113,257895,1500No
8191-XWSZGFemale0NoNo52YesNoNoNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceOne yearNoMailed check20,651022,9500No
9959-WOFKTMale0NoYes71YesYesFiber opticYesNoYesNoYesYesTwo yearNoBank transfer (automatic)106,77382,2504No
4190-MFLUWFemale0YesYes10YesNoDSLNoNoYesYesNoNoMonth-to-monthNoCredit card (automatic)55,2528,3500Yes
4183-MYFRBFemale0NoNo21YesNoFiber opticNoYesYesNoNoYesMonth-to-monthYesElectronic check90,051862,900No
8779-QRDMVMale1NoNo1NoNo phone serviceDSLNoNoYesNoNoYesMonth-to-monthYesElectronic check39,6539,6500Yes
1680-VDCWWMale0YesNo12YesNoNoNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceOne yearNoBank transfer (automatic)19,8202,2520No
1066-JKSGKMale0NoNo1YesNoNoNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceNo internet serviceMonth-to-monthNoMailed check20,1520,1540Yes
3638-WEABWFemale0YesNo58YesYesDSLNoYesNoYesNoNoTwo yearYesCredit card (automatic)59,93505,110No
6322-HRPFAMale0YesYes49YesNoDSLYesYesNoYesNoNoMonth-to-monthNoCredit card (automatic)59,62970,303No
6865-JZNKOFemale0NoNo30YesNoDSLYesYesNoNoNoNoMonth-to-monthYesBank transfer (automatic)55,31530,600No
6467-CHFZWMale0YesYes47YesYesFiber opticNoYesNoNoYesYesMonth-to-monthYesElectronic check99,354749,1504Yes
8665-UTDHZMale0YesYes1NoNo phone serviceDSLNoYesNoNoNoNoMonth-to-monthNoElectronic check30,230,200Yes
5248-YGIJNMale0YesNo72YesYesDSLYesYesYesYesYesYesTwo yearYesCredit card (automatic)90,256369,4510No
8773-HHUOZFemale0NoYes17YesNoDSLNoNoNoNoYesYesMonth-to-monthYesMailed check64,71093,100Yes
3841-NFECXFemale1YesNo71YesYesFiber opticYesYesYesYesNoNoTwo yearYesCredit card (automatic)96,356766,9500No
1 REPLY 1
lbendlin
Super User
Super User

Not sure if you realize it but you are going into Machine Learning territory with this one - you have all these data points and need to define the weight for each of them (how important they are to you), but more importantly you need to formulate your business question.  What insights are you hoping to get from the data? Any hypotheses that you want to prove or disprove?

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