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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 :
customerID | gender | SeniorCitizen | Partner | Dependents | tenure | PhoneService | MultipleLines | InternetService | OnlineSecurity | OnlineBackup | DeviceProtection | TechSupport | StreamingTV | StreamingMovies | Contract | PaperlessBilling | PaymentMethod | MonthlyCharges | TotalCharges | numAdminTickets | numTechTickets | Churn |
7590-VHVEG | Female | 0 | Yes | No | 1 | No | No phone service | DSL | No | Yes | No | No | No | No | Month-to-month | Yes | Electronic check | 29,85 | 29,85 | 0 | 0 | No |
5575-GNVDE | Male | 0 | No | No | 34 | Yes | No | DSL | Yes | No | Yes | No | No | No | One year | No | Mailed check | 56,95 | 1889,5 | 0 | 0 | No |
3668-QPYBK | Male | 0 | No | No | 2 | Yes | No | DSL | Yes | Yes | No | No | No | No | Month-to-month | Yes | Mailed check | 53,85 | 108,15 | 0 | 0 | Yes |
7795-CFOCW | Male | 0 | No | No | 45 | No | No phone service | DSL | Yes | No | Yes | Yes | No | No | One year | No | Bank transfer (automatic) | 42,3 | 1840,75 | 0 | 3 | No |
9237-HQITU | Female | 0 | No | No | 2 | Yes | No | Fiber optic | No | No | No | No | No | No | Month-to-month | Yes | Electronic check | 70,7 | 151,65 | 0 | 0 | Yes |
9305-CDSKC | Female | 0 | No | No | 8 | Yes | Yes | Fiber optic | No | No | Yes | No | Yes | Yes | Month-to-month | Yes | Electronic check | 99,65 | 820,5 | 0 | 0 | Yes |
1452-KIOVK | Male | 0 | No | Yes | 22 | Yes | Yes | Fiber optic | No | Yes | No | No | Yes | No | Month-to-month | Yes | Credit card (automatic) | 89,1 | 1949,4 | 0 | 0 | No |
6713-OKOMC | Female | 0 | No | No | 10 | No | No phone service | DSL | Yes | No | No | No | No | No | Month-to-month | No | Mailed check | 29,75 | 301,9 | 0 | 0 | No |
7892-POOKP | Female | 0 | Yes | No | 28 | Yes | Yes | Fiber optic | No | No | Yes | Yes | Yes | Yes | Month-to-month | Yes | Electronic check | 104,8 | 3046,05 | 0 | 2 | Yes |
6388-TABGU | Male | 0 | No | Yes | 62 | Yes | No | DSL | Yes | Yes | No | No | No | No | One year | No | Bank transfer (automatic) | 56,15 | 3487,95 | 0 | 0 | No |
9763-GRSKD | Male | 0 | Yes | Yes | 13 | Yes | No | DSL | Yes | No | No | No | No | No | Month-to-month | Yes | Mailed check | 49,95 | 587,45 | 1 | 0 | No |
7469-LKBCI | Male | 0 | No | No | 16 | Yes | No | No | No internet service | No internet service | No internet service | No internet service | No internet service | No internet service | Two year | No | Credit card (automatic) | 18,95 | 326,8 | 0 | 0 | No |
8091-TTVAX | Male | 0 | Yes | No | 58 | Yes | Yes | Fiber optic | No | No | Yes | No | Yes | Yes | One year | No | Credit card (automatic) | 100,35 | 5681,1 | 0 | 0 | No |
0280-XJGEX | Male | 0 | No | No | 49 | Yes | Yes | Fiber optic | No | Yes | Yes | No | Yes | Yes | Month-to-month | Yes | Bank transfer (automatic) | 103,7 | 5036,3 | 5 | 4 | Yes |
5129-JLPIS | Male | 0 | No | No | 25 | Yes | No | Fiber optic | Yes | No | Yes | Yes | Yes | Yes | Month-to-month | Yes | Electronic check | 105,5 | 2686,05 | 0 | 0 | No |
3655-SNQYZ | Female | 0 | Yes | Yes | 69 | Yes | Yes | Fiber optic | Yes | Yes | Yes | Yes | Yes | Yes | Two year | No | Credit card (automatic) | 113,25 | 7895,15 | 0 | 0 | No |
8191-XWSZG | Female | 0 | No | No | 52 | Yes | No | No | No internet service | No internet service | No internet service | No internet service | No internet service | No internet service | One year | No | Mailed check | 20,65 | 1022,95 | 0 | 0 | No |
9959-WOFKT | Male | 0 | No | Yes | 71 | Yes | Yes | Fiber optic | Yes | No | Yes | No | Yes | Yes | Two year | No | Bank transfer (automatic) | 106,7 | 7382,25 | 0 | 4 | No |
4190-MFLUW | Female | 0 | Yes | Yes | 10 | Yes | No | DSL | No | No | Yes | Yes | No | No | Month-to-month | No | Credit card (automatic) | 55,2 | 528,35 | 0 | 0 | Yes |
4183-MYFRB | Female | 0 | No | No | 21 | Yes | No | Fiber optic | No | Yes | Yes | No | No | Yes | Month-to-month | Yes | Electronic check | 90,05 | 1862,9 | 0 | 0 | No |
8779-QRDMV | Male | 1 | No | No | 1 | No | No phone service | DSL | No | No | Yes | No | No | Yes | Month-to-month | Yes | Electronic check | 39,65 | 39,65 | 0 | 0 | Yes |
1680-VDCWW | Male | 0 | Yes | No | 12 | Yes | No | No | No internet service | No internet service | No internet service | No internet service | No internet service | No internet service | One year | No | Bank transfer (automatic) | 19,8 | 202,25 | 2 | 0 | No |
1066-JKSGK | Male | 0 | No | No | 1 | Yes | No | No | No internet service | No internet service | No internet service | No internet service | No internet service | No internet service | Month-to-month | No | Mailed check | 20,15 | 20,15 | 4 | 0 | Yes |
3638-WEABW | Female | 0 | Yes | No | 58 | Yes | Yes | DSL | No | Yes | No | Yes | No | No | Two year | Yes | Credit card (automatic) | 59,9 | 3505,1 | 1 | 0 | No |
6322-HRPFA | Male | 0 | Yes | Yes | 49 | Yes | No | DSL | Yes | Yes | No | Yes | No | No | Month-to-month | No | Credit card (automatic) | 59,6 | 2970,3 | 0 | 3 | No |
6865-JZNKO | Female | 0 | No | No | 30 | Yes | No | DSL | Yes | Yes | No | No | No | No | Month-to-month | Yes | Bank transfer (automatic) | 55,3 | 1530,6 | 0 | 0 | No |
6467-CHFZW | Male | 0 | Yes | Yes | 47 | Yes | Yes | Fiber optic | No | Yes | No | No | Yes | Yes | Month-to-month | Yes | Electronic check | 99,35 | 4749,15 | 0 | 4 | Yes |
8665-UTDHZ | Male | 0 | Yes | Yes | 1 | No | No phone service | DSL | No | Yes | No | No | No | No | Month-to-month | No | Electronic check | 30,2 | 30,2 | 0 | 0 | Yes |
5248-YGIJN | Male | 0 | Yes | No | 72 | Yes | Yes | DSL | Yes | Yes | Yes | Yes | Yes | Yes | Two year | Yes | Credit card (automatic) | 90,25 | 6369,45 | 1 | 0 | No |
8773-HHUOZ | Female | 0 | No | Yes | 17 | Yes | No | DSL | No | No | No | No | Yes | Yes | Month-to-month | Yes | Mailed check | 64,7 | 1093,1 | 0 | 0 | Yes |
3841-NFECX | Female | 1 | Yes | No | 71 | Yes | Yes | Fiber optic | Yes | Yes | Yes | Yes | No | No | Two year | Yes | Credit card (automatic) | 96,35 | 6766,95 | 0 | 0 | No |
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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