Customer Churn Call Reason Analysis

This dataset provides detailed call log records linked to customer churn events, including call metadata, customer demographics, churn reasons, and resolution outcomes. It enables comprehensive analysis of why customers leave, how call center interactions influence churn, and supports the development of targeted retention strategies. The dataset is ideal for churn prediction modeling, root cause analysis, and customer experience optimization.

  • opened 5 times
  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Churn prediction modeling and risk scoring

Sample rows

preview · 8 of 65 rows · all 19 columns
customer_idstringcustomer_segmentstringcustomer_tenure_monthsintegerchurn_flagbooleanagent_idstringcall_idstringcall_datetimedatetimecall_duration_secondsintegercall_typestringchurn_datedatechurn_reason_codestringchurn_reason_descriptionstringresolution_statusstringcustomer_regionstringcall_topicstringfollow_up_requiredbooleanfollow_up_completedbooleancustomer_ageintegercustomer_genderstring
CUST10001premium34falseAGT001CALL200012024-03-04T10:12:18542inboundblankblankblankresolvedNortheastbillingfalsefalse41female
CUST10002standard21falseAGT003CALL200022024-03-12T15:24:08174outboundblankblankblankresolvedMidwesttechnical supporttruetrue28male
CUST10003basic15trueAGT002CALL200032024-01-16T13:56:46392inbound2024-01-20BILL01Disputed bill amount not resolvedescalatedWestbillingtruefalse36female
CUST10004standard8falseAGT004CALL200042024-02-06T09:33:2580inboundblankblankblankresolvedSouthaccount updatefalsefalse25female
CUST10005premium60falseAGT005CALL200052024-01-22T17:14:44623inboundblankblankblankresolvedMidwesttechnical supporttruetrue48male
CUST10006basic4falseAGT002CALL200062024-03-10T11:20:58259outboundblankblankblankunresolvedNortheastservice inquirytruefalse38unknown
CUST10007standard13falseblankCALL200072024-02-14T13:01:42120inboundblankblankblankresolvedWesttechnical supportfalsefalse31female
CUST10008basic9falseAGT003CALL200082024-02-17T16:25:03333inboundblankblankblankunresolvedSouthservice inquirytruefalse22male

What the 65 rows show

from the 65-row sample

Premium (customer segment) stands out: mean customer_tenure_months is 52.3, against 16.6 for the rest.

  • 18%churn_flag = true
  • 21median customer_tenure_months
  • 2call types
  • 3resolution statuses
  • 4customer genders
  • 7call topics
Mean customer_tenure_months by customer_segment65 rows
0408021.6standard26 rows10.2basic20 rows52.3premium19 rows
customer_tenure_months65 rows, in bands of 10
09181218127554204080customer_tenure_months →

Median 21, from 2 to 73.

agent_id60 rows with a value · 5 left blank
  1. AGT0027
  2. AGT0036
  3. AGT0056
  4. AGT0045
  5. AGT0014
  6. AGT2433
  7. AGT2372
  8. AGT2412
  9. AGT2392
  10. AGT2362
19 columns by typefrom the column list below
  • string 11
  • integer 3
  • date 1
  • datetime 1
  • boolean 3

Columns

19 columns in four groups
blueprint · 19 columns
columntypedescriptionexample
Text 11 columns
customer_idstringUnique identifier for each customeruniqueCUST10001
call_idstringUnique identifier for each call log entryuniqueCALL20001
call_typestringType of call (inbound or outbound)inbound · outboundinbound
agent_idstringUnique identifier for the customer service agent handling the calloptionalAGT001
churn_reason_codestringStandardized code representing the primary reason for churnoptionalBILL01
churn_reason_descriptionstringText description of the churn reason as provided by the customeroptionalService too expensive
resolution_statusstringStatus of the call resolution (resolved, unresolved, escalated)resolved · unresolved · escalatedresolved
customer_segmentstringCustomer segment or tier (e.g., 'premium', 'standard', 'basic')3 segments · optionalpremium
customer_regionstringGeographical region or market of the customer9 regions · optionalNortheast
call_topicstringMain topic or category of the call (e.g., billing, technical support, cancellation)7 topics · optionalbilling
customer_genderstringGender of the customermale · female · other · unknown · optionalfemale
Numbers 3 columns
call_duration_secondsintegerDuration of the call in seconds0 or more542
customer_tenure_monthsintegerNumber of months the customer has been with the company at the time of the call0 or more · optional34
customer_ageintegerAge of the customer at the time of the call0 or more · optional41
Dates and times 2 columns
call_datetimedatetimeDate and time when the call occurred2024-03-04T10:12:18
churn_datedateDate when the customer churned (null if not churned)optional2024-01-20
True or false 3 columns
churn_flagbooleanIndicates whether the customer churned after the call (true = churned, false = retained)false
follow_up_requiredbooleanIndicates if a follow-up action was required after the calloptionalfalse
follow_up_completedbooleanIndicates if the follow-up action was completedoptionalfalse

Use it for

  • churn flag18%12 of 65 rowsmean customer tenure …21.6standa…10.2basic52.3premium

    A telecommunications dashboard

    The churn_flag rate, customer_tenure_months by customer_segment and a breakdown of agent_id. Excel, Power BI or Tableau.

  • Why do the 19 premium rows have a mean customer_tenure_months of 52.3?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable customers with call_id, call_datetime and call_duration_seconds to fill a screen in front of a buyer.

Not quite right?

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This dataset65 rows19 columns
Yours1,000 rows19 columnscustomer_region: UK only

blueprint · customer-churn-call-reason-analysis

Behind this dataset

Same schema. As many rows as you need.

These 65 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Log churn call date and reason
  • Record customer ID and contract type
  • Flag preventable reasons (e.g. service issues)
  • Aggregate by churn reason category
  • Summarize churn rates monthly
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
customer-churn-call-reason-analysis

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