Subscriber Complaints and Case Management
This dataset provides a comprehensive record of customer complaint tickets in the telecommunications sector, including issue types, severity, resolution timelines, escalation paths, root cause analysis, compensation awarded, and customer satisfaction scores. It enables detailed analysis of service quality, operational efficiency, and customer experience, supporting both root cause identification and process improvement initiatives.
Sample rows
preview · 8 of 100 rows · all 13 columns| complaint_idstring | severitystring | compensation_awardedfloat | resolvedboolean | agent_idstring | customer_idstring | issue_typestring | complaint_datedatetime | resolution_datedatetime | resolution_time_hoursfloat | escalation_pathstring | root_causestring | csat_scoreinteger |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ABT9-4KLM | high | 15 | true | AGT756 | CUST3748 | network quality | 2024-04-10T15:22:00 | 2024-04-12T11:31:00 | 44.1 | frontline > supervisor | Network congestion in local cell | 6 |
| JZ7X9_PQ2B | medium | 5 | true | AGT342 | CUST1121 | billing dispute | 2024-03-27T10:12:00 | 2024-03-27T18:45:00 | 8.5 | frontline | Incorrect promo code applied | 9 |
| KLM49LZ9 | critical | 50 | true | AGT983 | CUST7822 | device issue | 2024-05-03T20:09:00 | 2024-05-08T12:02:00 | 112 | frontline > supervisor > manager | Device firmware failure | 5 |
| 7HVCF2QR | medium | 0 | true | AGT467 | CUST6723 | network quality | 2024-04-16T08:44:00 | 2024-04-16T16:20:00 | 7.6 | frontline | Temporary tower outage | 8 |
| QW8F2RTP | low | 2 | true | AGT453 | CUST2100 | billing dispute | 2024-04-19T11:03:00 | 2024-04-19T11:40:00 | 0.6 | frontline | Duplicate charge | 10 |
| B4GZ9KLM | high | 10 | true | AGT756 | CUST3748 | network quality | 2024-05-10T10:25:00 | 2024-05-11T09:40:00 | 23.2 | frontline > supervisor | Hardware fault in tower | 7 |
| ML9Q1PRT | medium | 0 | true | AGT610 | CUST4859 | device issue | 2024-04-29T13:34:00 | 2024-04-30T11:27:00 | 21.9 | frontline > supervisor | Battery defect | 8 |
| V0P8GZXR | low | 0 | true | AGT453 | CUST9900 | other | 2024-04-21T17:25:00 | 2024-04-23T10:15:00 | 40.8 | frontline | General inquiry | 10 |
| X9LK4-2RB | medium | 5 | true | AGT342 | CUST5981 | billing dispute | 2024-05-02T10:05:00 | 2024-05-02T13:50:00 | 3.8 | frontline | Late payment fee error | 9 |
| N1V8QZKL | critical | 30 | true | AGT983 | CUST7421 | network quality | 2024-04-30T22:10:00 | 2024-05-06T13:50:00 | 138.7 | frontline > supervisor > manager | Major fiber cut | 3 |
| PZ7RK8LQ | low | 0 | true | AGT610 | CUST2100 | device issue | 2024-04-08T08:15:00 | 2024-04-08T09:10:00 | 0.9 | frontline | Minor software bug | 9 |
| T2X1Q9LR | high | 15 | true | AGT756 | CUST9900 | network quality | 2024-05-05T15:30:00 | 2024-05-07T17:45:00 | 50.3 | frontline > supervisor | Intermittent signal loss | 6 |
| GZ8T1KLM | medium | 3 | true | AGT342 | CUST1121 | billing dispute | 2024-04-17T11:40:00 | 2024-04-17T12:35:00 | 0.9 | frontline | Misapplied tax | 10 |
| LZ8QK4TR | medium | 0 | true | AGT467 | CUST6723 | network quality | 2024-04-24T19:00:00 | 2024-04-25T09:50:00 | 14.8 | frontline | Software update delay | 7 |
| QK4TR7ZX | high | 20 | true | AGT610 | CUST4859 | device issue | 2024-03-31T16:18:00 | 2024-04-01T14:05:00 | 21.8 | frontline > supervisor | Screen malfunction | 4 |
| PRX1K7LM | low | 0 | true | AGT453 | CUST5981 | other | 2024-04-19T09:02:00 | 2024-04-19T10:01:00 | 1 | frontline | Inquiry on new plans | 10 |
| K5M1-QV7L | medium | 2 | true | AGT342 | CUST7421 | billing dispute | 2024-05-01T10:40:00 | 2024-05-01T12:55:00 | 2.3 | frontline | Auto-pay failed | 8 |
| S9LK4F2R | critical | 40 | true | AGT983 | CUST3748 | network quality | 2024-05-08T15:31:00 | 2024-05-12T17:40:00 | 98.2 | frontline > supervisor > manager | Major outage - fiber cut | 3 |
| V8R2W9LQ | medium | 5 | true | AGT610 | CUST6723 | device issue | 2024-04-15T14:15:00 | 2024-04-15T19:40:00 | 5.4 | frontline > supervisor | Hardware compatibility issue | 7 |
| P8R2X1TV | medium | 0 | true | AGT467 | CUST9900 | network quality | 2024-04-18T21:00:00 | 2024-04-19T13:00:00 | 16 | frontline | Temporary bandwidth reduction | 8 |
What the 100 rows show
from the 100-row sampleCritical severity stands out: mean compensation_
- 99%resolved = true
- 7.0median compensation_
awarded - 3escalation paths
- 4issue types
- 4.4median resolution_
time_ hours - 7median csat_
score
Median 7.0, from 0.0 to 60.0.
- string 7
- integer 1
- float 2
- datetime 2
- boolean 1
Columns
13 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
complaint_id | string | Unique identifier for each customer complaint ticketunique | ABT9-4KLM |
customer_id | string | Unique identifier for the customer submitting the complaint | CUST3748 |
issue_type | string | Type of issue reported by the customer (e.g., billing dispute, network quality, device issue)billing dispute · network quality · device issue · other | network quality |
severity | string | Severity level of the complaint (e.g., low, medium, high, critical)low · medium · high · critical | high |
escalation_path | string | Escalation path followed for the complaint (e.g., frontline > supervisor > manager)3 paths · optional | frontline > supervisor |
root_cause | string | Summary of the root cause analysis for the complaintoptional | Device firmware failure |
agent_id | string | Identifier for the customer service agent assigned to the complaintoptional | AGT756 |
| Numbers 3 columns | |||
resolution_time_hours | float | Total time taken to resolve the complaint, measured in hours0 or more · optional | 44.1 |
compensation_awarded | float | Monetary value or credits awarded to the customer as compensation (if any)0 or more · optional | 15 |
csat_score | integer | Customer Satisfaction (CSAT) score provided after resolution (typically 1-5 or 1-10 scale)1 to 10 · optional | 6 |
| Dates and times 2 columns | |||
complaint_date | datetime | Date and time when the complaint was submitted | 2024-04-10T15:22:00 |
resolution_date | datetime | Date and time when the complaint was resolvedoptional | 2024-04-12T11:31:00 |
| True or false 1 column | |||
resolved | boolean | Indicates whether the complaint has been resolved | true |
Use it for
A telecommunications dashboard
The resolved rate, compensation_
awarded by severity and a breakdown of agent_ id. Excel, Power BI or Tableau. Why do the 20 critical rows have a mean compensation_
awarded of 42.5? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Complaints100ABT9-4KLM15highJZ7X9_PQ2B5mediumCMP-5LK9TRVQ0critical
A software demo
Believable complaints with customer_
id, issue_ type and severity to fill a screen in front of a buyer.
This dataset100 rows13 columns
Yours1,000 rows13 columns
blueprint · subscriber-complaints-and-case-management
Behind this dataset
Same schema. As many rows as you need.
These 100 rows came out of a blueprint — 13 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
- Case/ticket ID unique identifier
- Subscriber MSISDN and customer account
- Issue type: billing error, network quality, device defect, service outage, fraud
- Severity: critical (service down), high, medium, low
- Channel: call center, retail store, web portal, social media, chatbot
- Creation timestamp and resolution timestamp
- First contact resolution (FCR) flag for efficiency metric
- Escalation: tier 1, tier 2, tier 3 technical support, executive escalation
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- subscriber-complaints-and-case-management