Complaints Resolved¶

Definition¶

Complaints Resolved refers to the number or percentage of customer complaints that have been successfully addressed and resolved within a given timeframe. This metric tracks how efficiently and effectively customer service teams are handling complaints.

Description¶

Complaints Resolved measures how effectively and efficiently your teams are addressing customer issues, offering a key signal of customer-centricity, support capability, and loyalty impact.

The relevance and interpretation of this metric shift depending on the model or product:

In SaaS and tech, it reflects how well your team handles product-related pain points
In DTC, it supports brand trust during returns, delays, or fulfillment gaps
In B2B, it aligns closely with renewal success and advocacy potential

A high resolution rate paired with positive outcomes suggests strong process maturity and customer empathy. A low or declining rate may signal under-resourced teams or broken workflows. Segment by complaint type, support tier, or time-to-resolution to improve effectiveness and customer outcomes.

Complaints Resolved informs:

Strategic decisions, like CS staffing, tooling investment, or process redesign
Tactical actions, such as real-time prioritization during peak periods
Operational improvements, including ticket triaging or agent training
Cross-functional alignment, by tying support performance to product, retention, and brand experience

Key Drivers¶

These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome

Support Team Empowerment and Triage Process: Fast routing and permission to act = faster resolution. Bureaucracy delays closure.
Clarity of Resolution Ownership: If no one “owns” the resolution — across support, product, or billing — complaints linger unresolved.
Follow-Up Communication Quality: Customers want closure, not just silence. How you communicate the fix matters as much as the fix itself.

Improvement Tactics & Quick Wins¶

Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.

If resolution rate is low, audit ticket routing and escalation paths — are the right teams seeing the right complaints?
Add automated “we fixed it” updates or resolution confirmations after issues are addressed.
Run a test offering direct escalation links for unresolved complaints after 48h, increasing resolution accountability.
Refine internal ownership playbooks so every complaint type has a clear primary and backup team.
Partner with support ops to set SLAs for complaint follow-up and closure, especially for VIP accounts.

Required Datapoints to calculate the metric
- Number of Complaints Resolved: The total number of complaints addressed and resolved.
- Total Complaints Received: The total number of complaints registered within the same time period.
Example to show how the metric is derived

A telecom company tracks complaints resolved in Q1:
- Complaints Received: 1,000
- Complaints Resolved: 900
- Resolution Rate = (900 / 1,000) × 100 = 90%

Formula¶

Formula

\[ \mathrm{Resolution\ Rate\ (\%)} = \left( \frac{\mathrm{Number\ of\ Complaints\ Resolved}}{\mathrm{Total\ Complaints\ Received}} \right) \times 100 \]

Data Model Definition¶

How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.

Complaints

cube('Complaints', {
  sql: `SELECT * FROM complaints`,

  measures: {
    numberOfComplaintsResolved: {
      sql: `number_of_complaints_resolved`,
      type: 'sum',
      title: 'Number of Complaints Resolved',
      description: 'The total number of complaints addressed and resolved.'
    },
    totalComplaintsReceived: {
      sql: `total_complaints_received`,
      type: 'sum',
      title: 'Total Complaints Received',
      description: 'The total number of complaints registered within the same time period.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'number',
      primaryKey: true
    },
    complaintDate: {
      sql: `complaint_date`,
      type: 'time',
      title: 'Complaint Date',
      description: 'The date when the complaint was registered.'
    },
    resolutionDate: {
      sql: `resolution_date`,
      type: 'time',
      title: 'Resolution Date',
      description: 'The date when the complaint was resolved.'
    }
  }
});

Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema

Positive & Negative Influences¶

Negative influences

Factors that drive the metric in an undesirable direction, often signaling risk or decline.
- Bureaucracy in Triage Process: Increased bureaucracy in the triage process can delay the resolution of complaints, leading to a lower Complaints Resolved Value.
- Lack of Resolution Ownership: When there is no clear ownership of the resolution process, complaints tend to remain unresolved, negatively impacting the Complaints Resolved Value.
- Poor Follow-Up Communication: Inadequate follow-up communication can leave customers feeling dissatisfied, reducing the effectiveness of complaint resolution.
- Insufficient Support Team Empowerment: Without the empowerment to make decisions, support teams may struggle to resolve complaints efficiently, decreasing the Complaints Resolved Value.
- Complexity in Resolution Process: A complex resolution process can hinder the speed and effectiveness of resolving complaints, negatively affecting the Complaints Resolved Value.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Efficient Triage Process: A streamlined triage process allows for faster routing and resolution of complaints, increasing the Complaints Resolved Value.
- Clear Resolution Ownership: When resolution ownership is clearly defined, complaints are resolved more efficiently, positively impacting the Complaints Resolved Value.
- High-Quality Follow-Up Communication: Effective follow-up communication ensures customer satisfaction and closure, enhancing the Complaints Resolved Value.
- Empowered Support Team: Empowering the support team to make decisions leads to quicker and more effective complaint resolution, boosting the Complaints Resolved Value.
- Simplified Resolution Process: A simplified resolution process enables faster handling of complaints, improving the Complaints Resolved Value.

Involved Roles & Activities¶

Involved Roles

These roles are typically responsible for implementing or monitoring this KPI:

Executive
Support Operations
Activities

Common initiatives or actions associated with this KPI:

Customer Support
Escalation Handling
Root Cause Analysis

Funnel Stage & Type¶

AAARRR Funnel Stage

This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:

Retention
Type

This KPI is classified as a Lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.

Supporting Leading & Lagging Metrics¶

Leading

These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.
- Ticket Volume: High ticket volume is an early indicator of customer issues or dissatisfaction. Increased tickets typically precede a higher number of complaints that need to be resolved, directly influencing the workload and efficiency of the complaints resolution process.
- Customer Satisfaction Score: CSAT provides immediate feedback on customer service interactions. Low CSAT often signals unresolved or poorly handled complaints, forecasting an increase in unresolved complaints and placing pressure on resolution efforts.
- First Contact Resolution: A high FCR indicates effective issue resolution on the first attempt, reducing the overall volume and complexity of complaints that require subsequent resolution. Poor FCR tends to lead to more unresolved complaints and follow-ups.
- Net Promoter Score: NPS is a forward-looking measure of loyalty and advocacy. A declining NPS often reflects underlying unresolved complaints and predicts future increases in complaint volume and the need for improved resolution.
- Customer Effort Score: High CES (i.e., customers experiencing high effort) indicates friction in the support process, which can lead to more complaints and lower resolution rates. Monitoring CES helps identify processes or touchpoints that, if improved, can enhance complaints resolved downstream.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Complaints Received: The number of complaints received is directly related to complaints resolved, as it defines the total workload and sets the upper bound for resolution rates. Trends in complaints received help contextualize resolution performance.
- Customer Churn Rate: High churn can be a consequence of unresolved complaints. Analyzing the relationship between complaints resolved and churn quantifies the broader business impact of complaint management effectiveness.
- Time to Resolution: The average time it takes to resolve complaints impacts customer satisfaction and can be used to assess the efficiency of the complaints resolution process. Longer resolution times often correlate with lower resolution rates.
- Customer Retention Rate: High resolution rates tend to improve retention; this metric confirms whether resolving complaints translates into actual business outcomes, such as customers staying with the company.
- Customer Downgrade Rate: A high downgrade rate can be linked to unresolved complaints or poor resolution quality, amplifying the business impact of ineffective complaint handling. Reviewing this relationship explains downstream financial effects.