A call quality audit sheet is only useful if it's built around observable behaviors, applied consistently across reviewers, and connected to a feedback loop that changes how agents perform. Most teams build theirs around generic criteria they found online and then wonder why QA scores don't correlate with customer satisfaction. This guide covers how to build a call quality audit sheet that produces consistent results, and what format choices matter most.

What a Call Quality Audit Sheet Needs to Include

Before formatting, get the criteria right. A call quality audit sheet covers three categories: compliance (did the agent follow required process steps?), communication (did the agent communicate clearly and professionally?), and resolution (did the agent actually solve the problem?).

According to ICMI contact center research, the most common failure in quality monitoring programs is criteria that are too vague to apply consistently. "Professional tone" as a criterion produces different scores from different reviewers. "Agent avoided sarcasm, interruptions, and defensive language" produces consistent scores.

What should a call quality audit sheet format include?

A call quality audit sheet format should include: agent name, call date, call ID or recording reference, evaluator name, scoring criteria with numeric weights that sum to 100%, space for transcript evidence on each criterion, an overall score, a required coaching action if the score falls below threshold, and agent acknowledgment. The format itself is less important than whether each criterion is written at the behavior level and whether reviewers know what "good" and "poor" look like for each one.

Building Your Call Quality Audit Sheet: Step-by-Step

Step 1: Define criteria at the behavior level

Write each criterion as an observable behavior. Instead of "empathy," write "Agent acknowledged customer frustration before explaining policy." Instead of "resolution," write "Agent confirmed the issue was resolved before ending the call."

Behavior-level criteria produce consistent scores across reviewers. They also make coaching conversations more specific: a supervisor saying "you didn't acknowledge frustration at the 2:30 mark" is more actionable than "your empathy score was low."

Step 2: Assign weights that reflect business priorities

Not all criteria are equal. Compliance criteria (required disclosures, identity verification) typically carry higher weight than tone criteria because the consequences of failure are higher. A typical weight distribution for a contact center QA sheet might allocate 30-40% to resolution, 20-30% to compliance, 20% to communication, and 10-20% to process adherence.

Whatever weights you choose, confirm they add to 100% and document the rationale. Reviewers who understand why compliance is weighted heavily apply it more consistently.

Step 3: Write context definitions for each criterion

The most common cause of reviewer inconsistency is undefined criteria. For each criterion, write what "excellent," "acceptable," and "needs improvement" looks like in practice. Include a transcript example for each level.

Insight7 uses a context column in its weighted criteria system, where each criterion includes descriptions of what "good" and "poor" look like with examples from actual calls. This is the same structure that produces consistent human scoring and is what the platform uses to calibrate AI scoring.

Step 4: Choose your format and delivery method

The most practical audit sheet formats for contact centers are:

  • Excel/Google Sheets: Easy to distribute, flexible for formula-based scoring, filterable by agent or date. Best for teams with fewer than 20 agents being manually reviewed.
  • QA platform with automated scoring: Insight7 and similar platforms apply your criteria automatically to recorded calls, generate per-agent scorecards, and surface patterns across 100% of calls rather than a sampled 3-10% according to Insight7 platform data.
  • CRM-integrated forms: Some teams embed QA forms in Salesforce or HubSpot as activity records. Useful for connecting QA scores to deal data but requires integration work.

Step 5: Calibrate before you score at scale

Before rolling out a new QA sheet, run a calibration session. Have three reviewers independently score the same five calls, then compare scores. Where scores diverge, the criterion definition needs refinement. Calibration should be repeated quarterly or whenever criteria are updated.

A Brandon Hall Group report on quality assurance in contact centers identifies calibration as the single highest-impact practice for improving QA consistency, more impactful than the format or platform used.

How do you create a call quality monitoring form in Excel?

To create a call quality monitoring form in Excel: set up a row for each call with columns for agent, date, call ID, and evaluator. Create one column per criterion with a numeric scoring scale (0-3 or 0-5). Add a formula row that calculates the weighted total. Use conditional formatting to flag scores below your coaching threshold. Add a notes column for transcript evidence per criterion. For multi-reviewer consistency, use a separate calibration tab with the same calls scored by multiple reviewers side by side.

Automating Call Quality Audits

Manual QA sheets have a ceiling: a team can review 3-10% of calls at best, which means most performance data never gets captured. AI-powered QA platforms apply the same criteria to every call automatically.

Insight7's QA engine scores each call against configured criteria, links every score to the transcript evidence that triggered it, and surfaces per-agent scorecards across all calls in the review period. When a score falls below threshold, the platform can auto-generate a coaching session targeting the specific criterion that failed.

Fresh Prints implemented this workflow and found that agents could "practice right away rather than wait for the next week's call" when the QA-to-coaching loop was automated.

If/Then Decision Framework

If your QA sheet produces inconsistent scores across reviewers, then the issue is criterion definition. Rewrite criteria at the behavior level and add "what good/poor looks like" context for each one.

If you are reviewing fewer than 10% of calls manually, then you are missing the performance patterns that drive coaching decisions. AI-powered QA covers 100% of calls with consistent criteria.

If your audit sheet format is working but coaching doesn't improve scores, then the problem is in the coaching workflow, not the sheet. Connect QA outputs directly to role-play practice sessions.

If you need an audit sheet that managers and agents can both use, then keep the format simple: one row per call, criteria columns with numeric scores, a weighted total, and a coaching action field.

FAQ

What should a call quality audit sheet format include?

A call quality audit sheet should include agent and call identifiers, behavior-level criteria with numeric weights summing to 100%, transcript evidence fields, an overall score, and a coaching action threshold. The format (Excel, PDF, QA platform) matters less than whether criteria are written at the behavior level and whether reviewers have calibration guidance.

How do you create a call quality monitoring form in Excel?

Create columns for agent, date, call ID, and evaluator. Add one column per criterion with a numeric scale. Use a formula to calculate the weighted total. Apply conditional formatting to flag scores below your coaching threshold. Add a notes column for transcript evidence. Run calibration sessions with at least three reviewers scoring the same calls before using the sheet at scale.

See how Insight7's call analytics platform applies your QA criteria automatically to every call and generates evidence-backed scorecards.