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Your team’s QA scores average 78%. Your operations head asks if that is good enough. You check with two industry peers and get two completely different answers. Welcome to the benchmarking problem that every BPO quality leader faces.
There is no universal standard for what constitutes a “good” QA score — and that is part of the problem. Benchmarks vary because QA scorecards themselves vary. One BPO might weight compliance at 40% and soft skills at 15%. Another might do the opposite. A score of 82% on a compliance-heavy scorecard for a collections process is not comparable to 82% on a customer satisfaction-focused scorecard for inbound support.
Scoring methodology matters too. Some centres use binary pass/fail criteria per parameter. Others use weighted rubrics with partial credit.
Then there is the sample size problem. If your QA team reviews only 2-3% of calls, those scores reflect a small, potentially biased sample. This is why leading BPOs are shifting toward 100% call auditing — not just for coverage, but for statistically valid benchmarks.
Despite the variability, enough data exists to establish useful ranges.
| Industry / Process Type | Good QA Score | Top Performer | Common Issue |
|---|---|---|---|
| Inbound Support | 75-85% | 90%+ | Soft skills scoring inconsistency |
| Outbound Sales | 70-80% | 85%+ | Compliance section dragging scores down |
| Collections | 65-75% | 80%+ | Regulatory script adherence |
| Technical Support | 70-80% | 85%+ | Resolution accuracy |
| Healthcare / Insurance | 80-90% | 95%+ | Compliance-heavy, zero tolerance |
Processes with strict regulatory requirements have higher baseline expectations. The gap between “good” and “top performer” is where most improvement opportunity lives.
Scorecard design. A 20-parameter scorecard with binary scoring will produce lower averages than a 10-parameter scorecard with partial credit.
Agent tenure. Teams with high attrition — common in Indian BPOs running at 40-60% annual turnover — will score 5-10 points lower than stable teams.
Language complexity. Multilingual processes with code-switching introduce evaluation challenges that affect scores.
Step 1: Baseline on full coverage. Audit 100% of calls for at least 30 days.
Step 2: Segment by process. Set distinct benchmarks for each process type.
Step 3: Focus on category-level scores. An overall QA score of 76% tells you little. Break it down by category.
Step 4: Track trend, not snapshot. A score of 75% improving by 2 points per month is healthier than a stagnant 82%.
Gistly Quotable: BPOs that audit 100% of calls using The 100% Coverage Model report benchmark accuracy improvements of up to 40% compared to sample-based QA programs.
Your QA score only means something if your measurement is reliable. Benchmark the process before you benchmark the number.
There is no single industry standard, but most BPOs target 75-85% for inbound support processes. Compliance-heavy verticals set higher thresholds at 80-90%.
For statistically reliable benchmarks, audit at least 20-30% of calls per agent per month. 100% call auditing eliminates sampling bias entirely.
Focus on the lowest-scoring categories. Build targeted agent coaching programmes around those gaps.
Ready to benchmark on 100% of your calls? See how Gistly audits every conversation →
Gistly audits every conversation automatically — compliance flags, QA scores, and coaching insights in 48 hours.