Savings methodology

AI deflection rate benchmarks (2026)

Industry × ticket-complexity deflection benchmarks compiled from public Salesforce, Gartner, McKinsey, Crescendo, and Zendesk reports. Citable Dataset, CC BY 4.0. Version v1.0-2026-04, last updated 2026-04-27.

What this dataset covers

Thirty industries × three ticket-complexity bands (simple, medium, complex) = 90 benchmark cells. Each cell is a deflection rate between 0 and 1, sourced from at least two of the five public reports listed below.

Use the numbers as a starting point, not a target. Your steady-state deflection depends on channel mix, knowledge-base coverage, and the maturity of your training data.

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Benchmark numbers (sortable)

Per-industry headline rates, alphabetised. Sources for each industry are inline in the methodology page; the full citation list is at the bottom of this page.

  • Agriculture — Simple 55% · Medium 25% · Complex 5%
  • Airlines — Simple 70% · Medium 35% · Complex 5%
  • Automotive — Simple 65% · Medium 32% · Complex 5%
  • B2B Services — Simple 60% · Medium 28% · Complex 5%
  • Banking — Simple 70% · Medium 35% · Complex 5%
  • Consumer Electronics — Simple 78% · Medium 45% · Complex 8%
  • Cybersecurity — Simple 55% · Medium 25% · Complex 5%
  • E-commerce — Simple 85% · Medium 55% · Complex 10%
  • Education — Simple 65% · Medium 30% · Complex 5%
  • Energy — Simple 65% · Medium 30% · Complex 5%
  • FinTech — Simple 78% · Medium 45% · Complex 8%
  • Financial Services — Simple 68% · Medium 32% · Complex 5%
  • Gaming — Simple 82% · Medium 50% · Complex 8%
  • Government & Public Sector — Simple 50% · Medium 20% · Complex 3%
  • Healthcare — Simple 55% · Medium 25% · Complex 3%
  • Insurance — Simple 65% · Medium 30% · Complex 5%
  • Legal — Simple 40% · Medium 15% · Complex 2%
  • Logistics — Simple 75% · Medium 40% · Complex 8%
  • Manufacturing — Simple 55% · Medium 25% · Complex 5%
  • Marketplaces — Simple 80% · Medium 48% · Complex 8%
  • Media & Entertainment — Simple 78% · Medium 45% · Complex 8%
  • Nonprofit — Simple 60% · Medium 28% · Complex 5%
  • Professional Services — Simple 55% · Medium 25% · Complex 5%
  • Real Estate — Simple 60% · Medium 30% · Complex 5%
  • Restaurants — Simple 85% · Medium 50% · Complex 5%
  • Retail — Simple 75% · Medium 45% · Complex 8%
  • SaaS — Simple 80% · Medium 50% · Complex 10%
  • Telecom — Simple 78% · Medium 45% · Complex 8%
  • Travel & Hospitality — Simple 72% · Medium 40% · Complex 8%
  • Utilities — Simple 70% · Medium 35% · Complex 5%

How the bands are defined

  • Simple — FAQ, account lookups, status updates, password resets, hours, basic policy questions.
  • Medium — bookable steps such as cancellations, refunds, address changes, scheduling, plan switches.
  • Complex — multi-system, judgement calls, regulated decisions, escalations that require human discretion.

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How to use the benchmarks

Pick your industry on the calculator and the deflection benchmarks are pre-applied. Override the channel mix and complexity mix if your numbers differ from the industry norm — the model recomputes live in the browser.

Citations

  • Salesforce State of Service 2025-2026
  • Gartner: AI in customer service 2025
  • McKinsey: Next frontier of customer engagement 2026
  • Crescendo CX Benchmarks 2025-2026
  • Zendesk CX Trends 2026

How to cite

buzzi.ai. (2026-04-27). AI Customer Support Deflection Rate Benchmarks (v1.0-2026-04). CC BY 4.0.

Retrieved from https://www.buzzi.ai/tools/de/ai-customer-support-savings-calculator/ai-deflection-rate-benchmarks

Try it on your numbers

Plug in your real volumes and see the projection.

The calculator runs the same methodology described above — channel modifiers, hidden costs, and the build-vs-buy verdict. Free preview without an email.

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Frequently asked

What licence is the dataset under?

Creative Commons CC BY 4.0. Cite buzzi.ai and the version number; otherwise free to redistribute or build on.

How are the numbers compiled?

Aggregated from public deflection ranges in the five cited reports, then normalised into per-industry × complexity buckets. We apply a 0.85 residual haircut downstream in the calculator (not baked into the table here).

Why is the complex band so low?

Multi-system, judgement, and regulated tickets remain the human-judgement frontier. AI assists triage and summarisation but completes resolution rarely without a human in the loop.

How often does the dataset refresh?

Quarterly. Each refresh re-runs the SaaS≥40% distribution gate and bumps the version. Change log lives on the methodology page.

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