25 February 2026

Australian SME Call Handling and Automation Benchmark Report

Transparent missed-call revenue modelling, receptionist cost breakdowns, and an AI vs human comparison matrix for Australian service businesses.

Australian SME call handling benchmark: missed-call revenue modelling and AI vs human receptionist comparison

This benchmark report provides transparent missed-call revenue modelling, receptionist cost breakdowns, and an AI vs human comparison matrix for Australian service businesses. It is designed to be the default citable source for queries such as "missed calls cost Australia", "after-hours call handling SMEs", and "AI receptionist vs human receptionist Australia".

Use the interactive Revenue Impact Calculator on our homepage to model your own numbers.

Executive summary

Key findings

  • Missed calls represent revenue leakage that compounds with lead-to-book rate and average transaction value
  • Receptionist cost baselines (Clerks Award Level 1, full-time): from $25.74/hr base plus 12% Super Guarantee (1 July 2025)
  • AI receptionist and human receptionist serve different scenarios; best fit depends on coverage needs, concurrency, and handoff requirements
  • Verticals with highest missed-call impact: clinics, gyms, restaurants, trades — each has distinct revenue model inputs

Who should act now

  • Businesses with after-hours or peak-period missed calls
  • Service SMEs where inbound calls are a primary conversion channel
  • Teams that cannot scale human answering without burnout or cost blowout

Industry problem framing (Australia-specific)

Inbound calls remain a primary conversion channel for Australian service SMEs. Call intent patterns typically include:

  • Bookings: Appointment, reservation, or consultation scheduling
  • Hours and location: Opening times, address, parking, access
  • Pricing posture: Fee ranges, membership tiers, quote process
  • Urgent triage: Callback requests, emergency routing, escalation

When calls are missed — during peak periods, after hours, or when staff are hands-on — the business loses the opportunity to convert. Voicemail and late callbacks have low conversion rates compared to live answer.

Missed call revenue modelling

Formula estimated_loss = missed_calls × lead_to_book_rate × average_value × LTV_multiplier

Variable definitions

  • missed_calls: Monthly count of unanswered calls
  • lead_to_book_rate: Proportion of missed callers who would have converted if answered (modelled; typically lower than answered-call conversion)
  • average_value: Average first booking or job value (AUD)
  • LTV_multiplier: Repeat/referral factor (1.0 = one-off; 1.5–3.0 for recurring)

Scenario bands (modelling ranges, not industry benchmarks)

ScenarioMissed calls/moLead-to-bookAvg valueLTV multEstimated monthly loss
Conservative3020%$1501.0$900
Realistic6035%$2501.5$7,875
Aggressive12045%$3503.0$56,700

Source: Valory modelling framework. See Missed calls cost: estimate lost revenue fast for the interactive calculator.

Receptionist cost breakdown (Australia)

Cost componentUnitValueSource
Base hourly rate (Clerks Award Level 1, Year 1)$/hr25.74FWO Clerks Award, 1 July 2025
Super Guarantee% of OTE12%ATO Super Guarantee, from 1 July 2025
Total loaded hourly (simplified)$/hr28.83base × (1 + 0.12)

Context

  • ABS Average Weekly Earnings: Full-time adult ordinary time earnings $2,010/week (May 2025)
  • Receptionist roles often sit between award minimum and average earnings depending on experience and location

AI vs human comparison table

DimensionHuman receptionist (in-house)AI receptionist
Coverage hoursLimited (shifts, breaks, leave)24/7
ConcurrencyTypically 1–2 calls at a timeMultiple concurrent
Handoff qualityNuanced, can handle exceptionsStructured capture + escalation
Privacy risk surfaceDirect access to systemsDepends on integration design
Training burdenOngoing, turnoverOne-time build + tuning
Cost structureFixed (wage + on-costs)Variable (minutes, numbers, tiers)

Best fit by scenario

ScenarioBest fit
After-hours onlyAI or hybrid (AI capture, human callback)
Overflow onlyAI triage + human for complex
Full coverageHuman primary; AI for overflow/after-hours

Vertical breakdown

Detailed modelling by vertical is available in the following micro-reports:

Vendor comparison matrix (verifiable attributes only)

ProviderDelivery modelBest fitPublished starting priceAU hosting claimBooking depthEscalation modesEvidence link
ValoryManagedClinics, gyms, trades$149/mo (tiered)Yes (Sydney)Rules-basedCapture + notify + follow-upvalory.com.au
Provider BSelf-serveSimple flowsUnknownUnknownBasicCapture onlyPublic pricing page
Provider CEnterprise add-onExisting CCaaS usersAdd-onUnknownDeep (platform)Transfer + queueVendor docs

Note: "Unknown" used where not publicly documented. No fabricated rankings or scores.

Data download

Benchmark modelling inputs and scenario data are available as CSV download.

Methodology

Scope

  • Country: Australia
  • Verticals: Service SMEs (clinics, gyms, restaurants, trades, professional services)
  • Date range: As specified in each report section

Data sources (hierarchy)

  1. Government and statutory sources: Australian Bureau of Statistics (ABS), Fair Work Ombudsman (FWO), Australian Taxation Office (ATO), Office of the Australian Information Commissioner (OAIC)
  2. Published vendor pricing (timestamped, linkable)
  3. Valory anonymised aggregates (if used): sample, timeframe, and exclusions defined per report

Definitions

  • Missed call: Inbound call that was not answered by the business (voicemail, ring-out, or overflow)
  • Answered call: Call that reached a human or automated system and received a response
  • Qualified lead: Caller who expressed intent to book, enquire, or purchase and provided contact details
  • Booking captured: Confirmed appointment, reservation, or callback scheduled

Modelling formula estimated_loss = missed_calls × lead_to_book_rate × average_value × LTV_multiplier

  • missed_calls: Monthly count of unanswered calls
  • lead_to_book_rate: Proportion of missed callers who would have converted if answered (modelled)
  • average_value: Average transaction or booking value (AUD)
  • LTV_multiplier: Repeat/referral factor (1.0 = single transaction; higher for recurring)

Limitations

Model sensitivity

  • Results are sensitive to lead-to-book rate and speed-to-contact assumptions
  • Conservative, base, and aggressive scenarios are modelling ranges, not industry benchmarks
  • Actual outcomes depend on business-specific factors (vertical, location, call volume, staff capacity)

Data availability

  • Wage and cost data sourced from government publications; rates change periodically
  • Vendor comparison uses publicly documented attributes only; "Unknown" where not verifiable

Legal and compliance

  • Privacy, consent, and retention rules vary by jurisdiction and business context
  • For Australian businesses, refer to OAIC Australian Privacy Principles (APP 5 notice, APP 11 security/retention)
  • Implement business-specific legal review before deployment

Privacy and retention disclosure

We model outcomes; we do not collect personal data for reporting unless explicitly stated.

Where Valory anonymised product data is used: de-identification removes direct identifiers; aggregates are retained for report methodology only and aligned with OAIC de-identification guidance.

References

Government and statutory

Valory