← Back to all posts

Fixa Trade Automation

The Real Cost of a Missed Call for Tradies: Most Are Customers You've Never Met

Fixa Team9 Oct 20269 min read

A missed call at a trade business is usually treated as a minor annoyance, the kind of thing you deal with between jobs. New Australian call data suggests that's the wrong read: across nine trade and home-service industries, nearly seven in ten inbound calls come from someone who has never called that business before, so a missed call isn't a missed chat with an existing client. It's very often a new customer who rang once, got nothing, and moved to the next name on the list.

That finding comes from the AIIMS Group's inaugural Australian SME Lead Response Report, covered by Dynamic Business on 28 August 2026. It's worth treating as a genuine data point rather than a marketing stat, with one honest caveat up front: AIIMS sells phone automation and marketing services, so the report is drawn from its own client base rather than an independent industry census, and it's also a pitch for AIIMS's own product. The underlying numbers are still specific and checkable, which is more than most "missed calls are costing you money" content in this category offers.

What Australia's Missed-Call Data Actually Shows

The report analysed more than 207,000 inbound calls across 858 client businesses in nine industries. Two figures matter for a trades business running on ServiceM8:

  • 9.2% of inbound calls go unanswered on average across the nine industries measured.
  • 69.3% of all inbound calls, across every industry in the study, come from first-time callers: people who have never phoned that business before.

Those two numbers compound. A dropped call isn't just a 1-in-11 event; most of the time, it's a 1-in-11 event happening to someone who has no existing relationship with you to fall back on. An existing client who can't get through might text, email, or try again tomorrow. A first-time caller usually doesn't. They ring the next business that shows up in their search instead.

flowchart TD A["📵 Missed call"] --> B["🙋 69.3% are first-time callers"] B --> C["📉 No existing relationship to fall back on"] C --> D["🏢 Most ring the next business instead"] style A fill:#e34948,stroke:#e34948,color:#ffffff style B fill:#eb6834,stroke:#eb6834,color:#ffffff style C fill:#4a3aa7,stroke:#4a3aa7,color:#ffffff style D fill:#2a78d6,stroke:#2a78d6,color:#ffffff

A missed call for a trade business is disproportionately a lost acquisition, not a lost conversation with someone you already know.

The Industries Where Missed Calls Hurt Most

The 9.2% average hides real spread between trades. The report named four industries specifically:

Industry Call drop rate
Flooring 17.9%
Roofing 17.6%
Pest control 5.1%
Solar 1.8%

The other five industries in the nine-industry sample weren't named in the coverage available, so this table only lists what's been publicly disclosed. That's worth flagging rather than guessing at the rest. Locksmiths weren't given a drop rate either, but they posted the highest first-time-caller share of any trade in the study at 82.2%, which tracks with how that trade actually works: almost nobody calls a locksmith they've used before unless they're that unlucky.

Flooring and roofing sitting at roughly double the average is a plausible pattern for project-based trades with irregular inbound volume: a storm front or a reno boom can flood the phone for a week, and anyone without 24/7 coverage simply can't keep up with the surge on top of a normal day's jobs.

Why a Missed Call From a New Customer Costs More Than You Think

For contrast, Chime Labs, Fixa's closest direct competitor by ICP and product shape, has put its own, separately-sourced number on the scale of this problem. Per Forbes Australia's coverage of Chime Labs' $900,000 pre-seed raise, the Sydney startup's own back-of-envelope estimate is that Australian tradies collectively miss around 270,000 calls a day. That's the company's internal maths, not an audited figure, same as the AIIMS number above. Two different vendors, two different methodologies, both landing on "this is a real and large problem" rather than a rounding error.

What neither number tells you on its own is what a missed call is actually worth to your business. That depends on your call volume, your close rate, and your average job value, and it's a calculation worth running with your own numbers rather than a national average.

A Worked Example: What a Missed Call Costs One Solo Trade Business

Take a solo electrician or plumber taking a fairly ordinary 40 calls a month, well within range for a one-person operation on Fixa's Solo plan. This is an illustrative scenario built from the industry figures above, not a measured result from a real Fixa customer. Fixa is pre-revenue, and nothing in this post represents an actual customer or case study.

Run the AIIMS averages against that volume:

  • 40 calls × 9.2% drop rate ≈ 4 missed calls a month.
  • Of those 4, 69.3% are first-time callers ≈ roughly 3 new-customer calls missed every month, or about 33 a year.
  • If even a third of those 33 would have converted into a job at a conservative $280 average callout (a hypothetical, illustrative figure, not a Fixa-measured number), that's roughly $3,080 a year in work that never made it to a job card.

Set that against what it costs to stop it happening. Fixa's Solo plan is $29/month (AUD, ex GST) with 25 calls included, running up through $0.55 down to $0.40 per call in overage beyond that. At 40 calls a month, this business would be paying roughly $29 plus overage on the extra 15 calls, call it $45-50/month, or around $550-600 a year: well under the $3,080 in illustrative recovered job value above. The gap doesn't need the exact numbers to hold. It needs the ratio to hold, and the ratio is large enough to survive being wrong by a fair margin in either direction.

flowchart TD A["📞 Call comes in"] --> B{"Answered in the first few rings?"} B -- "No" --> C["🚪 Caller gets voicemail or nothing"] C --> D["📉 ~69% have no history with this business"] D --> E["➡️ Most call the next business instead"] B -- "Yes, 24/7" --> F["🗂️ Job written into ServiceM8 as a job card"] F --> G["📲 SMS confirmation sent to the customer"] style A fill:#2a78d6,stroke:#2a78d6,color:#ffffff style B fill:#4a3aa7,stroke:#4a3aa7,color:#ffffff style C fill:#e34948,stroke:#e34948,color:#ffffff style D fill:#e34948,stroke:#e34948,color:#ffffff style E fill:#e34948,stroke:#e34948,color:#ffffff style F fill:#1baf7a,stroke:#1baf7a,color:#ffffff style G fill:#1baf7a,stroke:#1baf7a,color:#ffffff

The branch point isn't whether the business is good at the job. It's whether anyone, or anything, picks up before the caller gives up and tries somewhere else.

Where an AI Receptionist Like Fixa Fits

This is specifically the gap a 24/7 AI receptionist is built to close. Fixa answers every call around the clock, wired directly to ServiceM8, and writes what it learns straight into a job card, not a voicemail transcript someone has to action later and not a message queue. ServiceM8's own Office Agent, by contrast, is explicit about what it covers. Per ServiceM8's help centre documentation, Office Agent drafts quotes, invoices, and follow-ups and prepares bookings and Diary notes for approval, all of it working on a job that already exists in the system. Nothing in that feature set answers the phone. The 69.3% of calls in the AIIMS data that come from someone with no job in the system yet are exactly the calls Office Agent can't touch, because there's nothing for it to work from until something answers the phone first.

That's the design target behind Fixa's architecture, not a claim about measured containment or answer rates, which Fixa doesn't have data on yet as a pre-revenue product. It's the specific reason the product exists at the point in the pipeline it does: before a job card, not after one.

FAQ

What exactly counts as a "missed call" in the AIIMS data?

The report defines it as the drop rate across inbound calls logged for its client businesses: calls that didn't get picked up, as distinct from calls that were answered but didn't convert. It's a measure of phone coverage, not sales skill.

Why does it matter more that a missed call is from a first-time caller specifically?

An existing customer usually has another way to reach you or a reason to try again: a technician's direct number, a text thread, familiarity with how your business runs. A first-time caller has none of that. If the call doesn't connect, there's no relationship pulling them back; they just try the next search result.

Does Fixa answer every call, even during a surge in volume?

Yes. Answering calls around the clock, independent of how many arrive at once, is the core function Fixa is built around, and it scales with Fixa's plan tiers (25 calls on Solo up to 600 on Enterprise) plus per-call overage beyond the included allowance, rather than capping out the way a single human receptionist physically would.

What happens to a call once Fixa answers it?

It's written directly into ServiceM8 as a job, not handed back as a transcript or a message for someone to re-enter manually. That's the specific mechanism this post is pointing at when it talks about first-time callers "making it to a job card."

Do I need ServiceM8 to use Fixa?

Yes. Fixa's call-to-job-card workflow is built specifically around ServiceM8's API, alongside Outlook, Gmail, Google Calendar, and Sheets for scheduling and admin. It isn't a generic call-answering tool bolted onto an arbitrary FSM platform.

The Bottom Line

  • The average Australian trade business misses close to 1 in 10 calls, and roughly 7 in 10 of all inbound calls, missed or answered, come from someone calling for the first time.
  • Flooring and roofing businesses in the AIIMS data drop calls at close to double the cross-industry average; solar and pest control sit well below it.
  • A missed call from a first-time caller has no relationship behind it pulling the customer back, unlike a missed call from someone who already knows you.
  • Running your own call volume through the ratios above, rather than trusting a single national average, is the more useful exercise than memorising the 9.2% figure itself.

Sources