Case studies

The problem, the fix, the result.

Three projects for Australian businesses, told from the owner's side. Client names are left out to protect their privacy.

Twenty minutes, no charge, no pitch. If it is not a fit, I will tell you and point you somewhere better.

Home services · About 40 staff

An AI "brain" for a home services company

The problem

The business ran on what a handful of long-serving people knew: how to quote, which jobs to turn down, what to tell an upset customer. New staff took months to get up to speed. Owners and managers spent their days answering the same questions, and answers varied depending on who you asked.

What we did

We gathered the business's know-how into one trusted source: pricing rules, job procedures, policies, past quotes, common customer questions, customer call transcriptions and meeting summaries. Then we built an AI assistant that every team member can ask in plain language, from the office or from a ute. It answers in the company's own way of doing things, shows where each answer came from, and flags anything it is unsure about for a manager.

What changed

  • New staff productive in 3 weeks instead of 3 months
  • 60% fewer "quick questions" interrupting managers
  • Quotes issued same day instead of 2 to 3 days later
  • Customers now get a consistent answer, whoever picks up

Home services · About 1,500 inbound calls a month

Call scorecards for a home services company

The problem

The phones were the front door of the business, and no one could see what happened behind it. Managers could listen to only a few calls a week. They did not know how many calls turned into bookings, which calls should have booked and didn't, or where upsells were missed. Coaching was based on gut feeling.

What we did

We transcribe every call and score it against what a good outcome looks like for that business.

  • Call scorecards: every call is graded, so the picture comes from all calls and not a sample.
  • Booking rate tracking: by rep, by job type and by time of day.
  • Missed upsell detection: it flags the moments a rep could have offered a service plan, a second job or an upgrade.
  • Coaching for each role: CSOs, DSRs, dispatch officers and reps each get feedback on their own part of the job, and team leads get a short weekly list of what to work on.

What changed

  • 100% of calls reviewed, up from about 2%
  • The business now knows exactly which calls should have booked, and why the ones that didn't, didn't
  • Booking rate up from 58% to 71% in four months
  • About $14,000 a month in upsells captured that were previously missed
  • Reps get better every week, with 15-minute coaching sessions based on real calls instead of opinion

Professional services · 12 staff

Social media and blog content automation for a professional services company

The problem

The partners knew they should be publishing. Their expertise was the reason clients hired them. But content depended on whoever had spare time, so it came in bursts and then stopped for months. An agency was quoted at a cost that made no sense for the size of the firm.

What we did

We set up a content engine that turns what the firm already knows into steady publishing. The partners spend a few minutes a week giving their view on a topic or answering a client question. The system turns that into a blog article and a set of social posts in the firm's voice. A person approves everything before it goes out.

What changed

  • From 1 post a month to 5 to 7 a week
  • Partner time on content down from about 6 hours to 30 minutes a week
  • Website visits from search up 45% in six months
  • Costs a fraction of the agency quote

Some of the organisations I have worked with

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