AI personalisation designed around the way a Logan team actually runs.

Logan sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI personalisation template would catch.

What AI personalisation actually does

Every customer sees the right product, message, and offer - based on what they've bought, browsed, and asked. Built on first-party data, no creepy tracking required.

  • 01 Per-customer recommendations across web and email
  • 02 Dynamic landing pages tailored to traffic source
  • 03 Lifecycle messaging triggered by real behaviour
  • 04 GDPR + NZ Privacy Act compliant by default

Built on: Claude Vercel Edge Postgres Klaviyo

What we keep seeing in Logan.

  • Logan is trades, logistics and light manufacturing between Brisbane and the Gold Coast, with one of the most diverse populations in the country.
  • A dense band of transport, warehousing, manufacturing and home services businesses serving two capitals at once. Multilingual customer contact and after-hours enquiries are both bigger factors here than the numbers suggest.

We work with teams across Logan: Logan Central · Springwood · Beenleigh · Browns Plains · Meadowbrook.

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How we build AI personalisation for a Logan team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Logan business, so value lands before the build is finished. AI personalised CX.

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The outcome for Logan teams

The shape of the result for Logan teams: Conversion lift of 18-32% over generic site experiences. Built on Claude, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Koala Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Koala Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

What's the realistic timeline for AI personalisation with a Logan?

Most Logan businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".

Is AI personalisation worth it for a smaller Logan?

Often, yes - and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.

What's the realistic outcome for Logan businesses?

Conversion lift of 18-32% over generic site experiences. We don't promise tenfold lifts because we don't see them outside of marketing decks.

What happens if we want to swap a vendor out later?

AI personalisation is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Claude, Vercel Edge, Postgres, Klaviyo are our defaults, but the build is intentionally portable.

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We'll map your real workflow before quoting anything.

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Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.