Cleaning companies · Applied AI

For cleaning companies who want results in weeks, not a year-long transformation programme.

Every cleaning company business we've worked with has a different definition of "broken". AI personalisation only earns its keep when it solves the specific definition you'd give it on a bad day – which is why our first call is mostly listening.

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

Lay of the land

The two or three things that decide whether this works for cleaning companies.

  • Cleaning businesses run on recurring contracts and one-off quotes, both of which need fast, consistent follow-up to win.
  • Quote turnaround and scheduling reliability are what most decide whether a cleaning company keeps a client past the first job.
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How we build AI personalisation for cleaning companies.

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

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The outcome for cleaning companies

If we build the right slice first, cleaning companies feel the difference inside the first month. Conversion lift of 18-32% over generic site experiences.

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 Kiwi Dynamics, that drops to about 52.

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

Questions

FAQ

How quickly can we see something running?

Week three for a clickable internal demo against real data. Week six for a slice your team can actually use. We hold ourselves to those numbers because they're what stops a project drifting into "endless discovery".

What's the smallest engagement you'd take on?

A two-week paid discovery for cleaning companies that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

What's the realistic outcome for cleaning companies?

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 tools do you build AI personalisation on?

For AI personalisation we usually reach for Claude, Vercel Edge, Postgres, Klaviyo. We're tool-agnostic at heart – we pick what your cleaning company team can actually run after we hand the build over, not what looks good on a vendor sticker.

One reply, one direction.

We don't run sequences or follow-up automation. One useful answer, one decision on your side.

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Talk to us about this

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