Phoenix 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.
AI personalisation designed around the way a Phoenix team actually runs.
Our goal is to give Phoenix businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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 you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI personalisation runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Phoenix businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI personalisation compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
What we keep seeing in Phoenix.
- Phoenix is one of the fastest-growing metros in the country, running on construction, semiconductors and a booming population - AI here means scaling a business as fast as the city around it.
- A major semiconductor manufacturing build-out, a construction boom keeping pace with population growth, and a services sector racing to keep up with both. Phoenix businesses want AI that scales without a hiring spree.
We work with teams across Phoenix: Downtown Phoenix · Scottsdale · Tempe · Chandler · Mesa · Glendale.
Talk to us about this →How we build AI personalisation for a Phoenix team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Phoenix business, so value lands before the build is finished. AI personalised CX.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Phoenix businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Phoenix teams
We'd call the engagement a success when Phoenix teams are using the system without thinking about us. 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
How fast could we have AI personalisation in production?
Eight to ten weeks for most Phoenix businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for Phoenix businesses 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.
Do you have proof this works for Phoenix businesses?
Direct case study: Conversion lift of 18-32% over generic site experiences. Happy to walk you through full numbers on a call.
What if our Phoenix doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI personalisation specifically, we typically run that work on Claude, Vercel Edge, Postgres, Klaviyo and assume messy starting conditions from day one.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.