AI implementation
AI implementation for marketing teams
AI that runs on clean marketing measurement.
Build the observation layer, then automate the work that should never be manual.
What you get
Automation is only as good as the numbers underneath it. The work starts with measurement, then moves to the recurring tasks your team should not be doing by hand.
Measurement finance can trust
Tracking, data plumbing, and reporting definitions that hold up when finance asks how a number was built.
Assistants that run the recurring work
Assistants that draft, check, and ship recurring marketing analytics under your rules, with a person approving what goes out.
A working product when a tool is right
When the job calls for software, I build it. SearchMaster is one example: a live product, not a slide.
Curious how I run my own work this way? See the assistants I use day to day.
Who this fits
Brands and agencies running direct mail, paid search, or analytics operations who want fewer manual reports and numbers they can defend.
- Recurring reports that take hours and still get questioned
- Paid search or direct-mail spend without clean measurement
- Data spread across platforms that never quite reconcile
- A team ready to hand repeat work to an assistant with clear rules
Try it
See how AI search ranks you vs competitors
Enter your company and see where you show up in AI answers next to the brands you compete with.
Measurement in practice
Paid search case study: Catholic e-commerce and online education
A 12-month paid search and keyword optimization engagement for Matthew at CatechismClass.com, measured on revenue and return, not clicks alone.
Past customer example. Results vary.
Start with the measurement, then automate
A short call to map what you measure today, what is still manual, and where an assistant or tool would pay for itself.
Book an AI scope call