The entry point
AI Readiness Audit
One week. We look at your stack, your workflows, and your data, then tell you where AI fits and what to do first.
Fixed scope. About one week from kickoff to deliverable. The written deliverable is yours to keep.
Fit
Who this is for, and who it isn’t.
Buy this if
- You run GA4, Adobe, or Tealium and you are not sure where AI actually fits in it.
- Leadership is asking for an AI plan and nobody internally owns the answer yet.
- Vendor demos are stacking up and you need a way to judge them against your own workflows.
- You suspect parts of your reporting are wrong and want to know that before you build on it.
- You are an agency that needs an independent read on a client’s stack.
Don’t buy this if
- You already know the problem and want it built. Start with a roadmap or an implementation instead.
- You want a vendor recommendation you can forward without reading. The output is a set of trade-offs, not a shortlist.
- You need someone to validate a decision that has already been made.
- Nobody on your side can give up two or three hours in the week for the walkthrough.
- You are looking for a model to be trained or fine-tuned. That is engineering work, not an audit.
Scope
What we look at.
Stack audit
We go through the tools you are paying for and the data underneath them — GA4, GTM, Adobe Experience Platform, CJA, AJO, Tealium, whatever else is in the stack. What is implemented, what is half-implemented, what is licensed and never switched on. Then we look at whether the numbers those tools produce hold up, because a model reading bad data just gets to the wrong answer faster.
Workflow walkthrough
We sit with the people doing the work and follow a few real workflows end to end. Reporting, campaign setup, QA, handoffs between teams. The point is to find the places where AI takes time out or lifts quality, and to be equally clear about the places where it would add a step and save nothing.
Gap analysis
We put the two together and mark the distance between where you are and where the workflows you care about need you to be. Data gaps, tooling gaps, ownership gaps, skill gaps. Each one gets a rough sense of effort and sequence, so the recommendations come out ordered instead of listed.
Deliverable
What you get.
One written document, walked through live before it is handed over. It is yours whether or not we work together after.
Stack audit of current tools and data
A written inventory of what you run, how it is configured, and where the implementation does not match what the tool is being used for. Includes the data-quality issues we hit while checking it.
Workflow walkthrough to find where AI saves time
The workflows we walked, annotated with where AI can take work out and roughly what that is worth in hours or in fewer errors. The ones not worth touching are marked as such.
Gap analysis with a prioritized recommendation list
The gaps, ordered. What has to be fixed before anything else can start, what can run in parallel, and what can wait. Each item names the thing to do, not a category.
A written deliverable you own, whether or not we work together after
The document is yours. Take it to your team, take it to another firm, or run it yourself. There is no clause that makes it ours and nothing in it is held back to force a follow-on engagement.
Sequence
How the week runs.
Fixed scope · about one week. Four steps, in order.
- 1
Kickoff
A short call to agree scope and pick the workflows we will walk. We ask for read access to the analytics and MarTech tools in scope.
- 2
Stack review
We work through the implementations on our own time and note what does not add up. No meetings needed from your side.
- 3
Workflow walkthrough
One or two working sessions with the people who run the day-to-day. This is the only real time commitment we ask of you.
- 4
Deliverable
The written audit and the prioritized recommendations, walked through live so questions get answered, then handed over.
Proof
What it looked like in practice.
Professional Services
Vendor demos were creating confusion, not clarity
Leadership wanted an AI strategy but had no internal expertise to evaluate options. Vendor demos were creating confusion rather than clarity.
80% team adoption in 60 days
AI readiness audit delivered a prioritized 90-day roadmap. Three AI tools selected and phased into operations. Team adoption tracked at 80% after 60 days.
FAQ
Questions about the audit.
If something here is not covered, ask it on the call. There is no deck to sit through first.
What does an AI readiness assessment involve?
A structured process that covers three areas: a stack audit of your current tools and data, a workflow walkthrough to identify where AI can reduce time or improve quality, and a gap analysis. The output is a short, prioritized list of specific recommendations. It takes about a week from kickoff to deliverable.
How long does a typical engagement take?
It depends on the service. An AI readiness assessment typically wraps in one week. A GA4 implementation or migration usually takes two to four weeks. AEP implementations run 90 days. Fractional product and staff augmentation engagements are ongoing, either sprint-based or on retainer.
How is pricing structured?
Project-based for defined-scope work (audits, assessments, implementations). Retainer-based for ongoing engagements (fractional PM, staff augmentation). We size every engagement to the specific scope and share pricing in the discovery call.
What if our data isn’t clean enough for AI yet?
That is the most common finding, and it is the reason the audit looks at your analytics implementation before it looks at AI tools. If GA4 or your CDP is producing numbers you don’t trust, fixing that is the first item on the roadmap. AI built on unreliable data produces unreliable output faster.
Who actually does the work?
The person you talk to is the person who does the work. There are no account managers, no handoffs to junior staff. Sam leads all AI consulting, Google Analytics, Adobe, and MarTech engagements. Crystal leads product strategy and fractional PM engagements.
How do we start?
A 30-minute discovery call. No pitch and no deck — a conversation about what you are running today and what you are trying to get to. If there’s a fit, the usual next step is the AI Readiness Audit, which is scoped and priced up front.
Start with the audit.
Thirty minutes to confirm the fit and agree scope. Pricing is fixed and shared on that call, before anything starts.
Book a Discovery Call