AI marketing consultant · New York City
Real examples of AI and automation I've built into marketing analytics teams.
Problems in paid media, from overspend to a sudden drop in conversions to a data feed that stopped loading, tended to surface in the weekly performance review, days after they started.
I built AI-powered monitoring that watched everything: spend, performance across channels, and the data ingestion underneath it all. Anything off was flagged straight to the team in Slack.
Issues were caught as soon as they happened instead of in the weekly review.
Weekly and monthly reports ate up analyst time every cycle, mostly on pulling and formatting the same numbers.
I automated the reporting end to end, so the numbers arrive ready to read.
Teams spent their time on what the numbers meant instead of putting them together.
Every new experiment started with a blank page: writing the hypothesis, choosing markets or audiences, and working out how long it needed to run.
I templated test plans and power analysis so each new test starts from a proven structure, and every test is sized to give a clear answer before a dollar is spent.
Faster test launches, and fewer tests that end inconclusive.
For B2B clients, finding the right conversations to join meant scrolling through posts by hand.
I built automated workflows that scout posts where a client's services could be a match and surface them for the team to act on.
The team spends its time on qualified opportunities instead of searching for them.
I'm Chelsea Cramer, an independent AI marketing consultant with 13+ years in marketing analytics. I help marketing teams build AI workflows and automation into their analytics, so problems get caught the day they happen and analysts spend their time on insight instead of upkeep.
Most marketing analytics teams don't lose time on hard analysis. They lose it on everything around it: pulling the same numbers every Monday, rebuilding the monthly deck, writing up each test plan from scratch, and finding out a data feed broke only when someone notices a strange number in a review.
That work repeats on a schedule and follows clear rules, which is exactly what AI workflows and marketing automation do well. Taking it off your team's plate means they move faster and put their judgment where it matters: what's working, what to change, and where the next dollar should go.
Teams usually bring me in when they want to:
Because I come from marketing measurement, from marketing mix modeling to incrementality testing, I build these workflows around the numbers that drive budget decisions, not just the ones that are easy to automate.
Common questions
An AI marketing consultant helps a marketing team decide where AI is worth using and then builds it into their day-to-day work. My focus is the analytics side: monitoring and alerts, automated reporting, testing workflows and research, built so the numbers stay accurate.
Start with work that repeats on a schedule and follows clear rules, like monitoring performance and data feeds, building recurring reports, or drafting test plans. Those are quick to automate, easy to check, and free up the most analyst time.
No. The goal is to take the upkeep off their plate, like pulling data, assembling reports and watching dashboards, so they spend their time on analysis and recommendations.
Every workflow is checked against the source data before it goes live, and anything that feeds a budget decision keeps a person reviewing it. Alerts are tuned so the team trusts them instead of tuning them out.
Usually not. I start with what your team already uses, such as your data warehouse, BI tool, Slack and any AI tools you already have, and only suggest something new when it clearly earns its place.
Work with me
A 30-minute call is enough to spot the first workflow worth automating and what it would take. I'm based in New York City and happy to meet in person.
Book a 30-min call