Marketing Analyst
Support data-driven decision making across the marketing team
What You Do Today
Answer ad-hoc analytical questions, build quick analyses, train marketers on data usage, advocate for data-driven culture
AI That Applies
AI enables self-service analytics for marketers, answers routine questions automatically, generates quick analyses
Technologies
How It Works
The system ingests campaign performance data — impressions, clicks, conversions, spend, and attribution signals across channels. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Marketers can get answers to routine questions without waiting for you. You focus on the hard analyses
What Stays
Asking the right questions, translating analysis into action, building analytical culture
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for support data-driven decision making across the marketing team, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long support data-driven decision making across the marketing team takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your CMO or VP Marketing
“What data do we already have that could improve how we handle support data-driven decision making across the marketing team?”
They set the AI investment priorities for marketing
your marketing automation admin
“Who on our team has the deepest experience with support data-driven decision making across the marketing team, and what tools are they already using?”
They know what capabilities exist in your current stack that you're not using
a marketing ops peer at another company
“If we brought in AI tools for support data-driven decision making across the marketing team, what would we measure before and after to know it actually helped?”
They've likely piloted tools you haven't tried yet
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.