Marketing Analytics

Most marketing analytics tools are essentially dashboards looking for a question. The team logs in, stares at the numbers for a while, and walks away with a vibe rather than an answer. The actual decisions still get made anyway, mostly on instinct. Where to put the next dollar. Which channel is quietly decaying. Which segment is genuinely worth doubling down on.

The version of this work that's actually useful skips the dashboard entirely and surfaces the answer.

What we build

• Cross-channel attribution you'd actually defend. The system pulls from your ad platforms, GA4, CRM, and whatever else you're running, builds a model that fits your actual buyer journey, and reports the answer in language a CMO can take into a meeting.
• Anomaly detection. Flagging the spend that just stopped converting, the cohort that's falling off, or the campaign that's quietly outperforming, all before the next weekly meeting.
• Cohort and segment analysis. Real cohorts based on actual behavior, rather than the marketing tool's default segments.
• Budget recommendations. "Move this much from here to there," with the math sitting underneath it, rather than just a chart.

Where the AI actually helps

The pattern recognition across noisy, multi-source data, and the natural-language summary on top of that. The point being that your analyst stops functioning as a Tableau operator and starts being an analyst again.

What we won't do

Sell you another dashboard. The output here is a working analytics pipeline plus regular synthesis that you can actually act on. Get in touch.