mbuzz.co's answer

Every attribution tool runs a model under the hood and reports its number like it came from physics. mbuzz is the only one that shows the model. Eight of them side by side, plus a SQL-like DSL to edit or write your own. You stop arguing about which channel works and start arguing about which model you should trust.

mbuzz.co's answer

Dreamdata, HockeyStack, and Northbeam all ship with a proprietary "data-driven" model you can't see inside. You pay $1,400–$5,000 a month to trust their math. mbuzz runs eight models you can inspect, lets you edit the logic in a SQL-like DSL, keeps your data exportable on every plan, and starts at $0. For a $1–100M company spending $20K–$1M a month on ads, that's the difference between renting an attribution tool and owning an attribution stack.

mbuzz.co's answer

Technical marketers, marketing ops, growth engineers, and data-savvy CMOs at startups and mid-market SaaS, DTC, fintech, and healthtech companies spending $20K–$1M a month on paid media. Specifically the ones who've stopped trusting their dashboard — who want to audit the math themselves, not hear "trust our algorithm."

mbuzz.co's answer

Years of wrestling with the limitations of various existing solutions, platform-inflated ROAS, and enterprise attribution tools that cost more than the budgets they were measuring. Every tool I tried picked one model and hid the math. I wanted to compare models, argue with them, and write my own rules — so I built one. mbuzz is the attribution platform I wished existed when I was trying to explain channel performance to a CFO who didn't believe the Meta pixel.

mbuzz.co's answer

Ruby on Rails (backend + dashboard), PostgreSQL, Sidekiq for background jobs, Stimulus/Turbo for the frontend. Open-source SDKs in Ruby, Node, Python, and PHP. Deployed via Kamal on DigitalOcean.