Chicago · Marketing analytics · Paid media

I got tired of scrolling the Ad Library before every brief.

Mako Metrics is my answer to that afternoon. I spent six years inside Fortune 500 marketing teams and agency accounts, building dashboards and arguing about where the next dollar of ad spend should go. It started as a way to turn public Meta Ad Library data into a PDF you can brief from. It now runs the whole round: an agent that takes a client from that research to creative to a campaign built in the ad account, delivered paused for your approval.

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6+ years in digital marketing analytics · 4+ years on Fortune 500 marketing teams · 2 years in agency paid media · $100s of millions in ad spend managed and analyzed

Who Builds This

Hi, I'm Logan Riebel.

I'm a marketing analytics nerd based in Chicago. I like SQL more than I should, and I have strong opinions about how dashboards should be labeled.

For the last four-plus years I've been at ADP on the performance marketing analytics side: Tableau dashboards tied to Salesforce, media mix and multi-touch attribution pilots, bid tests, and budget conversations on enterprise-scale digital spend. Before that I was at Dentsu (iProspect) on two major telecom accounts, running incrementality work and 50+ A/B tests on large paid search programs. Earlier I freelanced under LR Marketing Analytics and spent a year and a half at OpGo Marketing managing client accounts and building Power BI reporting for paid channels.

That path matters for Mako Metrics. I've sat in the meetings where someone asks "what are our competitors running?" and everyone knows that means another hour in Ad Library. I built this so you get a structured read instead.

Have a question, or want to talk through a competitor before you buy? Email me directly at hello@makometrics.com.

Logan Riebel with friends at a beach event at night — Off the clock: still the same person who will nerd out about your competitor's ad mix.

Why Mako Exists

Competitor research should not live in screenshots.

Meta's Ad Library is public. The hard part is turning hundreds of ads into something a media buyer or strategist can use before the next creative review. We publish the method openly on the Mako blog, from Ad Library workflows to full competitor teardowns.

That research is now the front end of something bigger. May, our Meta ads agent, runs the whole round for agencies: the read on the category, the angles, the creative, and a campaign built in the ad account with tracking attached, delivered paused so a human approves it. The reports still sell on their own, because the read is worth having even if you build the creative yourself. See May, our Meta ads agent.

Structured, Not Scraped Chaos

Every order includes a PDF with the analysis and a ZIP with the ad files. We email you when the report is ready, and you download both from your portal at makometrics.com/portal.

Built by someone who reads dashboards daily

I've built governed models in dbt, shipped Tableau for GTM teams, and tested incrementality on real budgets. The analysis reflects how paid media people actually think about winners and losers.

Every number is traceable

Every figure in the report traces back to a real ad in Meta's Ad Library, and confirmed signals are clearly separated from inferred reads. You can verify anything we say.

How I think about it

A few rules I won't bend on.

Every claim in a report is backed by an ad you can go look at yourself.
Reports should answer "what should we test next?" not "here are 400 thumbnails."
If I can't explain a pattern in plain English, it doesn't belong in the deliverable.
AI helps me move faster on analysis and tooling. It does not replace reading the ads.

Where I've done the work

Fortune 500 teams, agency accounts, and client-side analytics.

ADP

Marketing Analytics Manager · 2022-present

Performance marketing dashboards, attribution pilots, and budget influence on enterprise paid media programs. Built agentic analytics on governed metrics (dbt, MetricFlow, Claude MCP).

Dentsu (iProspect)

Marketing Analytics Manager · 2021-2022

Incrementality testing and attribution for two telecom brands. 50+ A/B tests on bidding, creative, landing pages, and audiences on high-volume paid search accounts.

LR Marketing Analytics

Analytics Consultant · 2020-2021

Freelance Power BI work for healthcare and B2B software clients. Full-funnel dashboards, lead scoring overhauls, and geo-targeting tied to large monthly Google Ads programs.

OpGo Marketing

Performance Marketing Specialist · 2020-2021

Agency-side: 25 client accounts, consolidated reporting in Power BI, and hands-on optimization across a multi-account paid media book.

Tools I work in daily: SQL, Python, dbt, Tableau, GA4, GTM, media mix modeling, incrementality testing, and paid social. LinkedIn

Your competitor is already running ads. Your next round can start from that.

Run a client through May and get seven concepts and five creatives in about three minutes. Or buy the research on its own, delivered within 24 hours.

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