I saw a strategist in an account supervisor others had typed as client service. I moved her into Adaptive Audience, built her training around the platforms, testing and dashboards, and pushed her into new business and conference talks. She went on to lead all Adaptive Audience account services and pitch it in her own voice.
Insights, intelligence and marketing effectiveness
Leaders have more data than answers. I build the teams and systems that close the gap.
For more than 20 years I've turned competitive, media and customer data into decisions executives can use, most recently as VP, Media Intelligence at Innocean USA, Hyundai Motor Group's in-house agency.
This page is the overview. The full cases include client names and results, so I share them privately with recruiters and hiring teams. Once approved, you browse on your own with a one-time email code. Request case-study access →
Innocean USA 2023–26 · Mindshare 2019–23 · Hearts & Science 2017–19 · POSSIBLE 2015–17 · Sq1 and Adaptive Audience 2011–15 · ZAAZ 2009–11 · Vertis 2008–09 · in-house at SuperPages, Cox Communications and Tyler Junior College 2001–08
See the full career map →Twelve case studies: public summaries
Each summary gives the business question and my role. The full cases cover what we built and what leaders did with it; because they include client names and results, I share them privately with recruiters and hiring teams.
Insights and intelligence
The intelligence behind an automaker's weekly decisions
A competitive-intelligence system for three brands, built for a year of fast-changing market conditions.
My roleLed the team that built it; it fed the brands' weekly leadership reviews.
Teaching an AI analyst to reason like one
The Brain: governed data, 50+ industry guides and executive briefs in minutes instead of days.
My roleBuilt the first prototype and designed its industry guides, then ran point as the team built it out.
A challenger brand against long-established rivals
Competitive reads that turned share-of-voice tracking into recommendations leaders acted on.
My roleMy team produced the weekly reads; I led the method and the recommendations to marketing leadership.
The Competitive Scorecard
Rank, weight, gap: one method I've used at five employers to put a brand against the rival that matters.
How it's usedA one-page read of where a brand stands against the rival that matters, adapted at each employer.
Measurement and decision science
Proving fuel ads still worked
A linked brand-and-sales model that showed leaders what media contributed and where to move budget.
My roleClient owner, project lead and primary presenter; led the model refreshes with data scientists.
A head-to-head test for a university
Machine-learning targeting and creative scoring, tested head to head.
My roleOriginated the performance and creative models; ran analysts from Neo (a WPP performance agency) and Mindshare's data scientists as one team.
Measuring what media was really worth
Eye tracking for creative, holdout reads and new attribution models across three lines of business.
My roleLed marketing sciences with a bi-coastal team of 10.
Adaptive Audience: connecting digital media to in-store sales
The privacy-first measurement business I co-founded, from first client to acquisition.
My roleCo-founder and president; the business contributed to Sq1's 2015 acquisition by Ansira.
Products and customer experience
Four machine-learning modules, priced, sold and renewed
The Synapse product line I ran as business lead, from pricing to roadmap.
My roleBusiness lead for pricing and roadmap; my Los Angeles team built the modules.
Four kinds of buyers, one winning page
Pages written for how shoppers decide, screened by archetype and proven in live tests.
My roleCreated the archetype framework, owned the roadmap and ran the tests.
One testing standard for seven markets
A global testing program built to answer a category-defining rival, market by market.
My roleRan the A/B testing program across seven markets.
Selling digital ads inside a directory spin-off
Business-model research, product pages and a statement built from each advertiser's account.
My roleIn-house on the digital team: business-model research, product pages and the email programs.
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Intelligence built for the people deciding
I started as a designer, so I build intelligence people can read and use: one-page scorecards, monthly reads for a CMO, briefings an AI analyst drafts in minutes.
Start with the decision
"Who will decide with this?" is still my first question. Analytics counts when someone acts on it.
Research throughout
Business-model research and A/B testing in-house, then usability and testing at every agency since. Watch real people, then ask why.
Hands-on, then leading
I build forecasting models myself and lead the machine-learning work. Engineers own production code; I own the question, the method and the story.
Readable in a minute
If an executive can't read it in a minute, it isn't done. Design is part of the analysis, not a finish on top of it.
Building the people who run the work
I get into the trench with my team, push each person to find their own angle on the work, and believe the community around the work shapes the work.
I built every report hands-on with my first three analysts, all early in their careers, then gave each one a brand. They became the competitive-insights leads for each brand's leadership, and I promoted one to senior analyst.
One analyst pushed back on our AI platform because he preferred another tool. Instead of overruling him, I had him build a balanced comparison of the tools, the governance limits and the pilot use cases. His comparison won broader support from analytics leadership.
I ran analysts from Neo (a WPP performance agency) and Mindshare's data scientists as one team with one view of the client. After about a year, leadership approved expanding that pooled model across the office.
Three more leadership stories
One of my data scientists was brilliant and quiet. Instead of telling him to speak up more, I started a monthly lunch-and-learn and asked him to help run it. He took it over, and it grew into an agency-wide forum.
I hired a PhD engineer with deep data-science skill and little agency experience. He taught me machine learning, and I taught him client management and executive presentation. He went on to lead econometric modeling of his own.
I hired a specialist for search. He saw the testing work, asked to learn it, and I taught him. He ran the testing practice after I left and later stepped into my next role.
What teams and colleagues say
Brandon was a great manager who exemplified lead by example… getting different teams to achieve a common larger goal for the organization.Data scientist who reported to me · Hearts & Science · 2019
Brandon's ability to get groups working together across multiple departments… while always remaining calm, thoughtful and practical is an extremely valued talent.Colleague · Sq1 · 2014
I was impressed by his guidance, mentorship, and innovative mind… I fully trusted and respected him as a leader.Team member who reported to me for three years · Sq1 · 2014
Relocating to the Seattle area, open to remote
I'm looking for an in-house role in insights, intelligence or marketing effectiveness. If you're hiring, or know someone I should meet, I'd welcome a conversation. Not connected yet? Send a request with a short note.