Hi, I'm Abel.
I’m a social scientist figuring out how people interact with new things and new ideas. Check out my sample projects to get a sense of what this looks like across a variety of quant and qual methods.
As a co-founder of XandY I lead custom research studies to help clients find out why their users and target audiences do what they do (and how to change it). Using that data, I then design actionable strategies that make them more successful. Clients include billion-dollar companies, global nonprofits, and AI startups.
During my time as a scientist and professor, I published research on social psychology, behavioral science, public opinion, and communication strategy. I also led teams of junior researchers and taught courses on research methods, science communication, and data storytelling.
My research projects have been covered in the New York Times, The Washington Post, Reuters, ABC News, CNN, Forbes, LA Times, National Geographic, Rolling Stone, and others including The Onion.
Postdoc at Yale University | Ph.D. from UC Santa Barbara
Before my career as researcher, I was trying to make it on the professional beach volleyball tour (highest ranking #54).
Sample Projects
HERE’S SOME THINGS I’VE ENJOYED WORKING ON RECENTLY
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In this project, I lead a comprehensive custom study of consumer behavior and price tolerance for a large energy company so they could calibrate their bid for a development deal. Through a representative survey of energy consumers in their target market, our findings showed exactly how much consumers were willing to pay, and how different types of energy (onshore wind, offshore wind, solar, etc.) would impact public support for new builds.
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Here I led the analysis and reporting of an international market research initiative so our client (National Geographic) could understand how attitudes and behaviors about conservation—and about NGOs like themselves—vary across 12 countries (USA, Mexico, Brazil, UAE, Kenya, Indonesisa, etc). Using predictive modeling I was able to uncover the factors that are most strongly linked to key outcomes, and also how this underlying structure of influences differs widely across markets.
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Our client was launching a AI-powered tool to improve the contextual fit of digital ads (i.e., to make sure they show up in relevant, appropriate contexts), but needed feedback from marketing execs to understand their clients’ needs and preferences. I conducted dozens of interviews with these marketing execs to discover how to tailor this tool and its UX to best fit the needs and uses that were most important to these executives and their teams. By synthesizing the main themes and producing great data visualizations, I created an enduring resource that continues to guide their product strategy.
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In this project we crafted a digital ad campaign to resonate with a target audiences values and motivations. We pre-tested the videos (survey experiments, dial testing, etc.) and then after final editing and refinement they were launched as a digital ad campaign in 2 congressional districts in Missouri and Georgia. We randomly assigned half the zip codes to a treatment condition (got ads) and half to a control condition (no ads), and then used a representative survey to assess differences between the treatment and control. This field experiment showed a large persuasive effect of the campaign specifically in our target demographic.
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The decent election forecasts use polling data and the best forecasts also add in “fundamentals” (data about the current political landscape). But we decided we could be even more accurate by accounting for something that nobody else was looking at: information-seeking trends by internet users. Our thesis was that web traffic on informational sites (e.g., a candidate’s Wikipedia pages was a strong behavioral indicator of public interest that wasn’t being well-captured by the polling data (which only shows self-reported intentions, not actual behavior). By adding in this behavioral data, we were able to significantly improve upon the best election forecasts for dozens of elections. And our model had the largest advantage at times furthest out from election day when traditional polling models are at their weakest.
Plus, I get to build some great data visualizations:
First Principles
First Principles
Everything comes back to quality. There’s just no substitute for doing really good work that actually matters.
The user is king. Value is usually determined by how people respond. Success comes from making something useful.
There is only one (1) shortcut to mastery and unfortunately it is: fearlessly asking dumb questions.
Perfectionism unmasked is just fear of taking action. Leap and learn!
Uncertainty is your friend. Swim in oceans of unknowns and make good decisions anyway.
To the outside observer, your work and your play should be indistinguishable.
Your past self and your future self are politely demanding that you immediately stop thinking about them and focus on the present.
The secret sauce has always been: curiosity, imagination, kindness, and persistence.
You really can just do things.
Meme Bucket
