Nate Foulds

Nate Foulds
  • Product researcher at Instagram
  • New York City, USA


Scaling signals: using qualitative research to influence algorithms

At Instagram, we use research to find signals in the wild - about people’s backgrounds, behaviors, likes and dislikes - that can be incorporated into the algorithms we use to deliver content.

A few years ago, Instagram launched its algorithmically sorted Feed to the outrage of many users who preferred the chronological version. In data, however, we saw that instead of missing out on content, the ranked Feed actually increased the percent of posts people consumed from their friends and family. In both Feed and Stories, two of the most highly consumed surfaces in the world, it’s crucial that we deliver the right content to the right people at the right time.

In this talk you’ll learn about how qualitative research is leveraged to improve the strength of the algorithms that power Feed and Stories. For instance -- how can we predict which friends’ content is most appealing to you? We use ethnography, interviews, diary studies and more to gain insight into the signals that matter. Using these signals, researchers work with engineers to boost levers in the algorithm and test their hypotheses. By the end of this talk you should have ideas for how you can uncover your own signals and measure their impact in the wild.


Nate is a NYC-based design researcher currently leading research for Instagram’s Stories feature. Over the past 8 years, he’s worked in a number of related disciplines, from data to design, and found research to be his true passion. Before Instagram, Nate led research on the news experience at The New York Times and comes from an agency background. He’s known for his out-of-the-box research methods and enthusiasm for taking digital products through the entire development process.