Nate Foulds

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

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.


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.


The power of research & data, combined

Research and data are two sides of the same coin in the digital world. Data excels at showing us what’s happening, at what frequency, among how many users, while research’s strengths are providing context and storytelling about why things are happening. Often, data provides triangulation for the insights we gather in qualitative research, which can be the difference between stakeholders getting on board with your learnings or discounting them as anecdotal. At other times, when data isn’t straightforward or without tradeoffs, research provides the color and clarity needed to make a decision. Combining research and data at every step of your product journey will help you move forward confidently and quickly.

Learn how to facilitate better collaboration between the research and data functions on your team. There are a number of strategies for coming up with the right types of questions to ask, the right way to translate research findings into data deep-dives and vice-versa, and the right deliverables to create a rock-solid argument combining both disciplines.

This workshop is for beginner and intermediate researchers, designers and product managers who work with data folks, or directly with data, as part of their roles. Note however, that experience working with data yourself is not a requirement!

By the end of this workshop, you’ll feel comfortable with:

  • Starting a collaboration with engineers, analysts or anyone else who works with data in your company
  • Identifying ways research can inform data deep-dives and vice versa
  • Using frameworks that combine both research and data to measure outcomes
  • Planning a strategy sprint where both disciplines work towards a shared goal
  • Using research and data to convince stakeholders to invest in your opportunity.

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