How Amazon is leveraging researcher-driven AI for hybrid Quant + Qual research

The challenge

• As the senior UX researcher on Amazon's Apps & Games team, Sarah Kling has a ton of key questions to answer for cross-functional stakeholders across UX design, product, marketing, business development, and more.
• In Q2 of 2024, Sarah and her small team needed to scale their capabilities as the mountain of asks from other teams grew larger.
• Sarah launched a search for a tool that could:
  • Expand Amazon's research capacity
  • Accelerate speed to insight
  • Evolve their research toolkit

The solution

"Last summer, we ran pilot projects and compared multiple vendors," said Sarah. "We considered factors like research quality, platform usability, and vendor support."

A number of the tools Sarah and her team tested required significant manual effort across study design, execution, and analysis. She knew these tools wouldn't be enough to increase her team's research capacity or accelerate speed to insight.

Then, Sarah discovered Knit.

• Knit's AI automates tasks across the research lifecycle, so Sarah and her team can do more research in less time. They don't have to spend time on survey creation, data analysis, or reporting. Plus, with quant + qual in a single survey, they get a complete, nuanced picture of consumers in half the time.
• With end-to-end efficiencies across fielding, sampling, and analysis, Sarah can reduce operating expenses associated with research.
• Most importantly: because Sarah and her team spend way less time on execution, they can spend more time on foundational work.

“With Knit, we now have a more scalable system that reduces manual effort while maintaining high research quality. Knit provided end to end efficiencies with our research across fielding, sampling, and analysis. It does a lot of this gracefully on our behalf."