Webinar

How NASCAR is leveraging Researcher-Driven AI for Report-Ready Insights

Maxwell Miranda, Senior Manager of Consumer Insights at NASCAR, sits down with Knit Co-Founder & CEO, Aneesh Dhawan, to show off how Knit's Researcher-Driven AI platform is fueling NASCAR’s ability to keep a pulse on its ever-evolving fandom. Aneesh and Max dive into how Researcher-Driven AI is allowing for NASCAR to get to "report-ready insights" to drive quicker decisions – while overviewing real world insights and findings uncovered through the Knit platform.

October 15, 2024

Virtual

1. Challenge: Research turnaround was too slow

  • The Problem:
    NASCAR needed to deliver insights quickly to internal stakeholders — often within a week or less. Traditional research methods took 4+ weeks, with analysis and reporting being the most time-consuming processes part of these projects.
  • Knit’s Solution:
    Knit provided report-ready insights within 24 hours of survey fielding. NASCAR was able to move from research objectives to presentation-ready slides in days — not weeks or months.

“Being able to get the data at your fingertips with a platform like Knit is so quick… we've found a lot of efficiencies.”
— Maxwell Miranda, Senior Manager of Insights at NASCAR

2. Challenge: Too much time spent on analysis and reporting

  • The Problem:
    NASCAR’s insights team was spending too much time turning raw data into stories, delaying their ability to act or share findings broadly.
  • Knit’s Solution:
    Knit’s AI automatically generated slides, insights, and narratives based on business objectives. This freed up the team to focus more on strategy and stakeholder storytelling — not data wrangling.

“It really allows you to… create that narrative you want to from the data.”

3. Challenge: Difficulty creating stakeholder-ready deliverables

  • The Problem:
    Transforming raw survey data into polished presentations was time-intensive. NASCAR often needed deliverables they could confidently show to executives or partners quickly.
  • Knit’s Solution:
    Knit provided PowerPoint-ready slides with key takeaways, charts, and AI-summarized findings that were usable immediately. NASCAR even presented insights directly from Knit’s platform.

“We've even presented within the Knit platform and used the slides to showcase data.”

4. Challenge: limited resources to analyze open-ended feedback

  • The Problem:
    NASCAR’s team was small and couldn’t keep up with manually coding thousands of open-ended responses, especially from fan experience surveys.
  • Knit’s Solution:
    Knit’s AI-powered text analysis turned qualitative feedback into quantitative insight automatically — tagging themes, surfacing trends, and backing them up with verbatim quotes.

“The AI text analysis platform is probably our favorite part… turning qualitative into quantitative is super helpful.”

5. Challenge: Inability to Leverage Data from Other Sources

  • The Problem:
    NASCAR had valuable data sitting in other systems (e.g., guest experience feedback) that wasn’t being analyzed deeply because of time and tooling limitations.
  • Knit’s Solution:
    Knit allowed NASCAR to upload CSVs from other sources into the platform. They could instantly run AI analysis on open-ends and extract story-driven insights from previously untapped data.

“We uploaded the CSV… Knit helped us pull out that concerts were the second most important thing after racing [at events].”

6. Challenge: Difficulty Segmenting and Customizing Insights On Demand

  • The Problem:
    When stakeholders asked for new data cuts or follow-up questions, NASCAR couldn’t easily segment data by audience (e.g., Gen Z, Hispanic fans, casual vs. Avid).
  • Knit’s Solution:
    With AskKnit, NASCAR could ask the AI any question — even during a presentation — and get slides tailored to specific segments in minutes. It enabled live Q&A with data, not delays.

“We’ve used this feature live as questions come up… it populates insights we need on the spot.”

7. Challenge: Making Qualitative Feedback More Impactful

  • The Problem:
    Quotes and open-ends were often buried in static reports and didn’t convey the full emotion or impact of the fan voice.
  • Knit’s Solution:
    NASCAR used Knit’s video capabilities to capture fan reactions and assemble sizzle reels for internal and sponsor presentations — making the insights more visceral and memorable.

“Just hearing and seeing their reactions has been amazing… it makes qualitative feedback more impactful.”

8. Challenge: Reaching Beyond Existing Fan Base

  • The Problem:
    NASCAR wanted to reach non-fans, younger audiences, and diverse segments, which its internal panel didn’t always cover.
  • Knit’s Solution:
    Knit provided access to high-quality external respondents (via its panel), enabling NASCAR to explore new audiences with the same level of data fidelity.

“Whether it’s non-fans, Casual fans, or Gen Z… we always get the segmentations and cut that we need from Knit.”

Interested in seeing Knit’s Platform in Action?