Event

How Condé Nast is using AI-Powered Quant/Qual to explore emerging trends among future consumers

Maja Benedict, Director of Global Custom Insights at Condé Nast, sat down with Knit Founder & CEO, Aneesh Dhawan, at Quirks Chicago 2024 to show off how Knit’s AI-Powered Quant/Qual platform is fueling Condé’s research pipeline. Maja and Aneesh dive into how the Knit platform is enabling an unprecedented speed to insight for Condé Nast, with its application of AI technology from study design to storytelling.

March 26, 2024

Chicago, IL

Challenge: Declining data quality from traditional panels

  • The Problem:
    Condé Nast found that standard panel providers were delivering unreliable data — with up to 20% of responses flagged as bots or survey farms, leading to internal mistrust in survey results.
  • Knit’s Solution:
    Knit provided video-validated respondents — making it easy to confirm identity and authenticity, and rebuild trust in the data.

“We were seeing a decline in quality… it was making us not trust some of the data. Knit helped us reimagine it.”
— Maja Benedict, Associate Director of Global Custom Insights, Condé Nast

2. Challenge: Traditional qual research was too slow and resource-heavy

  • The Problem:
    Qualitative research was either outsourced (expensive) or conducted in-house (time-consuming). A single project could consume entire weeks from one or two team members.
  • Knit’s Solution:
    Knit’s AI-powered video analysis automated the most labor-intensive parts of qual — summarizing, tagging, and organizing responses — so the team could focus on interpreting insights.

“It meant that we could focus our time on insights instead of execution.”

3. Challenge: Hard-to-articulate behaviors around media consumption

  • The Problem:
    Understanding how people consume media — especially across platforms like TikTok or Instagram — was difficult through traditional surveys. Respondents struggled to recall behaviors and motivations.
  • Knit’s Solution:
    Knit’s video-based feedback gave respondents more space and comfort to explain nuanced behaviors, providing context-rich data.

“Video gives them more space to explain how they're feeling… it really allows us to get that deeper understanding.”

4. Challenge: Lack of scalability in qualitative insights

  • The Problem:
    Manually reviewing hours of qual video or text feedback was inefficient. It made qual hard to scale across multiple projects.
  • Knit’s Solution:
    With AI summaries and theme tagging, Knit gave the team instant access to high-level takeaways — while still allowing researchers to dive into raw responses as needed.

“AI contextual analysis lets us double tap into a theme or specific audience… without rewatching everything.”

5. Challenge: Need for unified quant + qual insights

  • The Problem:
    Condé Nast’s insights were often fragmented — quant and qual studies were run separately, analyzed separately, and didn’t easily integrate.
  • Knit’s Solution:
    Knit combined quant and qual in a single study — enabling analysis by both survey response and demographic cuts, and tying behavior to sentiment.

“You get the depth of qual and the breadth of quant… we could filter video by survey response or platform preference.”

6. Challenge: Slow research workflows and manual charting

  • The Problem:
    Building surveys, programming, and charting data all required significant internal time or paid outsourcing — especially for lean teams.
  • Knit’s Solution:
    Knit automated survey generation, programming, and PowerPoint-ready decks, allowing the team to move from fielding to insights almost immediately.

“By the time you close field, Knit gives you a fully charted deck — we used to outsource that. Now we jump right in.”

7. Challenge: Rising expectations with fewer resources

  • The Problem:
    With shrinking budgets and growing demand, the Condé Nast insights team had to do more with less — and faster.
  • Knit’s Solution:
    Knit acted as a research force multiplier — giving the team modern tools to work faster, smarter, and more proactively, without needing headcount expansion.

“Budgets are getting smaller, expectations are increasing… Knit helps us be strategic with our time.”

8. Challenge: Keeping pace with rapid industry change

  • The Problem:
    Media consumption, platform trends, and Gen Z behaviors were evolving too quickly for legacy research timelines to keep up.
  • Knit’s Solution:
    Knit enabled Condé Nast to stay proactive, arming teams with insights before stakeholders even asked — critical for supporting corporate strategy.

“We need to have the data before… not in four to six weeks — we need it immediately.”

9. Challenge: Need for strategic storytelling tools

  • The Problem:
    Insights needed to resonate with leadership and other non-research stakeholders — not just sit in a dashboard.
  • Knit’s Solution:
    Knit’s combination of verbatim video, theme analysis, and editable presentations allowed for compelling, story-first delivery that helped drive business action.

“Video is powerful for storytelling — it helps stakeholders really connect with the audience.”

Interested in seeing Knit’s Platform in Action?