1. Challenge: Slow research timelines
- The Problem:
Traditional vendors took 4+ weeks to execute and analyze a study — too slow for the fast-paced demands of innovation and internal stakeholders. - Knit’s Solution:
Knit helped deliver end-to-end research (Quant + Qual) in just 2–3 days, allowing Mars to meet quick-turn deadlines without sacrificing insight quality.
“People want things yesterday… this would’ve taken a month with another vendor. Knit was a game changer.”
— Cassie Jackson, Regional Manager of Innovation Insights at Mars Wrigley
2. Challenge: Fragmented quant and qual approaches
- The Problem:
Mars had to run Quant and Qual studies separately — often with different vendors — making it hard to synthesize and act on both types of data holistically. - Knit’s Solution:
Knit unified Quant and Qual in a single platform, with seamless workflows that let researchers cut qual themes by quant segments (and vice versa).
“We were looking for a one-stop shop… Knit let us combine both in one place and pull apart each layer as needed.”
3. Challenge: Limited access to qual at scale
- The Problem:
Traditional qual methods (e.g. IDIs, focus groups) were expensive, slow, and hard to scale, especially when trying to hear from hundreds of consumers. - Knit’s Solution:
Knit delivered hundreds of video responses in days — enabling Mars to explore category, occasion, and flavor insights with depth and diversity.
“Getting qual at scale is really nice — and hard to achieve quite often. Knit made that easy.”
4. Challenge: Time-consuming analysis
- The Problem:
Reading thousands of open-ended responses and coding themes was painstaking and resource-draining, delaying insights. - Knit’s Solution:
Knit’s AI assistant summarized responses, generated themes, and surfaced verbatims instantly — giving researchers a strong starting point without doing manual coding.
“The AI summary was something I’d have written myself — without spending hours reading 2,000+ open ends.”
5. Challenge: Turning data into stories
- The Problem:
Even with good data, crafting a narrative that connected dots and drove decisions was time-consuming and difficult to scale internally. - Knit’s Solution:
Knit helped Mars automatically generate insights headlines, pull curated verbatims, and build visuals like word clouds and AI-powered summaries — making decks more story-driven and shareable.
“Knit helps you get to that key insight faster — and build that story more efficiently.”
6. Challenge: Internal stakeholder expectations for voice of consumer
- The Problem:
Mars needed to bring the consumer voice into internal decks — not just stats, but video and emotion — especially for brands like Altoids and Ice Breakers. - Knit’s Solution:
Knit’s platform enabled Mars to create and export consumer showreels, integrating video soundbites into their presentations for maximum impact.
“We created showreels to bring the consumer to life… and show exactly what they think of our brands.”
7. Challenge: Juggling too many projects, not enough time
- The Problem:
The insights team had limited time to deeply analyze each new study — even when DIY platforms gave them access to raw data faster. - Knit’s Solution:
Knit combined automation + human flexibility to do the heavy lifting, letting Mars’ researchers focus on strategic interpretation — not busy work.
“With Knit, we’re not starting from scratch. It gets us 70–90% of the way there.”
