"dscout helps non-researchers empathize with our users. The platform enables us to capture the voice of the customer and share their perspectives throughout Lenovo."

“It was exciting because the concepts that we came up with for accessibility limitations very clearly were concepts participants were excited about even those without accessibility limitations. And this makes sense conceptually, theoretically: Designing for accessibility and designing for edge cases means innovating for everyone.”

"The project started in December, which was holiday shopping season—it actually seemed like a perfect time to do a diary study and ask people about their shopping experiences, because people are doing a lot of online shopping during that time."

“Another big hitting point was that dscout has this giant database of scouts who are eager and motivated to participate, and they're all over the country, and I have this ability to recruit for different types. The diversity in the pool was really important for this work.”

“We need to be in there, ensuring AI is continuously tweaked to account for potentially negative impacts and human unpredictability. That can only be done if humans are in there, testing and tweaking AI until it works for us. Working together, we can make quicker data-driven decisions and design services …

“We've been able to take on 40% more studies. I don't even think I could put into words how much time Private Panels saved us. It's completely changed the game for us.”

“There’s that sense of realness being there in the environment surrounded by the sounds and the different products. We learned that sustainability is a really complex multi-factored concept that means a lot of different things to different people; be it organic, grass-fed, animal welfare, or recycled packaging.”

"[With dscout], I can get a lot of quality data quickly that captures user experience in the moment and helps me and my team understand the issues users are having."

“As we start to make meaningful progress toward what we’re recommending, we’re going to immediately start learning things that challenge that vision. Yes, We have this future-facing, North Star vision for whatever initiative we happen to be working on, but it is not set in stone. As we learn things …

"Though we had a single learning goal, we still prioritized a mixed methods approach, a survey from research, and product analytics with data science. This enabled us to understand what was happening, by unpacking both behavioral and attitudinal data, the what, and beginning to understand the why. By combining research …

"Okay, we're going to have a six-week study and we’ve locked in the primary questions we want to ask.”

"I hadn’t talked to potential customers yet and started to think, ‘Do people really use a changing table or do they just avoid it? Do they not even go into the store?"

"I think what was a big aha moment is just how much the research would impact our go-to-market strategy and marketing language. And we've used so much of the keywords from the word cloud in our language, whether that's the website, or our pitch decks."

“Participants are so much less self-conscious on dscout. They’re hanging out and talking to you, and they’re getting super real. My clients are amazed they can’t get over the fact that people will do this.”

“We pulled only Lenovo product owners out of the screener for our mission, but have all other data back-logged."