Matsmart is an online food retailer selling mis-labeled or outgoing goods at discounted prices with home delivery, helping people buy items that would otherwise be thrown away because of reasons like surplus amount, expiration, incorrect or damaged packaging at a much lower cost than its original.
Existing research tools resulted in week-long research cycles, stopping teams from self-serving insights.
Teams at Matsmart can self-serve actionable user experience insights in days with Wondering’s AI.
Matsmart is an online retailer in Sweden dedicated to reducing food waste by offering surplus, short-dated, and discontinued food items at discounted prices. Their mission is to minimize environmental impact and promote sustainable consumption. The user research team at Matsmart is looking for ways to help the teams within the company scale their customer contact, self-serve insights and learn how to improve their user experiences faster, which brought them to Wondering.
Before adopting Wondering, Matsmart faced challenges with their existing research tools, which included tools like UserTesting.com. Working in cross functional teams and growing their user base across europe rapidly, the teams at Matsmart have a constant need to test assumptions and ideas with real customers.
As the Lead User Researcher at Matsmart, Sofia Dunemann wanted other teams, like product, marketing and branding to be able to get insights about their customers faster, and self-serve insights when possible. She explains:
“Our product, marketing and branding teams mostly work on tight deadlines and need user insights fast”.
She continues:
“The biggest challenge with UserTesting was that it takes a lot of time to recruit and plan, execute and analyze tests. We have several product teams to support, and have a need to get feedback faster.”
Recruiting participants, planning and conducting tests, and analyzing the results were all time-consuming tasks with UserTesting. On average, it took more than a week to gather insights from user tests conducted on UserTesting, and more than two weeks for any moderated studies conducted without any purpose built research tool.
Before starting to use Wondering, the research team at Matsmart had also tested using general purpose generative AI tools like ChatGPT to try to speed up their analysis. Whilst powerful, these tools still required considerable effort and prompt engineering to work, resulting in a lot of analysis having to be done manually.
Additionally, their existing research tools did not support testing across different languages, and had especially poor coverage in the Nordics (a key market for Matsmart). Sofia explains:
“Our old tools only transcribed in German and English and not in the Nordic languages, which stopped us from hearing from the right customers. We wanted to be able to hear from customers in all the markets we operate in.”
Matsmart initially tested Wondering to see how AI-powered research studies and analysis could help them towards their goals, including:
Here’s how the teams at Matsmart use Wondering’s AI-powered studies and AI analysis to learn from their customers in five steps:
"Wondering has been a game-changer for us," Sofia explains. "Using AI to quickly set up tests, gather and analyze feedback efficiently, and do so across multiple languages has saved us time and broadened our research capabilities significantly. It's truly a tool that bridges the gap between qualitative and quantitative insights."
Matsmart’s teams gets user experience insights in days with AI-moderation and analysis
Moving to Wondering has helped Matsmart’s user research team reduce the time it takes from an average of more than a week to an average of two days. They can now rapidly deploy AI-powered research studies to test new ideas and teams at Matsmart can keep up with changing customer needs across the different markets in Europe that they operate in, further enabling them in their mission to reduce food waste and promote sustainability.
“In two days we were able to interview 400 customers in about our product category pages, and share insights from the interviews with other teams, thanks to how fast the AI-studies and analysis are.” Sofia explains.
She continues: “The AI analysis is one of the biggest advantages we now have in our research process. We’re able to turn responses into insights really quickly, and I can share it with other teams if they want to dig deeper into the data easily.”
Matsmart interviews customers across the nordics with the help of AI-powered study translation
With the help of AI-powered translation of their studies, Matsmart can now interview customers in 50+ different languages, including languages they don’t speak themselves.
"It's really good that we can use it to interview customers in the Nordic smaller markets," says Sofia. "We can trigger studies in any language. That was a big limitation with tools we have used in the past."
Matsmart’s research team has further democratized access to user insights
Equipped with an AI-powered study builder, AI-moderated and multilingual research studies and faster analysis with Wondering’s AI, team members outside of the Matsmart user research team, such as product, marketing and brand teams at Matsmart were able to start self-serving insights directly. This helped increase awareness for how user research could be used to support decisions, and increased the frequency of research studies run across the business by 2X.
“It has become a lot easier for team members to access insights after we started using Wondering, and we now run twice as many studies as we did before we started using Wondering.” Sofia explains.
How you can replicate Matsmart’s success
By copying Matsmart and deploying AI-powered user research studies to collect targeted feedback from your customers, you can:
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Before adopting Wondering:
After adopting Wondering:
