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.

Challenge: Existing research tools resulted in week-long research cycles, stopping teams from self-serving insights

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.”

Solution: Helping teams self-serve user experience insights in days with Wondering’s AI-powered multi-language research studies and analysis

Matsmart initially tested Wondering to see how AI-powered research studies and analysis could help them towards their goals, including:

• Building a scalable research process that helped their teams gather insights from their customers quickly, whilst retaining oversight by the user research team. 
• Help teams at Matsmart learn from customers in each market they operate in, by letting  the teams recruit and interview customers participants in any language with the help of AI. 
• Share actionable user experience insights within days of starting a project, instead of weeks. 

Here’s how the teams at Matsmart use Wondering’s AI-powered studies and AI analysis to learn from their customers in five steps: 

1. The Matsmart research team uses Wondering’s AI-powered study builder to create studies within a few minutes, and then tweak the studies so they perfectly capture the questions they need answered.
2. Matsmart sends the study to customers going through specific product journeys on their website.
3. Wondering’s AI-powered studies dynamically prompts participants for more insights for each question asked.
4. Wondering’s AI analysis identifies key insights from all the responses collected.
5. The teams at Matsmart share these insights internally, and the product team’s implement their learnings into the product development process.

The impact: Teams at Matsmart can self-serve actionable user experience insights in days with Wondering’s AI

"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:

1. Validate new ideas and test your designs in days: Test your designs before you start building and quickly validate new ideas and concepts
2. Reach and learn from participants in different languages: With AI-powered language translation, you can gather feedback from participants in 50+ languages
3. Prioritize your product roadmap: Make informed decisions on which features to build next based on a deeper understanding of your users

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