With the number of foodtech startups and products reaching all-time highs, it has become increasingly important for products to attract and retain customers. Launching new products is expensive and the risk of failure is high. Product feedback is the ultimate tool for making the correct “prioritize or kill” decisions early, deprioritizing losing products, and developing more homerun products.
When we speak with foodtech companies, there are a few common pitfalls they make with their product feedback:
- Skipping product feedback: Shockingly, this is the most common mistake we see. While intuition is a key part of the development process, it’s no secret that user feedback is crucial for finding product-market fit (just look at the world of tech). Driving customer engagement, boosting trial, and maximizing repeat buyers are all key aspects that can be gained from external product feedback.
- Wrong audience: An easy way to get “external” feedback is to use friends, employees, or conference floors. Unfortunately, this does not yield accurate feedback. Even if you collect consumer feedback anonymously, these groups are unlikely to share their true feelings. Your friends, family, and coworkers are the most likely to like your food, and least likely to tell you if it is bad. When used sparingly, this can be a useful tool, but should not be used as the main source of your feedback.
- Poor survey design/analysis: There is a reason professors spend years conducting a single academic study. It is exceedingly difficult to correctly design a survey questionnaire and collect accurate data. In order to conduct a proper survey you must gather an unbiased, representative sample, avoid leading questions, and select the correct question type. And once all that is over, you still have all of the data analysis to perform!
- Sporadic Testing: It is too common to do a study immediately before a product launch with the hope of achieving one final “everything looks good” check. If you do, though, this feedback will probably arrive too late to provide insights you can incorporate. Doing small user satisfaction surveys throughout your R&D process will help you get actionable feedback with enough time to act.
- Inauthentic Settings: The most common feedback settings that we see are online surveys or white rooms. Online survey takers click through as fast as they can, with the goal of finishing as quickly as possible rather than providing helpful feedback. On the other hand, white rooms create bias because they don't reflect how people buy or eat food, and they are exceptionally expensive.. The best insights come from in-context data, such as: at the grocery store, on a restaurant menu, or in consumers’ kitchens.
To avoid these common pitfalls, let’s dive into how to properly conduct surveys on your food.
The first step of a survey is always to identify what questions you are trying to answer: is our product ready to launch? If not, how can we improve it? Which sensory attributes do we need to work on the most? Once you have figured out which questions need to be answered, you can start to develop key hypotheses: should we reduce firmness?
This is where it is nice to have a background in data science. During your survey design, you need to avoid biasing questions/answers, and use appropriate question types including “check all that apply” (CATA) and “just about right” (JAR). An example of an unbiased JAR question would be “How do you rate the firmness / softness of this burger? Much too firm, too firm, Somewhat too firm, Neither too firm nor too soft, Somewhat too soft, Too soft, Much too soft".
After concluding study design, you enter the data collection stage. Be careful to get consumer feedback in a proper setting (like an actual grocery store), with appropriate test design. Depending on your test, survey methodology can involve randomization, benchmarks, A/B testing, etc.
Once you have collected the responses, you can start analyzing your data to gain insights. When you are conducting data analysis, it is important to understand how different attributes are connected. For example, you could run a survey and see that people tend to think your burger is too firm, but how much does their firmness rating impact their overall approval of the burger? If the people who rated your burger as “too firm” liked it the same amount as people who thought it was just about right, then you should not focus on changing the firmness.
With this analysis, you can start to answer deeper questions such as: what's more important to higher purchase intent: flavor, texture, or appearance? How does changing firmness impact overall approval of texture? The most important insights are gained from quantifying how much people’s experience is impacted by the different sensory attributes. This can help you focus your R&D efforts efficiently and bring the very best products to market.
For folks who come from food R&D backgrounds without a background in statistics or academic research, creating and implementing an accurate survey can feel like a daunting task. The food industry has been stuck with the same product feedback tools since 1980–white rooms, two-way mirrors, and portions of a sample served through a slot. Not only are these methods inauthentic to how people experience food, they are also expensive and slow-moving.
We created Palate because the product feedback status quo wasn’t working for foodtech companies. We’re revolutionizing product feedback with authentic, agile approaches that help sustainable food brands build better products faster. We use pop-up events to stock your product on our grocer partners’ shelves or on the menu of one of our restaurant partners. You can also tap into our network of 150+ Executive and R&D chefs covering all cuisines, geographies, and food service verticals. These options provide our clients with high-fidelity, affordable data.
If you have questions about product feedback, please reach out to Tyler Dale @ [email protected], and Alex Weissman @ [email protected]. We’d love to chat with you!
Palate Insights is an official prize partner of XPRIZE Feed the Next Billion. This is a multi-year, $15M competition that incentivizes teams to produce chicken breast or fish filet alternatives that replicate or outperform conventional chicken and fish in: access, environmental sustainability, animal welfare, nutrition, as well as taste and texture.