How to create a product your customer loves 3/3: Interpreting survey data
How can you process the quantitative data that you got from a survey? Unveil allows you to create a product you know your customers love.
The last step of finding your customer’s true needs, is to process the data from your survey. This data captures the satisfaction and importance of your desired outcomes. Learn how to find the desired outcomes in my previous post.
With this survey data, you have a quantitative view on your customer’s wants. Data are just numbers, you also need to interpret them. Unveil by 0smosis shows what your customer data means for your business. Find Unveil by 0smosis here: unveil.0smosis.com
Unveil focuses on four things:
- The Customer side of the Value Proposition Canvas
- Market Basket Analysis
- Individual question calculations
- Demographics
Each of these four points helps you to create a product your customers love.
Preprocessing
Before you learn from your data, you need to preprocess it. Unveil reads your data in a specific way. It has three sheets, each with its own purpose. See the pictures for a demo.
- The ReadMe: An explanation how to fill in the template.
- Datasheet: This sheet contains the actual data. Fill in your questions in the first part. Make sure to fill your demographics first and afterwards the desired outcomes. Lastly for this step, make sure importance is first, satisfaction second.
- Questionsheet: List all your questions. Also point out whether the outcome is a pain or a gain. There are two approaches, Max/Min and Emo/Func. Currently Unveil uses Max/Min to fill in the
• Max/Min: increase are gain, minimise are pains.
• Emo/Func: all emotional jobs are gain, all functional jobs are pains.
To share your data with Unveil, perform these steps:
- Go to File
- Select Publish To Web
- Select ‘Datasheet’ instead of ‘Entire Document’
- Select ‘CSV’ instead of ‘Web Page’
- Copy the link
- Input in Unveil
- Repeat for theQuestionsheet
And that’s all the preprocessing necessary. Unveil will transform your data into usable insights.
Insights
If you don’t have your own data yet, you can do a testrun with some of our data. Just select the link next to the calculate button in the Unveil tool. This is an actual survey we have done for Hachu, one of our ventures.
Unveil uses a Market Basket Analysis. It groups outcomes respondents found important but feel dissatisfied with. We call important and not satisfied ‘underserved’. It gives a statement like “20% of people bought apples, bananas and chips”. Or in our case “47% of people think questions 20, 21 and 24 are underserved.
First up is the Value Proposition Canvas. Unveils fills in the Canvas with the most important gains and pains. These pains and gains are based on the Market Basket analysis. It shows what you need to focus on for your product.
For Hachu, this shows several gains such as that people want clearly defined options (20). For pains it shows that people want to avoid taking bad estimation around decisions (21) and want to avoid being overcharged (21).
Next you can see the baskets themselves. Don’t only focus on the largest basket, also look at the others. For the test data, almost 30% are underserved for 6 questions. This means that if we solve those 6 problems, 30% of people will have a better experience.
Third are the individual questions. It shows what percentage of people struggle, how bad do they struggle and a combined metric for both. The combination provides a useful insight. For example, over 50% of respondents struggle with question 31: ‘I want financial security’. But they only struggle a bit. This leaves question 31 quite low in the combined ranking. But don’t focus too much on these metrics. Different types of consumers can be behind the numbers. Solving the top 3 problems might provide only partial solutions to three segments.
The fourth part of Unveil is an overview of the demographics. From this, you can understand who filled in your survey.
I want to conclude with a call to action. Don’t only focus on the Unveil metrics. Dig deeper yourself. Unveil proves a nice pivot to understand customer data. If you find a better way to interpret data, do tell us. We would love to learn ourself how we can improve Unveil.
That’s it for the practical guide to Jobs-to-be-Done. I hope you learned from this series. Let us know what you didn’t understand, I’ll get back to you immediately!
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