- Overview of Experiments
Assumption Test #1:
Hypothesis: We believe that the users want a solution that is unintrusive and less physical.
Test: To verify that, we will show them the four solutions that are physical and intrusive, digital and intrusive, physical and unintrusive, and digital and unintrusive.
Metric: And measure whether or not, on average, digital consistently ranks above physical and whether or not, on average, unintrusive constantly ranks above intrusive. We will specifically be using the average.
Criteria: We are right if digital and unintrusive solutions have a higher mean than physical and intrusive solutions.
Assumption Test #2:
Hypothesis: We believe that customers will want to use our solution because their friends are using it.
Test: To verify that, we will share two fake equally effective products, where we tell them that it was referred by 5 of their friends or that they found it themselves. Have them rank how willing they are on a scale of 1-5 to sign up for the app.
Metric: And measure which one has a higher average ranking.
Criteria: We are right if the one with information on friends gets a higher ranking.
Assumption Test #3:
Hypothesis: We believe that customers are not motivated to make long-term changes.
Test: To verify that, we will provide two hypothetical solutions that cost the same amount of money, but one is a one-time payment that guarantees results in a year and the other is a monthly subscription (but same price over the course of a year) that also guarantees perfect posture by the end of one year.
Metric: And measure the number of votes each solution gets (start with just a one month subscription or just buy the long-term solution).
Criteria: We are right if more people vote to get a one-month subscription.
- Detailed Experiment Design
Assumption Test #1:
Present interviewee with a Google Form of the following to-be-ranked products:
- Tracking app
- Wearable reminder that buzzes every minute
- Ultra thin back brace
- Chiropractic visits (in person)
Statements should be ranked on a scale from 1-4 based on posture improvement solutions that they would most prefer, with 1 being most likely, and 4 being least likely.
Interviewee proceeds to describe, in words, why they picked their top option.
Finally, interviewee ranks 6 factors of what matters most to them for a solution from the following:
- Convenience
- Cost
- Comfort
- Minimal physical equipment
- Professional support
- Easily added to daily routine
Interviewee ranks them from 1 (being the most important factor) to 6 (being the least important factor).
Based on our research, there are four domains of solutions: physical and intrusive, physical and unintrusive, digital and intrusive, and digital and unintrusive. We chose a solution for each category with the following matches:
- Tracking app – digital and unintrusive
- Wearable reminder that buzzes every minute – digital and intrusive
- Ultra thin back brace – physical and unintrusive
- Chiropractic visits (in person) – physical and intrusive
As a result, the first question aims to investigate which category of solution is most preferred by customers. If the average ranking of the digital and unintrusive solution is higher (and preferably the highest) compared to a physical and intrusive solution, we will know our assumption is correct.
Additionally, the questions asking about why an option is their favorite pick will help us glean further insights as to why they picked a particular solution. This was specifically done in order to determine if they mention the digital/physical or intrusive/unintrusive scales. If they do, we can weigh these answers more heavily and be confident in our assessment of which type of product is most preferred.
Finally, the questions asking the participant for a ranking of important factors for a solution, allows us to understand what is most important in a solution for the participant. By analyzing which factors are most highly rated on average, we are able to determine which factors matter most to participants. If they highlight a factor like “convenience” or “minimal physical equipment”, it will help us better understand where the solutions fall along the axes.
Assumption Test #2:
Present interviewee with a Google Form with the following proposed scenario:
Let’s say you have found two apps to fix your posture! The first one is an app that was recommended to you by 5 of your friends who are using it and the other app was one that you found on your own, but seems like it would be effective from the research you did.
Have the interviewee rank each solution based on how likely they are to get the app, with 1 being very unlikely and 5 being very likely.
Pose the interviewee with a follow up question asking them whether they prefer an app they found themselves or recommended by friends for a health and wellness app, or if they have no particular preference.
Third, ask the interviewee the following question:
Imagine you’re deciding between two posture improvement products that are equally effective. Which of the following would most likely influence your choice (choose up to 2)?
The options they can select from should be as follows:
- Personal research and reviews
- Friends or family using the product
- Expert/professional advice
- Brand reputation
- Price difference
- I’d choose randomly if all other factors are equal
The first question was chosen to understand what type of posture related app our audience would prefer and if they would be more likely to use an app that their friends are using to test our assumption. If there is a higher average rating for the app recommended by friends, we will know our assumption was right. The second question, similarly, asks people if they have a direct preference in case our last question didn’t make it clear enough. If more people have a clear preference for an app recommended by friends, we will know our assumption is correct.
The final question aims to understand what factors most influence an individual’s decision to choose a particular product. This question was chosen because our underlying assumption was made to best understand how to drive customers to use a product. As a result, if we understand other similar factors, we can incorporate those into our solution. The factors with the most votes are indicative of the factors that users most care about in their solution and we want to make note of and make sure to implement them in our final product.
Assumption Test #3:
Present the interviewee with a Google Form of the following proposed scenario:
Let’s say you have found two products that are both equally effective and can fix your posture permanently in one year. The first one costs $144 up-front for the whole solution. The second one is based on a monthly subscription, and costs $12 per month (meaning by the end of the year, you will have paid $144 for that product as well).
Have the interviewee select the solution that they would prefer and briefly explain what led them to that preference.
Follow up by asking the interviewee if they have ever tried to improve their posture, and if yes, have them select which methods they have tried.
Lastly, ask the interviewee how long they consistently maintained the habit, with the options less than 1 month, 1-3 months, 3-6 months, 6 months-1 year, and over 1 year.
The first question was chosen to understand whether the interviewee would prefer a solution that requires a year-long commitment (due to the up-front cost of $144), or a solution that allows them to pay monthly and the ability to walk away ($12 each month, adds to the same $144 yearly). Additionally, it tries to understand better why the interviewee preferred the solution they selected. If more people prefer the monthly subscription solution because they want the option to save money and cancel the subscription, we know our assumption is correct. The second and third questions were asked to see if people have tried to fix their posture before and how long they were able to maintain that commitment. If the majority of people who tried to fix their posture only sustained the habit for a few months or less, we know our assumption is correct. Looking at the responses to the methods that people have tried in the past, we can better design our solution to address problems with past tried solutions.
- Recruitment Process
Our project focuses on the bad habit of bad posture. From our needfinding interviews, we realized that most undergraduate students spend a lot of time sitting down and in front of their devices. In addition, these students are busy and are constantly in the presence of other people. Based on our assumptions, it made sense for us to recruit people who know a lot of people/are pretty social, and have packed schedules (i.e. do research, go to the gym, go to club meetings, etc. in addition to class). Busy students should have a harder time keeping themselves in check with their posture, therefore being unable to commit to any long-term solutions and social students might be more easily influenced by their friends’ opinions. In addition, both student groups should want a solution for their bad posture that would not arouse any sort of attention, yet help them mindlessly.
- Experiment
Experiment Link: https://docs.google.com/forms/d/e/1FAIpQLSclr0Vtys21RCHEIlHeEcP2wXhgCxgMpOkafi8xerkBGkc5XA/viewform?usp=sharing
- Synthesis
Learning Card #1:
Hypothesis: We believe that the users want a solution that is unintrusive and less physical.
Observation: We observed that the ranking data from the responses shows that the digital solution (e.g., tracking app) and unintrusive solutions (minimal disruptions to daily routine) consistently scored high. The tracking app was the most preferred option (on average) for 3 out of 7 respondents. Several users emphasized non-invasiveness and seamless integration into daily life as key reasons for their preference.
Learning and Insights: From that, we learned that users are highly influenced by solutions that do not disrupt their day and are easy to implement (unintrusive). However, some physical options like the back brace still had reasonable support due to perceived effectiveness.
Decisions and Actions: Therefore, we will prioritize designing a digital product with minimal user intervention while also exploring lightweight physical options.
Learning Card #2:
Hypothesis: We believe that customers will want to use our solution because their friends are using it.
Observation: We observed the average likelihood rating for adopting a friend-recommended app was 3.43, while for the self-discovered app, it was 3.0. In addition, the majority of participants (4/7) stated that they prefer products that many people they know are already using (compared to products that they found themselves or having no preference). In terms of selecting which factors would be most likely to influence their product choices, Personal research and reviews, Friends or family using the product, and Expert/professional advice were all ranked equally high (4 votes each).
Learning and Insights: From that we learned that while friend recommendations received a higher rating compared to self discovery, personal research and expert opinions were equally influential, which suggests that users do not rely solely on their social circles for decision-making. Our results show that the popularity of a product among user’s social groups does matter a moderate amount (14.3% higher likelihood), but there might be other factors that are equally as powerful in terms of influencing a user to adopt a product.
Decisions and Actions: Therefore, we will still create a product that encourages social sharing since peer recommendations are still very influential. However, we will also make sure that our product can appeal to users who do their own research and try to get professional/expert endorsements.
Learning Card #3:
Hypothesis: We believe that customers are not motivated to make long-term changes.
Observation: We observed that 6 of 7 participants preferred the monthly subscription-based solution over the up-front yearly subscription, and gave reasons such as having the option to cancel and spending less money monthly. Additionally, 5 of 7 respondents mentioned that they had tried to fix their posture in the past and selected methods such as stretching and being more intentional about their posture. Lastly, of those 5 participants, only 1 of them recorded that they had maintained their habit for longer than a year, with 3 of the others failing to maintain the habit for more than 6 months.
Learning and Insights: From that, we learned that users prefer a solution that will give them the option to easily walk away and not make a long-term commitment to solving their posture problem. We also learned that 5 of the 7 individuals have tried to fix their posture in the past, meaning that despite their reluctance to engage in long-term solutions, most participants (5 out of 7) express a desire to improve their posture.
Decisions and Actions: Therefore, we will create a product that may use a subscription-based model with flexible cancelation options and also offer a trial period to build trust before longer commitments.
