White Paper Research
Researching the problem space, I first wanted to understand the thought process behind a trusted recommendation and if word-of mouth really was so powerful. In doing this, I found a few key studies that corroborated the influence of friends and family in decision-making. According to an industry report by Seven Rooms:
"When it comes to discovering new restaurants to dine at, over half of Americans (54%) rely on their friends and family to make a recommendation."
This is in comparison to only 30% for online review sites like Yelp and 10% for social media apps like Instagram. With this in mind, we went into our user interviews, to figure out what went into the average decision-making process.
Competitive Analysis
Our interviewees remarked that they would open up these apps and scroll until something 'popped up' that suited their palette, which was the reason behind their 'lack of intention.' This correlated with only 32% of our survey respondents noting that they made active efforts to compile and reference a list of saved restaurants.
Main Insights: Putting it All Together
Insight
Need
1. Users are more likely to trust their friends and family over other sources.
1. Users need a way to both give and receive recommendations from their friends.
2. Users passively search their local area until something "jumps out at them".
2. Users need something readily available.
3. Users take longer to decide in group settings, having to accommodate more preferences.
3. Users need a better way to facilitate discussion that allows them to compare and accommodate.
Ideating
I had a facet that would provide credible recommendations from trusted people, the user's friends and family naturally. The second leaned into the availability heuristic, curating said credible recommendations to keep them top-of-mind for the user at a moment's notice. And lastly, an efficient way to compare any restaurant in the moment, to weigh the pros and cons of each option, be it quality, distance, or price.
Design & Major Improvements
In the same vein where users could send and ask for songs while adding them to a playlist, I wanted to replicate this idea with restaurants.
And throughout this process, I continued to iterate on several concepts, receiving user feedback along the way.
Project Takeaways
I'm glad to have finished my first case study as I now realize the amount of time and effort is no small thing. Having finally got my hands dirty, I picked up a few things along the way, both about myself and going forward with future endeavors:
- Failure is just feedback. I spent a lot of nights unable to work on this project in fear of failing a lofty standard I had set for myself. Understanding the idea of 'failing fast' gave me the push I needed to realize that much of design revolves around failing, learning from it, and reiterating.
- Plan for my future self. When it came to documenting my process and the study itself, I could have made my life so much easier with better intentioned notes and takeaways. I didn't record my interviews and found my notes from prior weeks not making much sense in the present. Going forward, I plan to be much more thorough with documentation.
- Our way isn't the only way. I think my partner and I pigeonholed ourselves on this project. Eager to expand on the "Spotify for restaurants" concept, we had an initial idea and built around it rather than fully exhaust all possible avenues and angles. It's good to have inspiration but I'd like to open my mind to more possibilities with a blank slate.
- It doesn't need to do everything. We spread ourselves a little thin with an experience that wanted to provide a social component while also creating and managing lists of restaurants. Our solution was multi-faceted; this was a lot to juggle and played a hand in obscuring the bigger picture at times. In the future, I'd focus on limiting the scope of a project. Find out what's needed and go from there.
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