Google Side-By-Side

Ever felt hungry after an exam or long day's work and wanted to try something new to eat? Or tried to plan a night out with the family and could not find a restaurant that would fit a table of seven? Or had a 40 minute wait before your tables were ready and now had to do something to fill the time?

Introducing Google Side-By-Side, a comparison tool that helps to streamline the research process to find someplace to eat in the city and to enjoy the lively downtown atmosphere.

Our Main Objective

We felt like this was a necessary function to add to Google Maps as it would help to alleviate too things:

1. People did not know how to comparatively search for events and restaurants in Ann Arbor due to the number of different databases

2. Substantial lost of time is accumulated when dining out

Our main objective was to create a tool that was both easy to use and informative about the urban space to the user.

Creating Our Foundational Questions: The first step in our ideation process was to generate a list of “How might we…” questions to help us aligns our solution with our goals:

1. How might we improve the research ability of local restaurants/businesses in the downtown area?

2. How might we display essential information to the user in an accessible way?

3. How might we create a streamlined yet information dense experience while also being customizable to the user preferences?

Our main objective was to create a tool that was both easy to use and informative about the urban space to the user.

Exploration of Our Problem

Before we went right into solutioning, we utilized various different methods of exploratory research, allowing us to gather large amounts of user data that was both human and technologically relevant to our inquiries.

Gathering Our Thoughts

The data that we collected was then organized and analyzed. Through our findings, we found numerous trends and patterns to help our approach.

Technology Mediums: 4 major technological mediums were used during the searching process with Google Search and Maps coming out on top.

Decision Factors: Decision were mainly calculated on 5 different factors

Personas: There were 2 main personas observed, the College Student and Family/Social. These then could be broken down into 3 different sub categories.

Pathfinding Through Our Journey

To further organize our research, we created a journey map to map out the current process users take when deciding where to eat, noting what technology they used, where they used it, and if there were any problem/opportunity nodes.

Pain Points: Through our research we found there were too main pain points:

1. Comparing between restaurants is too clunky - To compare items like menus, ratings, pictures, etc, users had to cycle back and forth between the restaurants, adding unnecessary touchpoints

2. Information required to make a decision was not efficiently displayed: The information users said that would help out their decision making process was either hidden or on another page

Opportunity Points: We also noted to major opportunity points:

1. Idle time during wait - Wait times can often be very long, especially after an event. Making a feature to find something to do in the spare time could make the downtown more lively.

2. Calendar integration - The current share feature is great for one or two people, but for the larger parties such as families or the more scheduled users, more features could be added to improve efficiency

The Ideal Task Flow

Taking in all of the information we gathered, we started solutioning how we wanted our product to function. Before we went into designing the new interface, we wanted to get the step by step process right.

Iteration Makes Perfect!

Based on all of our finding and what our ideal task flow should look like, we narrowed our design focus in 3 different areas:

1. Improve the data shown to users

2. Improve the navigation from one tool to another

3. Improve the amount of data that can be selected from

User Testing

It would have been magical if we got it right the first time, but we did not. In fact, it was more like the 8th or 9th try. User testing was a crucial part of the iteration process because we wanted to make sure that users could understand the tools and information presented to them. Making a tool that looks nice is one thing, but designing it to act as an extension to the human decision making process was our intended goal.

In order to accomplish this, we tested a variety of design layouts, colors, and navigational sequences. We took note of what worked and what could be improved.

Technicals

Side-By-Side uses a variety of different databases and tools in order to make an all in one comparison tool.

Combining public event data, Google Maps statistics, Google Calendar, and business data from third party sources, Side-By-Side effectively creates an environment that is both rich in data points but not too overwhelming for the user.

Next Steps and Reflection

There are still improvements to be made to our final interface. Having the user customize the different attributes in the Prism tool, for example, would add a new layer of customization that the user can take advantage of in order to find restaurants to fit their personality.

Overall, we felt like we created a tool that can help all users, from impromptu to scheduled, curate the perfect night by finding the best place to eat and experience the variety of events that may be going on in the lively downtown area.