When setting up and teaching a course, a cooking instructor needs thoughtful and clear steps to get started. So, she took notes early on recipes, supplies, and places before picking where to go next.

On her last trip to New York, Sophia and her friend got horrible service. The hotel had a first-come, first-serve policy on room bookings. Those rooms that were the right fit also tended to become fully booked. The type of reservation she was looking for needed a suitable bathroom. 

Today, the plans are different. Can she hold onto the booking? Will she get it? 

She starts by choosing the venue. Yes, it would be more work to book. Her focus is an event where she can more easily bring her friends. She can choose the time and place. She will host a cooking class.

Important Events

Partly why she didn't want just another reservation at a steak house, as it was when Sophia had visited New York. There, the dining establishment ramp was broken, leaving her feeling like she had shown up at random, even though she set up a call and request beforehand.

The App

AccessiCity scores any place that gets reviews. The helpful details are in a single digit from 1-10 to predict a venue's tendency to follow a guest request. To Sophia, the steak restaurant’s history shows exactly what she is looking for. The app says that it bets that the future dining for this location will be positive. How? The app combs through trends in user reviews so that strong results are properly located. Here, it is looking for the likeliness first of a working ramp.

Problem

How might Sophia find something out about the history of a hotel or restaurant beforehand? 

As Is

The answer is shown with a number, where some information makes a score based on direct reviews.

AccessiCity predicts how her specific wants would work out in real life. At the early morning of the event, Sophia has passed this stage of planning. She knows she has a full day of driving ahead.

The start of Sophia's plans was to get to Tucson. She could also make things easier on herself by getting there early. She needs a way to know ahead of time: Is the business right?

She created her first event. She estimated about 25 guests. Thinking of a good time to meet, she also thinks about what the event might look like.

While searching she focused on a photo of a small house. It was about as good as a bed and breakfast. It was also a comfortable distance from the city.

The goal was to find a house with an inviting kitchen. Sophia feels she can inspire someone to enjoy cooking. In the past, there had been very little time for checking the facts thoroughly. She might have worked on the problem all night. She was looking for a particular type of event hosting.

Finding a comfortable space was important.

Sophia can't wait to give her class. 

What works

Sophia noticed a few key things in the app. "What's this for?" as she scrolls on to explore events.

The first barrier seen in a few tests was users where the users were left alone looked like confusion in the initial click-through. What it is that the app does, above the fold, is not clear. These are annoying places where greater detail is needed. 

A car's navigation screen also shows how it’s about to run its course, in a summary.

Within the app, creating an event with a set of options gives her a starting point for success.

On AccessiCity, given the option for the type of booking, she was given the option to include additional requests such as a donation.

She makes sure to include as much information as possible.

In the past, teaching cooking as entertainment seemed like a frustrating side project.

Looking for an outlet to channel old frustration, the app would become a touchstone. Now, others like Sophia can make readily available cooking classes.

Solution

"Maybe it will be a hit?" Which tags are necessary? What options can have cooking photos look just the way I want it?

It seems there is a lot here. How does Sophia have a clue about conducting an event search, providing details, or confirming the steps on her own?

As she goes about filling out the event page, Sophia is also looking for hints that the overall process going as expected and as she wants it. This is somewhat obvious only after she sends the event form at the end, for example.

After some work updating screens, new click-throughs now indicate what the app is for.

Testing

The app had no scores to be seen on the first page. The user knows about estimates of accessibility. As an event creator, they have the option to get feedback and create their own custom events.

Meaningful events

Indirectly, the app searches for events that trends a greater chance of satisfaction, for a specific frustration that has its counterpart in the real world. 

In Charge

She creates classes expecting experiences to be accessible.

Beyond the point, what was the successful change? Does the app show its purpose?

Filling out the section to create the event was a little long-winded but it didn't discourage her from being very specific.

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The cooking class missed a few key details quite early. Communication about accommodations could have helped.  Included was a trend that the venue was not likely to be able to reliably meet guest expectations.  According to one interpretation of the testing, the user needs to be set up for this prediction when starting to use the app.  Applying this recommendation goes toward the overall goal of efficiently navigating relevant accessibility information.

Problem

At an event venue, there are rules in place for accommodations?  People like her can be unburdened of doing the extra work of researching the venue beforehand.

A hotel, bank, or restaurant wants AccessiCity scores that don't just create negative perceptions.

Solution 

It is crucial to provide Sophia an introduction to the app that would have her feeling prepared to create a real-life event leading to a positive event atmosphere.

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