How might I reduce the no-show rate?— OLIO (C2C product) case study

What is OLIO?

Globally, over one-third of all the food we produce gets thrown away, and more than 50% of food waste is created in our homes. OLIO -share more waste less, the neighbor-to-neighbor food sharing app, is aiming to solve this problem.

I do believe this app will be contributing hugely to reducing food waste once it gets a larger user base. Yet, it seems that Olio needs more regular users, so I started to look into what factors serve as a deterrent for users in this food-sharing experience.

The no-shows

I investigated reviews for the app and interviewed 4 users to find out what they make of Olio, and what improvements they would like to see. More item lists, clear navigation, and a better search function… the list went on. But there was one fierce pain point, it was “the other user’s no-show”.

“I chose to share for good, not for wasting my time.”
— from a user interview

Once they experience a no-show, a user’s skepticism tends to run through all aspects of the app and it could ruin the whole experience and possibly push users out of a use cycle. New users were especially susceptible to frustration from a no-show, as they didn’t have enough positive experiences that would cancel out the negative experiences.

app reviews — “the no show is a real pain”

User journey map : Giver’s

Why don’t people show up?

What makes people not show up? Why couldn’t they inform the other user in advance that they can’t make it?

I conducted an anonymous survey to find out the reasons behind the no-shows. In total, 44 people participated in the survey, 18.2% of whom didn’t show up for a meet arranged through an app answered the survey with their honest reasons.

Reasons:

• Forgot the arrangement.
• No reason, just didn’t want to go (nothing to lose)
• Miscommunications
• Social anxiety etc

No shows are C2C platforms’ common problem. How do other platforms cope with no-shows?

Customer-To-Customer, Peer-To-Peer

In business, the actions of users (or customers) are less predictable than other factors. This is why the P2P/C2C business model is tricky, as it relies on individuals’ contributions for a smoothly running system. A no-show results in wasting time and resources, and missing out on other chances or clients. Although the service provider (business) cannot prevent certain behaviors of users perfectly, C2C services such as Uber, Airbnb, and Cambly have been providing a pretty stable experience.

Penalty

Polished penalty policies help. Uber regulates long-wait times and no-shows by charging a fee. Passengers and drivers have no way of shirking the fee since their payments are already connected to the app. In the case of Airbnb, hosts can choose a cancellation policy for each of their listings, and guests will be charged according to the policy the host chose if they cancel or don’t show up. For Cambly, lessons between tutors and students take place online. Since no-shows are pretty common on this platform, Cambly has policies to cope with unexpected absences for tutors and students; a strong rating system, and reservation penalties.

Precise time / location setting, and confirmation

These three apps also provide precise time and location settings. There’s no room for miscommunication. No double booking is allowed, and mutual confirmation is essential. Uber offers a dropdown menu for the location search to keep users from making typos, Airbnb and Cambly offer available dates on the calendar. An Uber passenger will be given a picture of the car as well.

Push notification and confirmation email

Once they have confirmed the time and location, users will get notifications as a reminder. Cambly’s double notifications (mobile push notification and email notification) are definitely better than missing a class.

How Olio prevents no show?

This is how Olio users arrange pickups

Let’s take a look at how Olio works. Although its penalty policy is not as strong as other apps’ since it’s totally free, there is a working system to penalize users who don’t turn up. A user can report that the other didn’t show up and can give them a low rating, and a user with persistent low ratings will have their account temporarily suspended. But there’s no guide for pickup arrangements or reminders, users will have to rely only on direct messages, which can leave plenty of room for miscommunications and forgetfulness. There is no system on Olio that can prevent no-shows in advance.

Airbnb doesn’t have a reminder, but it’s hard to miss when you’ve already paid lots of money

My assumption

Again, these were the reasons for no shows from my survey

• Forgot the arrangement.
• No reason, just didn’t want to go (nothing to lose)
• Miscommunications
• Social anxiety

It’s not surprising that no-shows keep disturbing Olio users. It clearly lacks ancillaries for users to avoid potential no-shows.

My assumption:

1. Forgetfulness and miscommunications make up half of the reasons for no shows; the no show rate could be reduced by up to 50% by adding a reminder and a mutual confirmation process.

2. The mutual confirmation process could instill a sense of responsibility in users.

My solution

In the current user flow, there is no confirmation process.

For this solution, I added a definitive step for mutual confirmation. And I created an option for reminders that works based on the time users agreed to.

Select-based input field for date, time and location

With this new design, users have to set a location and time to arrange the pickup.

A new flow from mutual confirmation to user rating

There is a “they collected the item” button to move to the next step, the user rating.

And importantly, in the final step, the app knows when to delete the location information, it’s personal information that nobody wants to keep stored for a long time.

Push notification reminders for arrangements.

Users can set reminders based on the arranged time so that they don’t forget.

Validation — the limitation of this case study

I assume this change would help users set more precise schedules and this additional process would instill a sense of responsibility in users, eventually reducing no shows. Yet, I probably need to test the following before implementing it:

• If the flow is clear to users
• If users are comfortable with sharing the precise location

For this case study, 4 in-person interviews and 44 survey participants are a small amount of data to generalize users’ pain points and reasons behind their actions. In addition, I couldn’t access actual data (no-show rate, revisit rate …). It’s unfortunately difficult to validate and measure the results of this project. These are the limitations I had for this case study.

Lastly, I can tell Olio is working hard, and I’m excited to see the changes they’re going to bring to the world. I support team Olio 🌱

Solo project / Duration: 4 weeks

Reference

• https://olioex.com/food-waste/the-problem-of-food-waste/ (The problem of food waste)
• https://www.airbnb.com/help/article/475 (Airbnb policy)
• https://help.ut.taxi/riders (Uber policy)
• https://camblyenglish.zendesk.com/hc/en-us/articles/360051355511-What-happens-if-I-miss-my-reservation- (Cambly policy)