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Building for trust.


Trust is dead online.

Problem: The food review system is broken. We can't trust the reviews we see online because of fake reviews and revenge reviews. This makes it nearly impossible to trust the reviews we see online.

What they do: Ping is seeking to fix the food review system, to make the restaurant and cafe discovery process enjoyable, quick and easy.

Solution: A quality controlled food recommendations system where you can trust what you see.

Going out to eat, we found that we simply didn’t trust the reviews we were looking at, which meant we were wasting a lot of time doing our own research to validate reviews.

The Context and Challenge.

A broken system.

This was a frustrating and time consuming process that made something that should be enjoyable, choosing somewhere to eat, an unpleasant experience. So we set out to fix this problem.

Project background and description

Our timeline here was undefined as we were setting out to fundamentally change an existing system, the world of food reviews. We had a budget of $70K and our purpose was to shake up a multi billion dollar industry.

The Problem.

Trust is broken.

To start, there was simply no place that we could go where we felt we could fully trust the reviews we were reading.


This again meant that a lot of manual research was required. Standing in the street doing this on  your phone isn’t the funnest thing to do.

Project goals and objectives

The goal here was to present the user with a restaurant of cafe recommendation they could trust in 3 taps or less.

Process and Insight.

Control content creators.

Talking to foodie influencers we further validated that the trust issue was rampant. Some existing platforms were being gamed by people with disingenuous intentions.


Restaurants were being threatened with 1 start reviews by users trying and win a free meal. We explored this world in depth and found that we needed to control who could submit reviews in order to clean up the data and deliver reviews you could trust.

The key differentiator that we established here was the fundamental goal of building a system focused on trust.


Testing this with users we discovered that we were on to something as the feedback we got was largely around minor tweaks to the User Interface.


What we took from this was that we had built a superior product, with $70K to that of our multi-national-multi-million dollar competitors.

The Solution

The Results

Fundamentally, we shifted the model here from an open-source model where anyone can do anything to an invite model. The invite model meant that we screened people before inviting them to create content for Ping on the web based content creator.


This meant that we were able to produce a much higher quality content for the end user on the iOS App, ultimately giving them restaurant and cafe recommendations they could trust.


This saved a lot of time as you could find a great restaurant or cafe recommendation with one tap, browse curated list with two taps on an iPhone and search for whatever cuisine you heat desired.

We also made it beautiful, so we made looking for somewhere to eat enjoyable again.


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