When you're tired of the same old Chinese restaurant on the corner and want to try something new, when you're looking for a last minute day care service for your kids, when you suddenly develop an unbearable tooth ache in the middle of a trip, if you are like most people out there, you are happy to turn to an online ratings service to get a recommendation.
In a 2013 study conducted by Yelp, more than 100 million consumers were recorded to have checked ratings for companies in 97 U.S. and international markets in just the first three months of the year. This trend only seems to grow every year. However, according to a newer study at the University of Colorado, Boulder, the belief that online user ratings are good indicators of product quality was largely found to be but a mere illusion. Author of the study and professor of marketing at CU-Boulder's Leeds School of Business explained, “The likelihood that an item with a higher user rating performs objectively better than an item with a lower user rating is only 57 percent.” She continued, “a correspondence of 50 percent would be random, so user ratings provide very little insight about objective product performance.” Then where exactly, can we find reliable reviews?
This is where Ezi (Eh - zee) was born. First, Ezi means "pig" in Igbo, which is why we made our mascot the pig, both for the app's icon and our review rating system. But more importantly, Ezi comes from the Igbo word for "genuine" and reflects our interest in providing users a platform to present genuine reviews of people's job experiences for both future employees and employers. Ezi also means "pig", which is why we chose a little pig for our app's mascot and review rating icon. What makes our application unique from Glassdoor or Indeed or any the many other pre-existing platforms is how we collect our data. Ezi utlizes the sentiment analysis of employee reviews and potentially doubles the accuracy of current job search algorithms.
The user first types in a job position or title they are intersted in applying for and inputs a location. The app then takes the user to a results page ranking companies by the postive employee feedback rate. So for an example, a company ranked at 87% indicates on average, 87% of the feedback of past and current employees with similar job positions and titles wrote positive reviews about their experience working at the company. In other words, users can compare companies based on the reviews written by past employees who have worked in the user's interested job positions.
Although Ezi's main platform is to connect users to a better, more meaninful work experience, ultimately we see Ezi as a product of our interest in improving search and Machine learning algorithms. We believe Ezi's applications are quite frankly, infinite. Whether it be movie reviews, product reviews, or any form of text feedback, we are hopeful that Ezi's algorithms can help shape a future where reliable information is accessible, thus guarenteeing the best experience for all users.