Helpshift’s Review Analytics gives a thorough, actionable breakdown of what people say about your product in the app store. You now have the ability to transform honest feedback into a solid product development and marketing strategy. Every week I’ll provide data-driven insights for an app based on its publicly available user ratings.
Uber has a global average review score of 3.8 on iOS. The algorithm does not include ratings without a review. Using the sentiment heatmap, we can determine how customers felt about the service on a day-to-day basis:
An on-demand service with 4 star ratings is good. However, like any app that does have 5 stars, there is a persistent reason why customers aren’t giving perfect reviews. Companies that research customer feedback will have better products overall, because that knowledge is crucial to find pain points that harm retention. Analytics is the first step when transforming your support center into a retention center designed to maintain LTV and improve ROI. To begin, let’s look at why Uber is “pretty great” but not flawless:
Positive reviews are often more useful than negative ones when discovering product hiccups. In this case, the customer LOVES Uber, yet granted 4 stars because of infrequent crashes.
Uber’s great advantage is their branding; they give the expectation that you have a private driver at your fingertips. When that brand promise is broken by inevitable problems, customers will go to the app store and write imperfect reviews. Uber could address that they are working on the crashes using a real-time FAQ or push messaging after a crash. This would transform many reviews into 5 stars by preserving the concierge experience that they pledge.
Dramafever–another on-demand mobile service–described how they use a knowledge base to get ahead of issues. He updates his FAQ instantly to tell customers he knows what’s happening and is working to get it fixed.
Review Analytics also comes in handy when finding ways to beat the competition. We searched “Lyft” in the database to discover why customers are mentioning them when rating Uber’s app.
We found that every time a customer mentioned Lyft was because they felt Uber provided inefficient customer service at the point of need. Some said resolving issues took several exchanges, and no one wants to email the company while waiting on a street corner at 1am. This is a big sign that Uber should invest in mobile customer care options.
Sean Kauppinen of IDEA explains in our fifth webinar that customer service does not have to be a cost center. When combined with modern mobile tools that provide proactive help at the point of need, support centers will actually improve customer retention and profits. We can certainly see from these reviews that native customer care would stop Uber’s customers from spending money on competitors. The cost of an upgrade would easily pay for itself.
This is how Uber’s customers felt overall:
- Our sentiment heatmap reveals that while most people are happy with Uber, there are consistent issues that bother some customers each day. Uber could research these reviews to iterate their product in a way that grants them a perfect score.
- Small crashes are padded by Uber’s impeccable campaigns and branding. They should continue to bolster their product offerings so that mishaps still garner good reviews.
- Critical topics show that customers love Uber’s service on average. Yet when a problem happens in that moment, customers complain that there is no reliable method to get in contact with the company. Providing proactive help and native messaging is the only way to solve on-demand issues, because a customer will not email you while standing on a city corner at 1am.
- Uber should leverage better customer support options to distinguish itself from Lyft. When analyzing the reviews, we found that most mentions of switching to Lyft were related to bad customer service in the moment of need or when a customer needs answers about pricing.