In a new series, we will be comparing user feedback for apps in a variety of domains using our unique approach to Natural Language Processing that combines machine learning with human curation. In the first of the series, we compare two US banking apps.
Subjects – American Express vs. Chase Bank
Data Source – Apple’s iOS Store
Time Period -
Customers indicate a positive overall sentiment for both companies, but Chase experiences a higher positive sentiment than American Express. It should be noted, however, that Chase’s positive sentiment is trending downward. As expected, the trend of positive sentiment tracks the ratings for each company.
The primary difference between Amex and Chase is navigability within the app, with Amex lagging behind Chase. Additionally, customers do not rate Amex as high as Chase on quick access to updated account details
The bottom left quadrant represents opportunities for either company. While neither Amex nor Chase is performing highly the rewards tracking dimension, an improvement on this dimension could indicate an opportunity of differentiation for a company.
For a full report please click here
If you want to learn more about how SetuServ deploys this optimized solution for its clients, please visit us at our website www.mineforinsghts.com
Posts Tagged action
The App market is hyper-competitive – For example, there are 100+ apps on Google Play store that allow you to create custom photos by cutting the image from one image and pasting it to the other image.
Also, customers are highly engaged with these apps. 100k+ customers rated these competing apps, and their reviews are a gold mine for insights on what customers love, hate and request. Identifying and acting on these insights is crucial to building a competitive edge in such a crowded market.
For example, one of the app makers mined thousands of app reviews & identified a high priority feature that customers requested on a consistent basis – “Adding a zoom feature for more precise cut/paste operations”. When the app maker added the first feature to the app in late February, customers got what they wanted and the reviews requesting that feature no longer showed up as shown in the blue line below -
However, a new relevant feature request started showing up in the reviews in March – “Ability to hide/unhide the magnifying glass”, as shown in the purple line graph above. Customers said that the newly rolled-out zoom feature overwhelmed their photos. When the app maker acted on this request by May, those comments went away in subsequent months.
This is an example of how app makers can use the feedback from their customers to improve their apps, assess how well they are working and stay ahead of the competition. However, recognizing and prioritizing feature requests or bugs amongst thousands of reviews is not easy with a cursory reading of reviews. A more systematic and scalable review mining approach is required to capture the insights that are actionable.
Given the constant threat of churn & the crowded competition, it pays to pay close attention to what the customer tells you and to act on it.
If you want to learn more about how SetuServ deploys this optimized solution for its clients, please visit us at our website www.setuserv.com or click here for a demo on synthesizing reviews.