SwipeX

About the Product

SwipeX is a mobile web feature that allows users to read the news more productively via bite-sized summaries. The aim is to encourage users to read more stories that they enjoy and be exposed to other topics.

SwipeX aims to:

Pique curiousity – it delivers news in summaries to make news reading more productive.
Personalisation - it learns the reader’s reading habits and preferred news stories and feeds the user content that interests them.

Our team studied the interests of millennials today and surveyed popular features of several social media platforms. Through our research, we were inspired by certain features of Instagram stories and Tinder, where users swipe for the next story/profile cards out of curiosity.

With our tool, each swipe presents the headline of the story and a summary for the readers to browse through. Readers can also choose to read the stories they are interested in by swiping up without having to go to another browser or application.

As the reader swipes for more cards, the algorithm will suggest other stories that the reader may potentially want to read. Eventually, readers will receive a mix of explorative news stories and stories that will most likely appeal to them through the feature, retaining the interaction of our readers for days to come.

Key Features

User onboarding - User taps on the SwipeX bubble and is introduced to a quick tutorial. The 3 tutorial cards provide information about the functions of SwipeX.

Card swiping – Each piece of news is displayed on a card. Users can swipe left to read the next card, swipe right to go back to the previous one, and swipe up to read the full article if interested.

Personalisation – After spending sufficient time on SwipeX, our tool learns the preferences of the user. The tool will start to provide news cards that potentially interest the user.

Metrics – SwipeX will collect and store certain types of non-sensitive user data. The number of unique users a day and the number of new users a day can be measured for reach and growth. The number of users who swiped right for more than about 7 cards and the number of returning users within their first week of use is measured to determine the retention rate. Time spent per card is also recorded to personalise the news stories better.

Future Iterations

We hope to improve the product through further iterations:

1. A save/bookmark function should readers want to read the articles more in-depth at a later time.

2. Editor’s Pick or Popular Read category with curated articles of importance to encourage users to read more widely.

3. Introduce a free subscription or sign-in model to push notifications and collect more data to curate more personalised articles

4. Sophisticated machine learning that will recommend articles to users based on other users of similar reading habits

Product Demo