Designed a data driven UX for a news aggregator platform


2 months


Design recommendations, Research artifacts

Alirtify wants to help people find trustworthy news

Alirtify is a news aggregator and forum where users engage with news through likes, reactions, and comments. Kobe's vision was to enhance trust in local news by enabling interactions among close friends and family on the app.

We were brought in to ensure the app aligns with user needs, identifying user groups and proposing design ideas accordingly.

How can Alirtify become the go-to platform for news validation?

After a discussion with the CEO of Alirtify, Mr Kwabena Okrah, we derived at the following set of questions that were to be the focus of the study:

  • How do people consume news (products, apps, internet)?

  • How do people currently validate news?

  • How can we help people validate news?

Existing design analysis

I found that showing the news source is crucial for user engagement, even though the current app doesn't highlight it enough.

I noticed that the app only showed interaction details from the broader world for each news article, without indicating how many close friends or family members engaged with it. Yet, our research emphasizes the significance of validation from one's social circle in determining user engagement with articles.

Recommendations which leverage social network

Better notifications of subscribed or interesting topics can be pushed to the user's device. The interesting topics can be related to people/contacts they follow or pertain to a particular region, thereby keeping the user's always updated.

We can enhance user experience by recommending topics of interest, such as those related to followed contacts or specific regions, to keep them always informed.

Recommendations - Presenting the facts

Our investigation revealed that clickbait headlines consistently repel readers. Alirtify can leverage AI to transform original headlines into unbiased ones, aiding users in understanding content and curbing the spread of misinformation by discouraging discussions based solely on headlines.

Users can gain a comprehensive understanding of the focused article by integrating links from trending articles via search engines like Google. Placing these links below the article summary in the initial view provides users with a broader context of the news story they're reading.

Additionally, incorporating government-backed data can empower users to make informed judgments, enhancing the article's impact.

Going ahead - Identity, DP models

We employed the identity model to outline user personalities, beliefs, and behaviors regarding news consumption.

Each identity comes with associated "Give Mes," offering specific suggestions to enhance the user experience within that identity cluster.

We utilized the Decision Point Model to uncover factors influencing users' decisions to engage with news.

These insights can inform feature conceptualization and validate design decisions, ensuring our product effectively delivers trustworthy news.

Interviews & Affinity maps

We conducted interviews to investigate behavior patterns in news consumption and validation, targeting users across various age groups and occupations. Utilizing affinity mapping, we analyzed user data to gain a comprehensive understanding of the issue.


Initially, we lacked clarity on our target audience, but identifying user types now strategically guides future studies.

Also, involving more stakeholders from journalism and academia can better identify problems and validate solutions.

Introducing Kobe to human-centered design techniques was a valuable experience. Kobe expressed delight with the experience, noting it provided him with a fresh perspective on tackling design challenges.