Goal: Is to create a common news platform to provide latest content or updates.

Clarifying Questions: Is this an mobile app(Yes)

Are we designing for Global or US: US

Are we targeting user aquisition right? Yes

Different set of personas

1) Regular reader who has ample amount of time to read different topics

2) A reader who has limited time and wants to just get latest news

3) Reader who is focused on specific topics like Politics, Sports, tech etc

4) Content Moderator

I would go with person who has limited time in work day and just want to get latest updates about the day.

Use cases for this persona:

1) I want to know top news from US as I have limited time.

2) I should be able to comment, share or like the content

3) If I miss reading,  I should get daily digest or something

4) Provide notifications around natural calamity, disaster or high alert.

Features                                    Importance to Persona                      Implementation

1. Sign Up/Register                Low/medium                                     Use FB SSO

2. Provide top news                          High                                      Use  reading Score

3. Send email if u miss login           medium                                    easy email digest

4. content to be share/vote/comment medium                                   easy

Prioritizng features based on importance to Persona: 2,4,3,1

Reading Score: How many people clicked on each content+ no of votes+ no of comments+ no of times shared

Metrics: 1) no of mobile downloads

2) no of activations

3) DAU/MAU

4) Avg.no of content clicks in a single session per user

5) Avg. session time

6) % of users clicked at least 1 page

From above 6 metrics, I will be focusing user aquisistion so my primary metrics would be downloads/activations and % of users clicked at least 1 page. And based on the value, i will dig secondary metrics.

Clarification:

• What is the goal of MS in this? Is it drive engagement? Is it another venue to gain considerable ad spend?
  • Ad spend, engagement
• Is it going to be an app or standalone website?
  • App & Standalone website
• What does the product do? Is it going to only curate (or) in the business of journalism and content creation?
  • Curate
• What will be the geo where it will be launched first?
  • USA
• Users
  • Anybody with internet

User Personas

• Morning reader in a commute
  • Characteristics – Busy professionals, lack of time. Prefers a digest with important news
• Avid news reader – Retirees, people with time in their hands spends time visiting many websites and reading news articles
• Young, teens – sports and entertainment fans

I am going to pick the busy professionals personas

• Pain points
  • Lack of time, commute. Needs a site that can be trusted and saves time and effort.
  • Wants to know what’s going on and doesn’t have time to go in depth for every story. Picks and chooses stories that they want to get a deeper understanding
  • Wants to be seen as knowledgeable and understand a topic in a multi-faceted way, diverse opinions
  • Have interest in politics, sports, local, state, entertainment

Prioritization

• Within the topics of curated news, some of the topics are by default trustworthy like game scores, sports results (to a certain extent)
• Have other sources for entertainment news currently
• Political news
• Local news
• State news

 

• I am going to pick non entertainment news along with sports as first order of implementation

Implementation

• Since we are in the creating a trustworthy curation of news , I am going to use a methodology similar to how ad/page ranking model works to score every news
• Classifying the trustworthiness of news using a trust index/number which is a number that can be derived from some algorithm, composing of many pillars, few of them below
  • Source of the news – website
  • Journalists if mentioned
  • Number of citations that have quoted this as a source – This can morph into a problem with virality. Care should be taken as when the virality goes up to do fact check
  • References to sources of information quoted in the news article
  • Automated Machine Learning/AI contextual analysis of the news
  • Automated fact checker – highlighting facts and opinions in a news article, Calling out data as not verified. If flawed calling out using a color coding
  • Tagging every article as the kind of story
    • Opinion/Point of View
    • Interview
    • News article
• On a curation/digest level, diversity of news is also important to help understand other points of views
• While sending curated digests, we will also send another link that might be offering a different point of view as identified by our AI model with tags like “you might like”
• Crowd sourcing for verification of facts

Evaluation

 

 

 

 

Metrics – Not focusing on ad metrics currently

 

• App
  • # of downloads
  • % increase of # of downloads  week, month
  • # of updates to software
  • # of profiles filled with preferences of news sections
  • # of App opens and histogram of App opens over time (daily, week, month)
  • Time spent in app (per user, cumulatively)
  • Time spent per story
  • # of shares of app
  • # of shares per news article
  • # of uninstalls
  • # of Crowd sourced fact verification requests
• Website
  • # of daily visitors, weekly, monthly
  • # of unique visitors, daily weekly monthly
  • % increase in visitors unique
  • # of accounts created
  • Pages per session
  • Session length
  • Bounce rate
  • Exit rate

Summarizing

 

Bulding a news ranking AI system using contextual analysis, crowd sourcing of validation