DIGITAL DESIGN

MIC CMS PRODUCTS

MIC CMS PRODUCTS

The Mic CMS is a suite of powerful products built in-house to help the many teams of the company work at peak performance. As the design director at the company, I along with others on the product team, built the CMS from a single application to a series of many tools that became the backbone of the company. Below is a small selection of products that were built for the CMS.

BRAND

Mic

ROLE

UX Design, UI, Production

YEAR

2013-2016

Article Preview, Distribution, & AB Testing

Building on the Mic Article Editor, the team wanted to be able to have more control over the distribution of articles, specifically how the articles would appear on social media. Our data showed that articles performance on Facebook was effected by the cover imagery, whereas Twitter users are more likely to click through because of a descriptive headline. We wanted the ability to optimize all aspects of an article before pushing to social. Over a period of a year, we iterated on a distribution product to push out content and A/B test it in order to determine the strongest combination for any given article.

Like many other products in the CMS, the article preview utilized a tabbed interface allowing users to view mobile, Facebook, Twitter, and tumblr views. Each tab allowed for various levels of override to target the audience demographics of that medium. Users could then create variations of overrides to test out article packages to a small segment of users. Tests could last minutes or days and then deliver analytics data to a custom database viewer.

Building upon the Mic Article Editor, the team wanted to be able to have more control over the distribution of articles, specifically how the articles will appear on social media. Our data showed the articles perform better/worse on facebook based on the cover imagery, whereas twitter uses are more likely to click through via a descriptive headline. We wanted the ability to optimize all aspects of an article before pushing to social. Over a period of a year, we iterated on a distribution product to push out content and A/B test it over other variations in order to determine the strongest combination for any given article.


Like many other products in the CMS, the article preview utilized a tabbed interface allowing users to view mobile, facebook, twitter, tumblr views. Each tabbed allowed for various levels of override to target the audience demographics of that medium. Users could then create variations of overrides to then test out article packages to a small segment of users. Tests could last minutes or days and then deliver analytics data to a custom database viewer.

article preview
AB-Testing-Results

Content Stream Queue

Once people finish reading an article on a site, how do you keep readers on the page? Keep showing them more content! In order to increase explorability and time on site we created a seemingly infinite continuous feed of articles for our readers. Unlike most competitors, these articles were not being added chronologically or even algorithmically. We wanted to have full control over what articles are shown to readers and when using as much data as possible. So we built a content stream queue that would allow us to program exactly what articles appear anywhere on the site and allow us to leverage the current site analytics data at the same time.

We designed it to be easy to use for any new team member but advanced enough to be leagues ahead of what competitors were doing. The database showed the sitewide default queue order as well as an article specific tab within the interface. Users could search for a variety of content types to then create a new queue for. Below every queue, users would see the most shared per view, most shared today, and most recent articles in which they could quickly pull from. The database allowed for drag and drop placement for reordering. Finally, without human intervention, the CSQ would default to appending new content with a queue of the most shared articles.

Once people finish reading an article on a site, how do you keep readers on the page? Keep showing them more content! In order to increase explorability and ‘time on site we created a seemingly infinite continuous feed of articles for our readers. Unlike most competitors, these articles were not being added in chronologically or even althoritmically. We wanted to have full control over what articles are shown to readers and when using as much data as possible. So we built a content stream queue that would allow us to program exactly what articles appear anywhere on the site and allow us to leverage the current site analytics data at the same time.


We designed it to be easy to use for any new team member but with advanced enough to be leagues ahead of what competitors were doing. The database utilized a tabbed interface showing the sitewide default queue order as well as an article specific tab. Users could search for a variety of content types to then create a new queue for. Below every queue, users would see the most shared per view, most shared today, and most recent articles in which they could quickly pull from. The database allowed for drag and drop placement for reordering was as easy as possible. Finally, without human intervention, the CSQ would default to appending new content with a queue of the most shared articles.

content stream queue

Lexicon

Lexicon is a database product built to assist our editorial & programming teams. It was a product built from the ground up specifically to leverage data for articles on media sites. It began with a request from our distribution team; they wanted to be able to gauge insights into the distribution of articles by leveraging big data. As the media landscape was moving forward, it was obvious that being able to gauge what readers were responding to was key to be able to anticipate what readers would want next. Working directly with our Director of Growth Product, we set up a system for how to successfully build a product that could gauge editorial trends.

Lexicon allowed people to view all analytic data related to an article in one view. Analytics include total amount of readers, click-through rate (CTR), shares (STR), and time and date it was initially shared on Facebook. Furthermore, people could segment articles based on sections, date range, headlines, and Facebook posts.

Lexicon is a database product built to assist our editorial & programming teams. It was a product built from the ground up specifically to leverage data for articles on media sites. It began with a request from our distribution team; they wanted to be able to gauge insights into the distribution of articles by leveraging big data. As the media landscape was moving forward, it was obvious that being able to gauge was readers were responding to was key to be able to anticipate what readers would want. Working directly with our Director of Growth Product, we set up a system for how to successfully build a product that could gauge editorial trends.


Lexicon allows people to view all analytic data related to an article in one view. Analytics include total amount of readers, click-through rate (CTR), shares, (STR), and time and date it was initially shared on facebook. Furthermore, people can segment articles based on sections, date range, headlines, or whether it was ever posted to facebook.

lexicon
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