This article is the second in a 3-part series that outlines technology solutions to the big challenges that traditional media companies (particularly those in Asia) currently face. If you have not read the first part yet, do take a look here.

May 8, 2016

BuzzFeed and New York Times have showcased two wildly different but enormously effective ways of running an online media website, and building an in-house CMS system has contributed significantly to their success.

New York Times has developed Scoop, which allows journalists to manage workflows and collaborate in real-time. BuzzFeed has developed a CMS that lets users create listicles, quizzes and other interactive articles with ease. Both these systems serve wildly different purposes, but add critical value.

However, most traditional media sites — and practically all in Asia — are still using CMS systems developed by external vendors or legacy systems. This has two drawbacks.

1. Editorial and product teams are unable to add functionality into the CMS without going through weeks of submitting change requirements and liaising with the vendor
2. Even minor changes (like modifying the order in which something appears on the home page) can take longer than expected because developers do not have access to the CMS code

A. Integrating point-of-publishing analytics in the CMS

While I am a fan of both BuzzFeed and the New York Times, I believe that there CMS systems can (and should) do more in an era that is increasingly defined by predictive analytics. Moreover, CMS systems should allow publishers to reuse content components in order to reduce the turnaround time for producing an article.

With this in mind, we created our own CMS system at The Broadline. This CMS has 3 main features.

1. Identifying bad headlines, and giving suggestions for improvement

Over the last 4 months, I crawled through all links published by major publishers every 30 minutes, and studied how content spreads across the web (in the Indian context).

I did this to create a social listening tool that shows what India is talking about on Facebook in real-time (more on this in the next post), but a great side effect of this was that this gave me a huge repository of content that showed what headlines and content work on social media.

I then codified this into an algorithm that tells you when a headline is “bad”, and gives suggestions to improve it. While this does not guarantee that your content will be successful, it does do a reasonable job at weeding out ineffective headlines.

Integrating algorithms like this with the CMS means that journalists can be given quick, intuitive advice about how they can write better articles without disrupting their typical workflow

2. Telling journalists how long someone will take to read their content, and how complex it is to read

Journalists can often misjudge how long someone will take to read their content, and they can also misjudge how easy there article is to read. While there is no formula for judging the best content length, or the best readability level, journalists perception of these should be objective in order to ensure that the content written is appropriate for the audience it is meant for. For instance, it would make little sense to write a scholarly piece about juicy celebrity gossip.

To counter this, we integrated Medium’s read time algorithm and the Flesch-Kincaid grade level in our CMS so that the writer could get feedback about these parameters before the piece was published.