Why we developed ROSA and why Google thinks it’s good for publishing
Updated: Aug 28
If you’re a content creator or work in publishing then the Google News Initiative Data Lab APAC 2020 Playbook is a must read.
The playbook was borne out of the GNI APAC Data Lab, a publisher-centric program that aims to help Asia-Pacific publishers transform from “developing” to “mature” by adopting data-focused processes.
At Incites we’re especially pleased that our ROSA framework was cited as a best practice by Google for content planning.
What is the ROSA framework and what does it mean for your business?
The ROSA framework is an approach that we have evolved at Incites over the years working with publishers and brands to help them use their data to grow and monetise their audience through content.
Data and analytics can help editors and newsrooms drive results with their content in many and varied ways so we needed a simple way to organize all the different approaches into a coherent framework.
The basic idea is that growth opportunities with content generally fall into one of four categories, that is:
Previously successful content topics and tactics that you should Replicate
Existing content that you should tweak or Optimize
Content that you should Stop (creating)
Content that you should Amplify ie through paid or organic channels
How does Incites determine which content to Replicate, Optimize, Stop or Amplify?
The ROSA framework is a data-driven approach to developing actionable insights. Not only does our ROSA framework provide insight into what is currently happening within organisations and markets, it also provides actionable recommendations to further enhance workflows and reduce operational costs.
We came up with this framework by defining the overarching business objective (e.g. a specific conversion outcome), generating a score for each article in relation to this business objective, and comparing this with scored metric(s) which represent how well content is reaching their audience. At the core of our ROSA framework is our scoring algorithms which score data points on multiple criteria defined by business objectives. Based on these scores, data points can then be plotted on a plane and use its associated location to drive the actionable ROSA insights.
For example, the “Replicate” articles are identified on the basis of well they outperform other articles in terms of driving brand-lovers, registered or subscribed users both in terms of audience size and average time-spent.
“Optimize” articles over-index in terms of attracting an audience but under-perform in terms of driving outcomes like engagement and recirculation.
“Stop” articles are those that attract little to no audience and do not engage users. Establishing a pattern in terms of common characteristics of these articles is key to ensuring that resources are not wasted on these types of stories.
“Amplify” articles over-perform in terms of engagement and recirculation but have not over-performed in terms of traffic or audience size. Consider what would be the most effective channels to re-promote or redistribute this article.
With incites.ai, we use ROSA to literally tell storytellers what stories to tell
The incites.ai platform helps publishers grow reader revenue by delivering actionable AI-powered insights, written in simple natural language, to their newsrooms.
Instead of dashboards, the ROSA insights are delivered as actionable messages directly into the editorial workflow eg. as messages posted automatically into Slack, MS Teams, Content Management Systems and anywhere work happens.