We live in a world where there is no shortage of data: first-party, third-party, and zero-party. However, most publishing organizations run the risk of boiling the ocean with too much data at their disposal and too little actionable insights to be gleaned from it. In my view, data visibility can bring alignment across multiple departments of a publishing organization and steer the organization towards common goals.

This post is about two specific use cases and actionable insights from first-party data that publishers can use to optimize their editorial and subscription strategies. These tangible use cases can help you seed a solid foundation for a data driven organization.

Using data to optimize editorial strategy

Most publishers rely on last touch attribution to understand which content converts users to subscriptions. No matter what attribution methodology you use, there are gaps in coordination between the editorial and marketing teams at most media organizations – which ultimately results in leaving subscription revenue on the table. Let’s take this 2×2 scatter plot as an example:

The ability to plot each piece of content on a conversions versus pageviews scatter plot can distill strategic outcomes for the entire organization. Each quadrant on the scatter plot leads to actionable insights for different departments:

1. High Conversions – High Pageviews: This segment of content is being marketed well and is generating high conversions. Maintaining status quo with all departments is recommended with content falling in this quadrant.
2. High Conversions – Low Pageviews: This segment of content is being marketed poorly but has high conversions. The marketing team should take action to promote this content across all of its channels.
3. Low Conversions – Low Pageviews: This segment of content is not converting. The action is on the editorial team to reconsider its strategy for this type of content. Alternatively, the subscriptions team can consider trying a lower priced offer for this type of content to test if the conversions go up.
4. Low Conversions – High Pageviews: This segment of content can be earmarked outside the paywall to maintain a healthy balance of site traffic.

The main takeaway to consider here is not about data collection but more about data representation and the importance of data visibility within the entire organization in near real-time. A simple graphic like this can help editorial and marketing teams understand what actions need to be taken. Still, there needs to be alignment on common goals, constant coordination, and outcome based service level agreements (SLAs) in place to execute on any editorial strategy.

Using simple data points to convert never-subscribers

Almost every publisher has two main types of audiences: ardent fans and casual users. For the sake of simplicity let’s call them subscribers and never-subscribers. To convert never-subscribers, you first have to know who they are. The good news is you don’t necessarily need sophisticated AI to understand who your never-subscribers are. There are many simpler options and proxies at your disposal.

Assuming you track the digital footprint for anonymous users, you can track which users have rejected your subscription paywall once or twice in the last 30 days. It is a clear indication that the user is casual in nature and potentially seeks another offer in order to convert to a paying user. Lowering the hurdle to a bitesize offer might be a prudent move at this stage.

Another proxy to identify never-subscribers would be to dissect the sources of your site traffic. Other than direct traffic, you will have traffic coming from social media, chat apps, content aggregator sites, search, paid media, etc. Attributing a scoring mechanism depending on the source could quickly help decipher if the anonymous user is a potential subscriber or not. For example, you may find Twitter users have a higher propensity to subscribe but Facebook users are very unlikely to subscribe. With this in mind, you should show a lower threshold offer to users landing from Facebook.

If you have global audiences, you could dissect anonymous users by geography. For example, you might say that domestic users are more inclined to take my all-you-can-eat subscription while international users will require a lower entry barrier. With this in mind, I might offer an introductory bitesize subscription option.

Here is an example that publishers can use to segment their audiences from very basic traffic data:

At the end of the day, if you are in the digital subscriptions business, your objective is to maximize your recurring revenue. This requires you to understand the lowest payment threshold an individual user is willing to commit to. With that information in hand, your marketing team must make a concerted effort to re-engage the user to move up your value chain.

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About the author

Abhishek Sharma is a Co-Founder and CTO of Fewcents, a plug-and-play solution for publishers and creators to collect small payments in 80+ currencies. He has 18 years of experience in strategic consulting, vendor management, project and delivery management, business analysis, solution design, and application development. He specializes in building high-frequency trading systems, integrating with payment partners such as Paypal, Stripe, etc, and working on regulatory risk engines using big data technologies. Prior to this, Abhishek worked at DBS Bank, Credit Agricole, and MSCI Inc.