‘Lifting all boats’: Publishers explore total revenue optimization

As publishers diversify further beyond advertising with subscriptions and other audience revenue streams, they are thinking carefully about how to prioritize monetization opportunities to extract as much revenue as possible from their audiences.

This holistic approach to audience monetization — often referred to as “total revenue optimization” or “total monetization” – seeks to understand and optimize revenue generation across a range of sources including subscriptions, advertising, e-commerce, licensing, events, and more. The goal is to enable various revenue streams to work alongside each other in a way that maximizes publishers’ overall revenue and ultimately squeezes as much revenue from individual audience members as possible.

Efforts to optimize total revenue are in their infancy, but publishers’ changing business needs and priorities, advances in artificial intelligence and analytics, and the availability of more robust data have all helped accelerate interest in recent months. As a result, conversations about “balancing” different revenue lines are quickly evolving into ones focused on boosting revenue instead.

“Subscriptions and advertising can be at loggerheads sometimes, but I would argue they don’t have to be. What if it’s not a balancing act but an optimization game we all need to play?” said Fortune Media’s chief customer officer, Selma Stern.

Publishers experimenting with the idea of total revenue optimization are doing so to varying degrees. Some are taking more human-centric approaches and attempting to break down “silos” between different departments and teams across their businesses. This often involves facilitating data sharing and communication and encouraging joint decision-making and compromises that “lift all boats.” Others are exploring ways to incentivize revenue-generating teams to work more collaboratively rather than competing with one another, which could result in the dismantling of compartmentalized revenue goals and “owned” profit and loss statements (P&Ls) in some instances.

Some publishers are going a step further and leaning on technology to make automated revenue decisions. This requires dynamic approaches to paywalling content and a sophisticated understanding of how different parts of a publisher’s business might benefit from specific audience members taking different actions at different times.

For example: One visitor to a publisher’s website might be required to subscribe to access content, while another might be prompted to make a one-off payment. A third might be asked to share personal information in exchange for access, while a fourth might find content freely available but loaded with advertising.

Automated revenue decisions

Fortune Media ultimately hopes to make automated real-time revenue decisions by weighing signals such as first-party behavioral information, content type, device types, time of day, referral source, and many more. It may opt to remove paywalls to monetize via advertising instead, for example, for pageviews it believes have a low propensity to convert new subscribers.

“Our vision is to take all of these different sources of information about the user and build an engine that makes automated monetization decisions on a pageview basis,” Stern said. “Monetization is not a balancing act, it’s a math problem… In the age of AI, extreme optimization will be possible.”

The company is using this approach to improve the “efficiency” of its paywall. The company’s data suggests that 25% of subscription conversions on its site come from 1% of its pageviews, so it’s now showing paywalls only in instances where conversions are likely to occur. Stern said, “We’re converting twice as many subscribers and showing the paywall half as frequently.”

Organizational wins

The Atlantic is also taking a data-informed approach to help balance its subscription and advertising businesses, albeit in a less automated fashion. It employs a framework it calls “unified yield,” which factors in various data points related to its advertising and subscription businesses, and attempts to gauge which decisions and tradeoffs are most likely to drive “organizational wins.”

“If there is a big campaign the advertising team has sold on a section that’s also converting subscribers at a high rate, how do we come to a point where we optimize for what’s best for the organization at large? Unified yield enables us to do that,” said The Atlantic’s chief growth officer, Megha Garibaldi.

Data is being collected centrally and used to fuel cross-department conversation and collaboration, but it is not trusted to dictate decision-making.

“We don’t always input things into this model, but we operate with this idea in mind. When we first put this model out there, culturally it created an environment where people would look first at the data before taking a more qualitative decision,” said Garibaldi.

Demand for data

As revenue optimization becomes more science than art, demand for access to comprehensive data and analytics tools is growing. Vendors are launching tools and services designed to give publishers a more nuanced understanding of the relative value of their different revenue sources in response.

The subscription technology and analytics firm, Piano, is currently pitching a new tool to publishers called Ad Revenue Insights, which it says enables publishers to measure and analyze advertising performance to identify the tactics that drive the most revenue. This type of information might then be combined with subscription revenue data to help inform the type of automated monetization decisions Fortune and others are striving for.

“Should a particular article for a particular user at a particular moment be locked or open? Is it better to let [a user] keep reading and see more ads, or to lock content and get them to become a subscriber? Those are the questions that ad revenue insights can answer,” according to Piano’s EVP of media strategy, Michael Silberman.

Consultancies and data analytics firms are also ramping up their “total revenue optimization” capabilities. Some are promising to help publishers better measure and understand the relationship between different revenue sources, while others are offering to help restructure internal operations and approaches.

Theory vs. reality

The theory of total revenue optimization holds, but it remains to be seen if and how publishers will be able to implement it successfully. “Lifting all boats” makes sense on paper, but aligning incentives between different revenue-generating teams is often difficult when real-world internal politics and competing incentives get in the way. Similarly, sudden shakeups and reorganizations risk derailing publishers’ revenues if executed poorly.

Opportunities to eke out incremental revenue will continue to catch the attention of publishers in an environment where they continue to face significant challenges to the ongoing viability of their businesses. Conversations around total revenue optimization will continue to intensify as publishers’ direct audience monetization efforts evolve and their reliance on advertising and third-party revenue sources dwindles.