Identifying the Broken Publisher Revenue Model to Create New Opportunities

Unlikely connections and doings may lead you to the revenue model of your dreams.

From the start, Jon Roberts kicked off PubForum Coronado Island with profound insight giving the event great momentum. Much of the audience left with the lasting idea that sometimes unexpected journeys lead to groundbreaking discoveries. 

Don’t be afraid to take risks and try new things, publishers. We see this through Roberts’ unique career journey and his assistance in shifting Dotdash Meredith to focus on improving user experience instead of bombarding users with ads. The strategies he and his team implemented to increase user engagement and better understand the publisher’s audience helped reshape Dotdash Meredith’s revenue model positively.

While his journey from research scientist to a digital media professional might seem far-fetched, this path is more common than one may think. From this crossover of disciplines, we see that data analysis, experimentation, and problem-solving skills from the scientific world are of high value in digital media. 

There’s a science behind increasing revenue and effectively targeting audiences in a cookieless world. According to Jon Roberts, these are your four keys to success:

Take Risk: No Risk, No Reward

If there’s one thing science and data have in common, it’s experimentation. Starting his career focusing on dark matter and cosmic phenomena at prestigious institutions like CERN and NASA, Roberts sees data as the central theme in making a transition from science to digital media. Our industry holds loads of data, and its potential for guiding decision-making and audience targeting is immense. The scale of data available presents a playground for experimentation.

At Dotdash Meredith, Roberts and his team implemented transformative strategies that seemed crazy at first since they challenged the conventional approach. These moves were made when the company was small, so at that time, no risk meant no reward. They took revoked ads from web pages in hopes of enhancing user experience. While this calculated risk initially seemed backward, it paved the way for their innovative revenue model. 

Analyze your practices and closely examine ad placements. This can help you identify bad ads. At one point, Dotdash Meredith had to remove a ton of ads from their webpages. This move initially hurt their revenue but helped shape the advertising landscape overall. 

Unravel the Floor Pricing Strategy

Floor pricing can be very complex, which is why it is important to think strategically. According to Roberts, the first step is to break down the value of all the slots to learn what the market will pay. Different domains have different values. Different content drives a different value and then different slots. 

When you look at those features and floors by grouping your inventory that fallsl into these buckets, you can see valued inventory and then push the price up to see how the market responds. 

“We intentionally let 15% of the ads go to house ads because that actually makes us more money because it pushes up what people pay,” Roberts explained. “If you let people buy that 15% of inventory for what they’ll pay for it you get all the long tail scammy advertisers of the internet buying them for pennies. If you put the floor at $10, for example, the people who would have paid $5 for it end up paying $10.”

Develop a Real Understanding of User Intent 

Understanding user intent in the present moment is far more valuable than relying solely on historical data. It’s time to say goodbye to the cookie-based approach and hello to an intent-based approach.

Roberts encourages publishers to think more keenly about intent-based targeting, as it harnesses real-time users’ behavior on content from their tailored ads to match their behaviors. Users’ interests and actions are in constant flux, so present behavior must be at the forefront. 

When you work with the right advertisers, on the right content, with the right message, you will see your engagement go through the roof. If a consumer is on a page doing one thing and the ad on the page is relevant to what they are doing, they will surely click it. 

Historically, contextual targeting doesn’t scale, so you have to talk about the context on the page and feed the user’s intent. 

Think Outside the Typical Measurement Box

Another thing that Roberts highlights is that targeting is easy, but measurement is hard, and while calling targeting easy may be a stretch, getting the targeting to work is relatively straightforward. Getting it to run through all the pipes is more of a challenge because the businesses are so reliant on cookies at this time.

At DotDash Meredith, they are experimenting with some SSP and DSP partners, and learning just how deep the cookie logic is in the weeds. This is where measurement is critical Roberts says, “If you can run a campaign on a cookieless market but can’t explain to your boss that it worked and you cashed out, what’s the point?” 

“We just have to acknowledge that we could never measure everything. If you go through the list of ways clients are looking to measure the efficacy of campaigns, you’ll see first click attribution, or even 30-day lookbacks,” Roberts explained. “But you also have sales lift, brand lift, foot traffic to store. The industry has told itself that deterministic tracking of Internet ads is the only way to do it. So, therefore, if you can’t track, it doesn’t exist.” 

Work with your Privacy Sandbox teams. Targeting is a piece of that, and much of Privacy Sandbox is about measurement and attribution, PPID for frequency capping, and the attribution API to have anonymous but full attribution. These are all tools that need to exist to solve the measurement problem. 

From being a physicist to transitioning into the media industry, Robert’s story is a testament to the power of multidisciplinary thinking and applying scientific principles to solve complex problems in new domains. He has used his expertise in data analysis, experimentation, and understanding complex systems to pave the way for innovative approaches to user experience, targeting, and measurement in the digital media landscape. 

As the ad tech landscape continues to evolve, the infusion of scientific thinking has the power to drive the industry forward.