On this episode of the Publisher Lab, we have a special guest filling in for one of our usual hosts, Tyler Bishop–it’s our Digital Content Manager, Anthony Moore!
Anthony just rejoined the marketing team after taking some paternity leave and although he feels sleep-deprived, he’s happy to be back in the office.
While we can’t get completely away from talking about generative AI, we did have some great topics that had nothing to do with it.
Watch the podcast on YouTube or wherever you listen to podcasts, like Apple.
Are PMP deals the future of advertising revenue?
While ad rates may be down, programmatic advertising is on the rise when you consider if ad dollars are going to print or digital; it is estimated that by the end of 2022, companies spent $123.22 billion on programmatic advertising.
In previous years, this money was mainly put into open exchanges, but increasingly more advertisers are wanting to engage in exclusive marketplaces with premium inventory. These are called PMP deals, or private marketplace deals.
PMPs are increasing in popularity because of ad fraud; in a report by KSM Media, it was estimated that 18% of open exchange inventory was ad fraud. This comes out to approximately $1.4 billion of loss per year for advertisers.
PMPs are conducted through a deal ID to make a bid that is assigned to an inventory package, which can then be purchased by advertisers through demand-side platforms.
When looking into PMPs, you may come across two types of deals: a private auction versus a preferred deal. Private auctions are composed of publishers who offer inventory to a select group of buyers, giving them priority to bid before going to the open exchange. Preferred deals are usually a one-to-one deal for a fixed, negotiated price; if the buyer doesn’t want the inventory, then it goes to open auction.
PMPs can be beneficial to both publishers and advertisers. They give publishers more control over their inventory, can result in advertisers paying a higher CPM (cost per mille), and are less work than direct sales. For advertisers, PMPs can be favorable because they often get direct access to data on their audience and traffic volumes, spend less time negotiating, reduced ad fraud, and have greater control over brand safety.
Where publishers may run into issues with PMPs is that bidders could take advantage of publishers. Additionally, there is a sales overhead because publishers have to reach out to advertisers. Since multiple bidders aren’t competing for PMP deals by default, so once an offer is created, it’s important to get it to the right advertisers and sell it as quickly as possible; rather than just putting your inventory out there in an open exchange, there is a bit of sales involved.
Anthony, who has been a publisher a roughly a decade, knows that no matter what is happening in digital publishing, creating good content is the most important and beneficial thing you can do for your website. This provides more appealing ‘real estate’ for advertisers, who will then favor your inventory more. Since your content is high-quality, publishers can then leverage that into making PMP deals.
Publishers that are able to be versatile and learn new skills are going to fair better in the long run, and that includes learning how to branch out with advertising. A publisher is not just a content creator—they also learn SEO, webinars, email marketing, affiliate marketing, social media ads, etc. Similarly, publishers who are open to learning about something like PMP deals are going to have more opportunities.
This is especially important as ad fraud becomes more prevalent; advertisers are going to turn to private deals increasingly more if ad fraud isn’t contained in some way in the near future, and unfortunately, that doesn’t look like it’s going to happen.
As TikTok and AI-Powered Bing rise in popularity, advertisers still stick to Google
As the marketplace becomes increasingly more saturated, digital advertising costs continue to rise. This, and the ever-changing ways people search the internet, are prompting advertisers to look for ways to diversify.
A large portion of the younger generation, Gen Z, use TikTok or even YouTube as their means of search over Google or use sites like Reddit or Amazon as product information search resources.
However, even though search is shifting, many advertisers aren’t ready to put money towards much outside of Google and risk brand safety before these other options are more vetted. Additionally, as the economy continues to change this year, there is less willingness to experiment. And really, TikTok cannot become a real competitor against Google unless its search became more efficient and the company scaled more.
Because of this, Google is likely not that concerned with the rise of TikTok, but it does need to consider how things are changing. There is a lot of data showing that if search engines do not adapt—such as Google pushing its generative AI, Bard—they will fall behind and lose relevancy.
TikTok has only been showing ads since 2019, but their ads are very interactive and it can even be hard to tell that it’s not just content; the same cannot be said for most ads on Google.
If we consider where TikTok and even digital content was five years ago, TikTok was hardly relevant and it was much easier to create a website and get visitors than today. Similarly, it was easier to get traffic on a platform like Medium back then. Now, TikTok is all over, the internet is over-saturated with websites, and Medium has blown up as a way to publish content without having to operate a blog. In five years’ time, things will be drastically different than they are now. Publishers that can hop on trends as they are ramping up are more likely to be very successful.
SEO keyword research in the wake of ChatGPT
With partnerships like Microsoft and OpenAI, generative AI is moving quickly. Though AI-driven chatbot technology has been around for a while, it was not broadly accessible until recently.
ChatGPT has already sped up the way we do research and this includes keyword research. However, publishers should be wary of relying too heavily on generative AI to do the heavy lifting for them; the real value of SEO is still quality research. Currently, generative AI cannot apply the important human touch that keyword research still requires. While ChatGPT can certainly help, such as clustering keywords by topics and organizing them by user intent, it cannot provide the “human differentiator of assessing the psychological nuance of keywords.”
As Anthony explains, it’s like making a cheesecake, which requires precision: all of the ingredients can be measured pretty well and then thrown together, but it would just make an ‘okay’ cheesecake. The accuracy of the measurements and the way in which they are mixed make a great deal of difference. ChatGPT can make an alright cheesecake; humans can make a delicious one.
Publishers can certainly use ChatGPT to do keyword research but relying solely on generative AI to do it all is not going to be conducive to the most effective SEO. Keyword research tools, like Moz and SEMrush are still necessary to pinpoint and nail down the appropriate keywords based on monthly searches and difficulty of keyword.
SEO is constantly changing and adding generative AI into the mix is only adding to that. It is likely that generative AI and tools like it will be integrated into keyword planning tools and content and topic analysis features sooner rather than later. While SEO can be daunting, the more publishers are willing to learn how to use generative AI—especially as it becomes increasingly more involved in keyword research—the better off they will be.