First, as you can see above, I have rebranded this newsletter to The Medium. It's the same newsletter focused on three to four key trends per quarter, but it is now oriented a bit more narrowly.
As you may have figured out, the new branding is a nod to Marshall McLuhan's "The medium is the message", and a reflection of my focus on the moving pieces of media's evolution from wholesale to retail models.
PARQOR will remain the primary brand, and I will be building out membership services under that brand. Watch this space!
Last, Monday is a national holiday, so the Monday AM Briefing will be sent on Tuesday.
The Medium offers deep insight and analysis of the media marketplace as the business models for "premium content" are redefined by creators, tech companies and 10 million emerging advertisers
In Q2 2023, The Medium will be focusing on three trends. This essay covers "'The definition of scarcity is continuously evolving away from linear and towards walled gardens.”
After leading venture firm Andreessen Horowitz (a16z) wrote a blog post on the future of Customer Data Platforms (CDPs), it is time to revisit the topic. I have not written about CDPs since last September, when I discussed whether CDP *software* represented a paradigm shift in media.
What is a CDP? They have primarily been built for in-house marketing teams as customer relationship tools. They are intended to solve for the historical operational pain point of multiple teams with multiple databases that often have the same customers but are not able to share data (or prefer not to). A CDP “can unify that data, help teams slice and dice audiences, enrich customer profiles, and paint an overall customer profile for the business team to act upon.”
I have long assumed CDPs will serve as the hub and spoke solution to the question “Media companies have millions of consumer credit cards on file. What are they building for their customers?”.
I previously believed that media companies who are successfully able to reorient their operations around a CDP are more likely to solve for the pivot from wholesale to retail. A CDP should facilitate the launching, marketing and ongoing management of direct-to-consumer (DTC) businesses.
For example, when Paramount Global launched The Paramount Shop in March, a CDP would centralize both Paramount+ and Paramount Shop customer data. This would allow the Paramount Shop team to determine which Paramount+ subscribers watch “1923”, and then market “1923” merchandise to viewers of the “Yellowstone” offshoot series. In the past, that data was typically siloed.
So, as I asked in today’s Medium Shift column, why don't we see more DTC product launches like the The Paramount Shop? I think the a16z essay, and data entrepreneur Jonathan Mendez’s response to it both offer some valuable insights and answers.
Key Takeaway
Data warehouses are rapidly become more advanced and as marketing and advertising technology moves to the cloud. Could these rapid changes be a reason for media companies' inability to successfully pivot from wholesale to retail?
Total words: 1,300
Total time reading: 5 minutes
The CDP or the data warehouse?
The a16z essay argues that, to date, CDPs have been “magic wands mostly waved by the marketing specialists at large organizations in the name of customer segmentation and identity resolution for more accurate ads.” But, the CDP has evolved quite a bit recently because the data stack — basically, a collection of various technologies that allow for raw data to be processed before it can be used — has evolved, too [NOTE: a16z is “talking your own book” in its post, highlighting select investments it has made in data stack-related businesses, while leaving out mentions of other companies in the marketplace].
The data stack has become more centralized around the cloud data warehouse - increasingly the system of record or authoritative data source for all consumer data owned — and that has resulted in a dilemma facing marketing and data leaders: “Where should we consolidate the customer data, the CDP or the data warehouse? And, more importantly, where does that leave business users who need access to customer data in a fast but trustworthy manner?”
There are two ways of looking at this dilemma through the PARQOR lens.
First, it suggests why media companies have struggled with the launch of more direct-to-consumer models beyond streaming. It is a common sense question: How do you build services that target consumers across multiple channels when the technology for targeting consumers is evolving rapidly?
If CDPs were the preferred solution last September, they seem less likely to be a solution, today.
Second, anti-tracking initiatives across the marketplace are pushing advertising technology or AdTech away from software as a service vendors and into the cloud. As Myles Younger, Head of Innovation and Insights at U of .Digital notes in a presentation ”Meet Adtech’s Newest Frenemy: Cloud”:
Adtech needs audience and event data.
This data is increasingly blocked from traveling the web by anti-tracking tech in browsers and mobile devices.
This is forcing more data to move on a server-to-server basis using Cloud backends.
Meaning, there are technological and legal obstacles to connecting the dots between user data and then using it for commercial purposes. Building the solutions in the cloud circumvents key legal and technological obstacles.
The CDP solution is no more (?)
This is why Jonathan Mendez’s contrarian perspective is valuable here. He thinks that a big part of why we don’t hear much about CDPs anymore is because “The customer data platform is the data warehouse.”
So, what we are witnessing in real-time are media companies trying to build and evolve for their own consumer databases. At the same, the advertisers who buy from them are also building and evolving their own consumer databases in response to anti-tracking
These dynamics do not necessarily make it harder for media companies to build and launch direct-to-consumer products and lines of business. But, it reads like it makes it harder to build broader ecosystems beyond a single service or handful of services. In this light, launching The Paramount Shop was not a failure of Paramount Global to have launched it earlier, but rather may have been a success under difficult circumstances.
But, one also has to wonder whether — given the backdrop of upfronts and the growing demand for biddable environments and programmatic inventory — the more pressing issue for media companies is ensuring advertisers remain happy buyers as their demand shifts away from linear. As Younger points out, data “warehouse-native” marketing technology (which allows marketers to create, run, and manage online marketing campaigns and conduct onsite marketing) is “creeping” into marketer data stacks. Meaning, there are first-party apps that now run within the data warehouses that assume the roles of third-party Adservers, Demand side platforms (DSPs), and attribution/measurement.
Effectively, the traditional means by which advertisers buy, serve and track advertising are changing rapidly, enough so that media companies with decreasing operating income (and talent) must solve for the pain points of their advertising businesses, first. Their sell side technology must be compatible with the buy-side's as advertiser technology evolves. If it isn't, ad buyers have plenty of more sophisticated options from the likes of Roku, Google, and Amazon.
A quick note on artificial intelligence (AI)
Over the weekend I will be speaking on a panel at my college reunion. The panel will be focused on Hollywood, and will have classmates who work in the entertainment industry. One of the questions we will be discussing is “The Future of AI in Entertainment aka Are we all out of a job??”
As I argued last year, I think the future business models for videos produced by AI engines are going to look a lot like the creator economy. The businesses best positioned to host all AI-generated content, to target different content to fans of those celebrities with an algorithm, and to monetize it are Netflix, YouTube or TikTok.
But Mendez makes an interesting AI-related prediction in his essay:
“The brand’s cloud is going to handle everything data and the data warehouse or lakehouse is the platform. Owned and paid, merchandising and product, finance and forecasts. Applications and services will operate inside databases filled with rich AI ready data. That is what is actually rising.”
It is a vision of AI as individual native applications sitting within a data warehouse. That is not an answer to the question the panel is being asked, but perhaps it should be. Because the implication is that AI will ultimately dictate which marketing content we will see depending on the data a media company has on us.
This may not sound new, but there is a key difference from the existing, now outdated model of ad servers, DSPs, and attribution/measurement disconnected from each other because they are often different companies or siloed products within a larger organization. The view of us as consumers is now truly holistic, and the decisions that are made about serving us content from data within a warehouse may be made without human insight or guidance.
It reads like the very opposite of “co-dependence” between advertisers and publishers, where both parties cared little for the intersection of context and data. But it also does not read like a solution to it, as it implies that AI applications will understand the intersection of context and data because they will be engaging with both constantly within the same data warehouse.
It is a profoundly different way of thinking about the future of the media business.