#9 - Group-Level Strategy for Big Media

Originally published in The Times of India .

As AI technologies reshape the digital landscape, big media companies must transition from open websites to algorithmic walled gardens to not only offset short-term revenue loss (due to Search Generative Experience) but also kickstart long-term growth.

Why Transition Revenue

Throughout history, great companies have undergone transformational shifts to stay relevant, often by creatively destroying their established revenue models.

?The New York Times and FT transitioned from print to digital, Netflix pivoted from DVD rentals to streaming, and Disney evolved from home video sales to the Disney+ platform. Similarly, Apple famously disrupted its own iPod line with the introduction of the iPhone. Today, every car manufacturer is reimagining its factories, supply chains, and skill sets to become electric vehicle producers.?

Such transitions are challenging, akin to landing one plane (new product) on the runway (cash flow) while another has not yet fully taken off (old product).

For media companies, the shift to algorithmic walled gardens represents a similar evolution—one that’s not without its challenges but essential for long-term survival.

Why It Matters

Algorithmic walled gardens collect first-party user data and utilize sophisticated algorithms to target content, products, subscriptions, and ads, often with dynamic pricing tailored to individual users. This approach offers several advantages:

Offset Short-Term Revenue Loss

On-platform consumption can increase significantly—by as much as 50-100%—helping to offset revenue losses due to changes in search algorithms, like Google’s Search Generative Experience.?

Kickstart Long-Term Growth

In the Google Play Store, multiple, often competing apps target the same users on the same interface. Similarly, an algorithmic walled garden is a platform that allows big media to run multiple revenue models efficiently—achieving each revenue model’s top-of-the-funnel targets with limited exposure—and effectively, with higher conversion rates and differentiated pricing.

Targeting improves the effectiveness of affiliate deals, reader revenue products, and ads compared to non targeted, spray-and-pray approaches. Price differentiation algorithms can help improve average revenue per user.

Future-Proofing Against Industry Disruptions

While Big Tech advances into the LLM-driven landscape, media companies must at least catch up with technological innovations from a decade ago to build the data maturity needed to compete in the coming decades.

A Tale of Two Product Strategies

Media companies face a choice between two distinct strategies:

Open Website: Most media companies operate standalone websites that depend on search and social platforms for discovery and distribution . These platforms primarily engage anonymous users who do not log in, resulting in low user retention and low monetization potential.

Algorithmic Walled Gardens leverage logged-in users who provide first-party data. Companies like Netflix, Meta (Facebook, Instagram, WhatsApp), and Amazon exemplify this model, using recommender systems to drive high engagement and revenue. The benefits are clear: higher user retention rates, increased average revenue per user, and the ability to implement dynamic pricing and targeted advertising.

The table below illustrates these distinctions clearly.

However, transitioning to a walled garden approach isn’t without challenges. Privacy concerns, increased complexity, and the significant investment required to develop and maintain these platforms are critical considerations that must be addressed.

But, isn’t it the same running a subscription mandate??

No.?

Subscription as a thin paywall layer on top of the existing ‘open website’ stack isn’t effective long term. In fact, subscription is one of the revenue models that an algorithmic walled garden enables.

Then?

Secure most of the business by keeping the open websites of each brand as is to continue extracting distribution and monetization from algorithmic marketplaces

Building an algorithmic walled garden, i.e., post-login on all websites and on all apps (mobile or connected TV), all users from across all brands collapse into one super website and one super app.

Feed content from all owned brands in the algorithmic walled garden platform. Here’s why it matters:

• Historically, most big media companies have adopted the House of Brands strategy with each publication targeting a specific audience set.
• But this fragments your audience’s loyalty. For instance, a reader might use Vox for news but turn to Wirecutter (part of The New York Times) for product recommendations instead of The Strategist (part of Vox).

Heavily incentivize audiences to move from the open website to the algorithmic walled garden by giving reward points, discounts, promotions, premium content, etc.?

Technically, this is called a ‘hedged garden’ instead of an ‘algorithmic walled garden’ because big media will continue to operate the logged-out websites. Who is using this strategy? Generally, all products that start as ‘open website’ and later transition into ‘algorithmic walled gardens’ often evolve into ‘Algorithmic Hedged Gardens’. These products strike a balance between openness and restriction.?

• A good example is Disney: some lower-end content, like cartoons, is available on YouTube, while premium content is exclusively within their algorithmic walled garden—Disney+.?
• Other examples include the New York Times and Zomato, which similarly balance free access with exclusive, gated content.

A Tale of ‘Two’ Product Strategies

The ‘open website’ and ‘algorithmic walled garden’ products require fundamentally different sales, business, product, technology, and editorial teams. Below are few examples:

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Organization Structure Change

Pulling this off isn’t viable without organizational structure change.?

Here’s how: Collapse all media brands into two business units (and thus two P&Ls):

1. One for the open website.
2. One for the algorithmic walled garden.

Typically, a media business organization structure would have a different business head, product head, and editor for each publication. Something like:

Instead of this, collapse it into:

What about The Editorial Organization?

Today, most news products are a chimera, a tangled mix of mismatched elements struggling to form a coherent identity. Hence, there is constant activity in the product/technology (distance) but limited outcome (displacement).

In contrast, the algorithmic walled garden should be constructed as a platform, much like SubStack, YouTube, X, Kindle, App Store, etc. and on top of which different items are distributed and monetized, which include:

• Content
• Monetization

Monetization can be divided into ads, e-commerce products, events, subscriptions, courses, affiliate deals, etc.?

May a thousand flowers bloom. Similarly, there are hundreds of small, independent editorial teams covering audience interests from multiple perspectives. The focus of the central editorial team moves to identifying opportunities, building an incentive structure, and ensuring trust and safety.?

But why has no news company done this?

Lots of reasons.?

One key reason is that most targeting algorithms built are for e-commerce, social media, or long shelf-life content media like OTT. There is limited work done internationally on balancing nuances of a scaled up news product.

Additionally, transitioning to a walled garden approach requires significant investment in technology and data management.

Conclusion

In an era where data drives decisions, transitioning to algorithmic walled gardens is a viable option for big media companies to consider. I am eager to hear if you have other strategies that are substantial enough to meet the needs of a large media company. I would love to hear your thoughts.

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Want to republish it? This post was released under CC BY-ND — you can republish it as is with the following credit and backlinks: ‘Originally published by Ritvvij Parrikh on The Times of India . The author retains the copyright and any other ancillary rights to the post.