The NBA had a very strong advertising year.

In this episode of Media Monitor, Kelly Sweeney and Sean Wright break down Guideline’s latest NBA advertising report and explain how the league grew ad revenue from roughly $1.5 billion to $2.1 billion in a single season.

A big part of the story starts with distribution.

After Warner Bros. stepped back from its previous role, the NBA expanded across NBC, Peacock, Amazon, ABC, ESPN, Hulu, and other platforms. That created more places for audiences to watch and more inventory for advertisers to buy.

The result was a major increase in streaming revenue.

Sean explains that streaming ad revenue climbed from roughly $10 million to $874 million, driven by a combination of simulcasts, exclusive games, and broader digital access.

Pricing also moved higher. Regular-season unit rates increased substantially, meaning the league would have generated more revenue even if the number of ads sold had stayed flat.

But more changed than pricing.

The NBA also reached an estimated 170 million people during the season, its highest reach in roughly 25 years. That broader audience helped create stronger demand across the regular season, playoffs, and Finals.

Kelly and Sean also unpack why Finals comparisons require care.

A seven-game series naturally creates more advertising inventory than a five-game series. Looking only at total Finals revenue can make performance appear flat. Comparing the first five games of each series tells a very different story and shows much stronger year-over-year growth.

The episode closes with another encouraging signal: advertiser participation was more diversified across product categories, meaning the NBA’s growth was not dependent on just one or two areas of the market.

In this episode:

• Why NBA ad revenue rose from roughly $1.5B to $2.1B
• How streaming changed the league’s advertising economics
• The effect of NBC, Peacock, Amazon, ABC, ESPN, and Hulu distribution
• Why regular-season unit rates increased
• How the NBA reached roughly 170 million people
• Why streaming revenue jumped so sharply
• How exclusive streaming games contributed to growth
• Why the NBA now compares differently with the NFL on streaming revenue
• How playoff demand performed
• Why Finals revenue needs to be adjusted for series length
• The difference between total Finals revenue and game-for-game comparisons
• Why broader advertiser participation matters
• What the next NBA season will have to do to match this year’s performance

Media Monitor breaks down what’s happening across media and advertising and explains what the data actually means.

Follow and subscribe wherever you get your podcasts. New episodes every Wednesday.

If you’d like access to the benchmark report or want to suggest a topic for the next part of the programmatic series, reach out to press@guideline.ai.

If you enjoyed this episode, be sure to follow or subscribe so you don’t miss future conversations on advertising, media strategy, and cultural marketing moments.

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Advertising spend can be growing while the market underneath it is becoming more fragile.

In this episode of Media Monitor, Kelly Sweeney gives Sean Wright a new goal: create an index important enough to have his name attached to it.

Sean may already have a starting point.

Inspired by a discussion of market concentration and monopoly measurement, Sean applies similar mathematical thinking to Guideline’s advertising data to ask a different question:

How much of advertising growth is being driven by only a small number of categories?

Guideline tracks 89 advertising subcategories. Rather than looking only at the headline growth rate for the market, Sean examines how widely that growth is distributed.

If many categories are contributing, the market appears more balanced.

If one or two categories account for a disproportionate share of incremental spending, the headline number may hide more risk than it reveals.

Sean explains that early analysis suggests the concentration of advertising growth may be strongly associated with what happens in the market roughly 11 to 12 months later.

That creates potential applications for agencies, publishers, advertisers, and anyone trying to assess the health of advertising demand.

The current picture provides an interesting example: advertising growth is concentrated among relatively few categories, while spending declines are spread across a broader group.

For Sean, that combination suggests more risk beneath the headline growth number than the topline figure alone would indicate.

Kelly and Sean discuss how a concentration index could help agencies think about negotiations, publishers assess revenue exposure, and industry leaders get a faster read on market conditions without having to interpret dozens of category trends individually.

The conversation also introduces the idea of publishing the new indicator as a recurring Guideline market measure—with the final name still very much up for debate.

And, naturally, Jimothy the raccoon makes another appearance.

In this episode:

• How market concentration can reveal risk that topline ad growth misses
• The economic index that inspired Sean’s advertising analysis
• Why growth concentrated in a few categories can make the market less stable
• Why diversified advertising growth can indicate healthier conditions
• What concentrated gains and broad-based declines may signal today
• How the model could help agencies, publishers, and advertisers
• Using advertising category data for strategic decision-making
• Why a single index could simplify dozens of category trends
• The potential predictive relationship between concentration and future ad spend
• How publishers can assess dependence on a limited set of advertisers
• Why diversification matters for advertising revenue
• The early plans for a recurring Guideline advertising concentration index
• The debate over what the index should actually be called

Media Monitor breaks down what’s happening across media and advertising and explains what the data actually means.

If you’d like access to the benchmark report or want to suggest a topic for the next part of the programmatic series, reach out to press@guideline.ai.

If you enjoyed this episode, be sure to follow or subscribe so you don’t miss future conversations on advertising, media strategy, and cultural marketing moments.

And if you’re listening on Apple Podcasts or Spotify, a quick rating or review helps more people discover the show.

AI agents may automate more of media buying, but WPP’s Devon DeBlasio believes people still need to remain at the helm.

In this installment of Media Monitor: Conversations at Cannes, Guideline Chief Product Officer Steve Silvers sits down with Devon DeBlasio of WPP to discuss how agentic systems could change advertising—from buying media and building audiences to influencing how brands appear inside AI-generated recommendations.

WPP has committed to helping develop standards for agentic buying, working with organizations including IAB Tech Lab and Prebid. Devon explains why common protocols and guardrails matter as buyer agents, seller agents, and MCP-enabled systems begin interacting across the advertising ecosystem.

A central question runs through the discussion:
Which decisions should an AI agent be allowed to make, and which should still require human approval?
Devon describes WPP’s “human at the helm” approach, particularly when actual media dollars are being committed. AI can identify signals, generate potential audiences, surface insights, and automate parts of a workflow, while experienced people remain responsible for decisions with financial consequences.

The conversation then turns to audience strategy. With large pools of historical performance data and increasingly capable models, agencies may be able to create more tailored growth audiences instead of relying as heavily on standardized audience segments.

Steve and Devon also look at a newer question for marketers: What happens when the entity you need to influence is an AI agent?

Consumers are increasingly asking systems such as ChatGPT, Gemini, and Claude for product recommendations. That creates a new brand challenge around how a company appears inside AI-generated responses, which signals shape those recommendations, and how marketers might influence brand perception in an agentic environment.

The discussion closes with data literacy. Natural-language interfaces may make sophisticated analytics accessible to more marketers, but easier access to data does not remove the need for consistent measurement, shared definitions, sound governance, and human judgment.

In this episode:

• What agentic media buying means for advertisers
• Why WPP is helping develop standards for agentic buying
• WPP’s “human at the helm” philosophy
• Where AI automation ends and human approval begins
• Why WPP is beginning its agentic buying work with CTV
• How buyer and seller agents could interact
• How AI could create more tailored growth audiences
• The role of historical performance data
• Moving beyond standardized audience segments
• What “influencing algorithms” could mean for marketers
• How brands appear inside ChatGPT, Gemini, Claude, and other LLMs
• The emerging relationship between AI discovery and brand perception
• AI agents as a new layer between brands and consumers
• How natural-language interfaces change data analysis
• Why common definitions and standards still matter
• Why human judgment remains part of automated media buying

Media Monitor: Conversations at Cannes is a special summer series featuring conversations with leaders across media, advertising, data, and technology.

Also subscribe to the regular Media Monitor podcast, released Wednesdays, for analysis of the data and trends shaping the media market.

If you’d like access to the benchmark report or want to suggest a topic for the next part of the programmatic series, reach out to press@guideline.ai.

If you enjoyed this episode, be sure to follow or subscribe so you don’t miss future conversations on advertising, media strategy, and cultural marketing moments.

And if you’re listening on Apple Podcasts or Spotify, a quick rating or review helps more people discover the show.