There are weeks in programmatic advertising when the volume of concurrent announcements strains comprehension, and this has been one of them. In the 48 hours straddling June 16 and June 17, 2026, a car company tested a fundamental change to how bidding decisions are made inside an SSP, a ride-hailing platform extended its first-party data signals beyond its own apps for the first time, a measurement vendor launched episode-level brand safety controls for podcast inventory, a data platform rebuilt itself as an agentic CDP with that same measurement vendor as a launch partner, and a platform that rebuilt its advertising infrastructure in April added three new measurement features to the system it is still assembling. Cannes Lions begins next week. The industry arrives carrying more structural change than it has carried to the South of France in years.

Hyundai and Chalice test containerized bidding at the SSP

The most technically significant story of the week, and the one that received the least mainstream attention, was reported by AdExchanger on June 16. Hyundai has been testing a containerized ad tech integration between Chalice AI and the SSP OpenX, in which Chalice AI's custom bidding models run inside OpenX's cloud infrastructure rather than inside a DSP. The implications of that arrangement are substantial, though the industry has been slow to absorb them.

The standard programmatic supply chain has a fixed topology. The DSP sits on the buy side, holds the advertiser's audience data and performance goals, and sends bids into SSP auctions. The SSP mediates between publisher supply and DSP demand. The DSP wins or loses each auction and receives the feedback: impression served, conversion tracked, outcome measured or not. That feedback loop, flowing exclusively back to the DSP, is what has given demand-side platforms their structural advantage in programmatic for more than a decade. The SSP executes the transaction. The SSP learns nothing about whether it worked.

Containerized bidding changes the topology. By running Chalice AI's decision layer inside OpenX's infrastructure, Hyundai gains access to a far larger slice of total supply than any DSP would normally be rationed. DSPs receive a portion of each SSP's available inventory, governed by auction logic and latency constraints. When the bidding model runs inside the SSP's own container, it can observe and evaluate the full supply pool before deciding where to bid. For a large automotive advertiser with complex audience requirements, that broader inventory view produces a materially different set of opportunities than the rationed DSP view.

AdExchanger notes that Chalice AI has updated its positioning to describe itself as "the platform-independent AI media decisioning company," and OpenX has adopted the descriptor "The Intelligent SSP." These are not arbitrary rebranding choices. They signal a direction: as AI bidding models become more capable and cloud infrastructure becomes cheaper, the question of where AI models run inside the programmatic chain reopens. The DSP's historical advantage came from owning the feedback loop. Containerized bidding is the first structural mechanism with the potential to disrupt that advantage at scale.

This connects directly to a thread that PPC Land covered on June 11 when Magnite launched Orchestration, and to the broader argument AdExchanger's sell-side opinion contributor made on June 15: that the future of bidding will not be won by DSPs alone, specifically because the SSP's exclusion from the outcome feedback loop is structurally incoherent in a market moving toward outcome-based buying. The Hyundai-Chalice-OpenX integration is the live test of whether that argument holds.

PPC Land's coverage of Optable's agent readiness framework on June 16 named agentic discoverability as one of six publisher readiness pillars, and the ORTB extensions and agent-accessible inventory APIs required for that pillar are exactly the protocol surface that containerized bidding operates on. The bid logic runs at the SSP. The publisher whose supply reaches those models earliest gains a structural advantage. Publishers that cannot express their inventory in machine-readable deal structures with sufficient granularity will be invisible to the new decision layer.

Uber Offsite: first-party data leaves the platform

On June 16, Uber Advertising announced Offsite Ads, a product that extends Uber's managed first-party data and ad signals beyond the Uber and Uber Eats apps to Meta and Google Shopping for the first time. MediaPost confirmed the announcement the same day, describing it as extending Uber Advertising's managed first-party ad and data signals across Meta and Google Shopping through connected ad formats.

The product's architecture distinguishes it from standard data licensing arrangements. Uber is not simply selling audience segments to Meta or Google for those platforms to activate autonomously. The signals travel in a managed format, meaning Uber maintains oversight of how its first-party data is applied in off-platform environments. The integration uses Uber's purchase-derived behavioral signals, trip frequency, cuisine preferences, order patterns, and location context derived from actual transactions, rather than the interest-based or demographic approximations that third-party data providers typically offer.

This matters because Uber's first-party data is behavioral in a specific and commercially relevant sense. Somebody who orders from five different Thai restaurants via Uber Eats is not a modeled Thai food enthusiast. They are a verified Thai food buyer, with purchase timestamps, average order values, and frequency data attached. That difference in signal quality is what makes Offsite Ads commercially interesting. The signals Uber applies to Meta and Google Shopping campaigns carry the authentication that platform-native targeting data does not.

The Offsite product sits alongside two other announcements Uber made simultaneously. Offers on Uber places commercial offers directly inside the Uber ride experience, visible to passengers during trip waiting and transit phases. New Uber Eats premium formats include brand takeovers and sponsored placements that give restaurant brands higher-visibility inventory. Taken together, the three products represent Uber Advertising's attempt to build a full funnel: premium visibility inside owned apps at the top, purchase-signal-enhanced reach across Meta and Google in the middle and at the bottom.

The retail media context here is important. PPC Land has tracked the growth of retail media attribution problems extensively, citing Incremental's meta-analysis of 150,000 campaigns and $350 million in ad spend showing that siloed retail media attribution misses between 36% and 53% of true campaign ROI. Uber Offsite introduces a different model: rather than keeping retail media signals inside a walled garden and forcing cross-media attribution externally, Uber is extending its signals into third-party measurement environments with the managed data architecture intact. Whether the closed-loop measurement capability survives the move into Meta and Google properties is a question that will be tested in practice.

What Uber Offsite also signals is the beginning of a wider pattern. Commerce platforms with verified purchase data are recognizing that the value of that data extends beyond their own inventory. Amazon has done this through Amazon DSP and Amazon Marketing Cloud. Walmart did it through the DV360 integration announced on June 11, which PPC Land covered at the time, activating Walmart shopper audiences on YouTube with closed-loop measurement. Uber Offsite is the ride-and-delivery equivalent of the same strategic move.

IAS extends into audio and into the CDP layer

Two announcements from Integral Ad Science on June 16 and June 17 trace a consistent strategic expansion. Individually each is significant. Together they suggest IAS is deliberately positioning itself at the intersection of two infrastructure layers that the industry has long treated as separate problems.

IAS launched episode-level pre-bid optimization for Spotify podcasts on The Trade Desk on June 17, through a product called IAS Context Control for Spotify podcasts. The product classifies individual podcast episodes before a bid is placed, using 33 avoidance segments across 11 categories at three risk levels: high, medium, and low. The classification runs at the episode level, not the show or app level, which closes a gap that has made podcast brand safety a less precise instrument than display or video brand safety despite significant growth in audio ad revenue.

U.S. podcast advertising reached a record $2.9 billion in the most recently measured period, a rise of more than 17%. That growth has been happening alongside a persistent measurement gap: audio contextual classification has lagged behind the tools available for display and video, and the granularity mismatch has meant that programmatic audio brand safety has operated on less precise inputs than every other major channel. AdExchanger reported on June 12 that digital audio represents roughly 30% of media consumption for the average American adult but attracts only 3% of annual U.S. ad spend, a ratio that industry participants attribute in part to the absence of mature programmatic workflows and measurement. IAS's episode-level controls address one of the most concrete components of that gap.

The product is available through The Trade Desk starting in July 2026, with other DSP partners to follow later in the year. Buyers configure controls inside the existing Trade Desk interface, applying the same brand suitability framework they already use across display and video.

The Databricks announcement, published June 16, is a different kind of infrastructure story. Databricks launched CustomerLake, an agentic CDP embedded natively in the Databricks environment, with IAS as a launch partner. The IAS role here is not brand safety in the buying workflow. It is signal enrichment: over 300 billion daily IAS media signals, contextual classifications, brand suitability scores, and viewability data, connect directly to the first-party audience profiles that brands store inside CustomerLake.

CustomerLake is architecturally distinct from both traditional CDPs and composable CDPs. Traditional CDPs require data extraction and loading into a separate system. Composable CDPs assemble modular tools on top of an existing data warehouse. CustomerLake is embedded inside Databricks natively, operating on Unity Catalog governance and Lakehouse storage without requiring any data movement. The IAS signal layer sits within a third-party data marketplace that enriches first-party profiles in place, meaning the enrichment is governed by the same access controls and lineage tracking as the underlying customer data.

The technical components that support CustomerLake include Lakeflow for real-time and batch ingestion from marketing tools and advertising platforms, Unity Catalog for unified governance and federated access to external systems including Snowflake and BigQuery, Genie for natural language querying of governed data, a Real-Time Profile API for low-latency personalization at the moment of user interaction, and Agentic Identity Resolution for AI-driven cross-source record matching that improves over time.

What IAS gains from the Databricks partnership is presence inside the data layer where advertising decisions are increasingly being made before any DSP or trading desk is involved. What Databricks gains is a credible measurement and contextual signal partner for an agentic CDP that positions itself as the environment where brands can build AI-driven audience logic without extracting data to a separate system. The mutual interest is legible. So is the market position that emerges if both scale successfully.

Fox buys Roku: what a $22 billion deal means for CTV advertising

The acquisition that dominated coverage earlier in the week continued to generate analysis. Fox Corporation agreed on June 15 to acquire Roku for $22 billion, paying $160 per share at a 34% premium. PPC Land's coverage and MediaPost's Television News Daily both confirmed the terms. The deal joins Fox's live sports rights and news programming, Tubi's FAST library, and The Roku Channel, and the Roku operating system, which runs on more than 100 million active accounts, into a single CTV advertising and streaming platform.

The CTV advertising implications are structural. Roku's OS is the most widely deployed streaming platform in the United States, with inventory touchpoints across the home screen, content discovery, and ad-supported streaming. Fox brings Tubi, which carries 1,700 FAST channel titles, and live sports rights including NFL, MLB, and soccer. The combination creates an entity that can offer advertisers reach at the OS level, content sponsorship at the live event level, and FAST channel adjacency in a single buy.

MediaPost cited a Guggenheim Securities estimate that Roku's redesigned home screen, which was approximately 20% rolled out at the time of the deal, represents one of the most significant monetization opportunities in Roku's history. That home screen inventory became programmatically accessible to The Trade Desk and Google DV360 as of Q3 2026, as PPC Land reported on June 10 in the context of Samsung's parallel move into programmatic home screen ads. The timing is notable: Roku opens its home screen to programmatic buyers precisely as Fox acquires the platform, creating a scenario in which the new parent controls both the premium content environment and the programmatic access layer for the most-watched home screen in American streaming.

The advertising consequences extend into the Tubi FAST channel ecosystem. VAB published data in June 2026 showing that 89% of U.S. streamers use ad-supported services, with interactive CTV ads producing 138% higher brand recall than standard formats. PPC Land's coverage of that VAB data placed Tubi's 1,700-title FAST channel count in the context of a broader market shift toward ad-supported streaming. The Fox acquisition brings that FAST inventory under the same ownership as Roku's OS, creating cross-surface reach that no previous CTV entity has held.

For the broader CTV advertising market, the deal reshapes competitive dynamics in ways that will take months to clarify. Competing platforms, including Peacock, Hulu, and Paramount+, face an entity with distribution scale at the OS level that their content libraries cannot replicate. Ad tech intermediaries that have depended on fragmented CTV supply will find that a meaningful proportion of that supply is now consolidated under a single seller with the incentive to maximize direct deal flow.

Publicis coins a phrase, and the industry hears itself

Ahead of Cannes Lions, Publicis Groupe published a mockumentary-style film on June 16 satirizing what CEO Arthur Sadoun described to Adweek as "AI pitch-maxxing": the phenomenon of agencies aggressively overselling their AI capabilities in pitches to win business. The Adweek coverage of June 16 described Sadoun's argument that overhyped AI promises and cut-price pitches are fueling industry job cuts, with the film serving as a pre-Cannes positioning statement that clients want proof of business impact rather than promises.

The timing is deliberate. Cannes Lions begins June 21, and the festival's award categories have been increasingly accommodating AI-enabled creative work. The World Federation of Advertisers published research on June 15, cited by MediaPost, indicating slow progress among advertisers integrating AI into award-worthy creative executions despite widespread enthusiasm for AI as a topic. The gap between AI as a marketing conversation and AI as a verifiable creative outcome is precisely the gap Publicis is naming.

Sadoun's use of "pitch-maxxing," a word built on the internet vernacular of maximizing something to its extreme, is a calculated choice. It frames a widespread industry behavior as excessive and ultimately self-defeating, while positioning Publicis as the agency that builds demonstrable AI capability rather than marketing it. The framing works in part because it is accurate. Agencies pitching AI capabilities they have not fully built, claiming speed improvements they cannot sustain, and winning business on promises rather than evidence, are a documented pattern in the current agency landscape.

The Publicis-Trade Desk settlement provides additional context. Digiday reported on June 12 that the two companies resolved their months-long dispute through a joint statement, without disclosing the terms. The dispute began in March when Publicis pulled The Trade Desk from its recommended DSP list following an audit that found alleged fee stacking irregularities, and Trade Desk's stock fell roughly 13% at the height of the conflict. The resolution allows Publicis to arrive at Cannes without the largest DSP dispute in recent agency history still unresolved, positioning the holding company as having addressed the fee transparency issues it raised while settling on terms that neither side has disclosed.

Together, the pitch-maxxing satire and the Trade Desk settlement allow Publicis to frame its Cannes narrative around accountability, both in AI capability claims and in programmatic fee structures, without having to defend specific positions on either. That is a sophisticated approach to a festival where narrative positioning often matters as much as product announcements.

Reddit at 21: the bot economy disclosed

Steve Huffman published a post to Reddit on June 16 marking the platform's approaching 21st birthday, and the operational numbers he disclosed deserve sustained attention from the advertising community. Reddit's systems now block up to 23 million spam views per day through proactive detection models, and the platform revokes nearly 2 million inauthentic votes daily. These figures, offered under Huffman's longstanding username u/spez, are the most specific operational disclosures the platform has made about its integrity infrastructure.

The 23 million figure refers to content intercepted before it reached real users. The 2 million figure refers to votes cast by inauthentic accounts and retroactively stripped from public tallies. Both numbers imply infrastructure of significant scale and complexity. Blocking 23 million spam views per day requires a pre-serve detection pipeline classifying content at millisecond latency across millions of concurrent submissions. Revoking 2 million votes daily requires continuous processing of vote events, cross-referencing account signals, and retroactive adjustment of public vote counts without creating visible artifacts in the community interface.

Huffman placed these numbers in a deliberate frame. The post argues that Reddit's community-governed, pseudonymous environment represents authentic human opinion at a time when, as he wrote, the rest of the internet is filling up with synthetic content. That argument has commercial weight for advertisers, because what they are purchasing when they place budgets on Reddit is proximity to organic community discussion. The claim that this discussion is being actively defended against synthetic intrusion at this scale is a verification of the value proposition.

The numbers also connect to a broader industry measurement crisis. Lunio's Q1 2026 analysis of 64 million clicks, covered by PPC Land on June 13, found LinkedIn's invalid traffic rate at 17.62%, Bing at 12%, and Google Display up 132% year over year. HUMAN Security's May 2026 data showed agentic traffic fell 4.3% month over month while blocking rates rose to nearly 9%. Reddit's disclosure places its own numbers in a market where most platforms disclose nothing comparable, which is itself a form of competitive positioning.

The legal history reinforces the context. Reddit restricted its robots.txt file in 2024, granted Google exclusive automated crawl access through a licensing deal, and filed suit against Anthropic on June 4, 2025, alleging unauthorized content scraping for AI training. Huffman's 21st anniversary post is the celebration version of the same argument made in those legal and technical actions: Reddit's authentic human content has value, that value is being defended at industrial scale, and the cost of that defense is not being externalized onto advertisers in the form of undetected invalid traffic.

X rebuilds measurement, feature by feature

X announced three new features for its rebuilt Ads Manager on June 16: a Google Tag Manager integration for no-code X Pixel and Conversion API setup, a unified developer environment consolidating CAPI implementation tools, and a real-time conversion diagnostics dashboard. All three build on the platform's comprehensive advertising infrastructure rebuild that began in April 2026.

The significance of separating these into three distinct announcements, rather than a single bundled release, is underappreciated. Bundled announcements obscure which component solves which problem. By naming each feature separately and describing its specific function, X is demonstrating a more methodical engineering approach than the platform's advertising operations have historically shown.

The GTM integration targets advertisers without engineering resources. Google Tag Manager is the most widely deployed tag management system in digital advertising, and integrating X Pixel and CAPI setup into its guided workflow means that any advertiser already using GTM for other tracking purposes can implement X's server-side measurement without writing code. Both Pixel-only and dual Pixel-plus-CAPI configurations are supported through the integration.

The unified developer experience consolidates CAPI implementation into a single Ads Manager location. Before this change, teams managing CAPI configurations at scale across multiple accounts had to navigate between multiple documentation sources and separate tool interfaces. The consolidation reduces implementation time and decreases the probability of configuration errors that degrade signal quality.

The real-time diagnostics dashboard is operationally the most valuable of the three for active campaigns. Conversion signal health, including Pixel firing status, CAPI delivery confirmation, and signal gap identification, is visible in the Ads Manager interface continuously rather than requiring post-campaign analysis to surface. A campaign running with broken CAPI configuration currently silently degrades attribution for its entire flight. The diagnostics dashboard makes that degradation visible during flight.

For a platform attempting to recover advertiser confidence after years of structural instability, the sequencing matters. April rebuilt the platform. June adds measurement infrastructure to the rebuilt foundation. The next question is whether the rebuilt platform and the measurement improvements together produce demonstrably better attribution outcomes for advertisers, and whether those outcomes show up in the campaigns currently running.

SEO: LLMS.txt carries no ranking weight

In a more technical corner of the industry, Google clarified on June 16 what many SEO practitioners had suspected: LLMS.txt files, a proposed standard for communicating with large language model crawlers, carry no benefit and no penalty for Google Search rankings. Search Engine Roundtable's recap of June 16 covers this alongside a parallel clarification from Google that HTML remains the standard for SEO and that Markdown files used in AI-oriented documentation formats provide no SEO advantage.

The practical significance for digital marketers is that LLMS.txt adoption, while potentially useful for controlling LLM training data access, is not an SEO instrument. Agencies and publishers that invested in LLMS.txt deployment as a ranking signal, or that have been counseling clients to do so, need to revise that guidance. The Search Engine Roundtable recap also notes that Google has confirmed there is no practical SEO difference between using a subfolder structure and other URL configurations for US-specific site sections, which closes another long-standing uncertainty in international SEO implementation.

The LLMS.txt clarification connects to a broader set of questions about how publishers manage AI crawler access. PPC Land covered the New York State Assembly's passage of A11292 on June 5, which would require AI crawlers to disclose identity and purpose to news publishers or face $15,000-per-day penalties if signed into law. UK publishers have separately deployed Search-Only Contracts to bill AI scrapers 500 pounds per scraped article through county courts, a mechanism PPC Land covered on June 15. Google's clarification that LLMS.txt is not an SEO factor is distinct from the question of whether it is an effective crawler access control, which remains unresolved.

Microsoft Advertising adds seniority targeting and Product Explorer

Two Microsoft Advertising product additions rounded out the week on the search side. Microsoft Advertising launched Product Explorer for US advertisers managing catalogs under 100,000 SKUs, giving advertisers a unified searchable view of product status, serving eligibility, and performance metrics inside the Ads Manager interface. Search Engine Roundtable's recap from June 16 confirmed the feature's availability across US accounts.

The Product Explorer launch addresses a persistent pain point for mid-market retailers running Shopping campaigns at scale. Managing catalogs of tens of thousands of products has historically required switching between feed management tools, product data systems, and campaign interfaces to understand why specific products are not serving, what eligibility issues are preventing impressions, and how product-level performance is tracking against campaign goals. Product Explorer consolidates that diagnostic view into a single searchable interface inside the platform where the campaigns run, reducing the number of systems a practitioner needs to navigate to understand catalog health.

The 100,000 SKU ceiling is notable. It positions Product Explorer explicitly for mid-market retailers rather than enterprise accounts with catalog sizes that exceed that threshold. That targeting of the mid-market is consistent with a broader Microsoft Advertising positioning strategy that differentiates from Google Shopping by offering tools that serve advertisers who lack the dedicated feed operations teams that large-scale Google Shopping management typically requires.

Separately, Microsoft Advertising added 10 LinkedIn job seniority levels as a targeting dimension for search and audience campaigns across 29 markets including the US and EMEA. The seniority levels range from unpaid through entry, junior, senior, manager, director, vice president, C-suite, partner, and owner. This LinkedIn data integration extends targeting precision for B2B advertisers specifically, who have historically been limited to industry and job function targeting at the LinkedIn data layer available through Microsoft Advertising.

The 29-market rollout is unusually broad for a first deployment. Most Microsoft Advertising LinkedIn targeting expansions have launched in limited markets before expanding globally. Deploying seniority targeting across the US and the major EMEA markets simultaneously signals confidence in both the data coverage and the advertiser demand. For B2B campaigns targeting senior decision-makers, the ability to distinguish between, say, director-level and C-suite audiences within the same LinkedIn data layer changes the economics of search advertising on Microsoft in ways that matter to enterprise software and professional services advertisers in particular.

Both additions come in a week when LinkedIn itself made two separate announcements that PPC Land covered earlier in the cycle: a new Creator Marketplace and BrandWorks platform for B2B brands, and a new analytics metric splitting post impressions into in-network and out-of-network reach. The seniority targeting addition is the B2B channel's direct response to advertiser demand for more precise professional audience control, and its 29-market rollout signals that Microsoft is scaling this capability globally rather than testing it in a limited geography first.

The WFA's AI creative assessment, and what it reveals about dual-track adoption

The World Federation of Advertisers published research on June 15 in partnership with Cannes Lions indicating, as MediaPost reported, "slow progress" among advertisers integrating AI into award-worthy creative executions. The finding arrives immediately before a festival where AI as a creative tool has been one of the dominant pre-Cannes conversations for two consecutive years.

The gap between AI as a marketing topic and AI as a verifiable creative contribution is the same gap Publicis named with its pitch-maxxing satire. The WFA research appears to quantify that gap from the advertiser side: brands are discussing AI, attending AI panels, signing AI platform contracts, and building internal AI capability, while the proportion of those organizations producing creative work that demonstrates AI integration to award-entry standard remains limited.

The implication for media and advertising practitioners is that 2026 may be the year when AI separates into two distinct categories inside the industry: the category of AI applied to infrastructure, measurement, and data operations, where deployment is extensive and accelerating, and the category of AI applied to creative production at a quality standard that distinguishes the work, where deployment is slower and more uneven. The programmatic infrastructure news of the past 48 hours sits firmly in the first category. The award category performance the WFA is measuring sits in the second.

That distinction matters for how agencies position themselves heading into the back half of 2026. An agency can demonstrate AI infrastructure competence through verifiable deployments: CAPI implementation rates, agentic campaign automation, CDP integration, and measurement accuracy. These are auditable. The claims Publicis is satirizing with pitch-maxxing are often unauditable, which is why they can be made in a pitch without verification. The WFA's "slow progress" finding is the creative equivalent of Publicis's pitch-maxxing concern: advertising that claims AI integration but cannot demonstrate it at an award-entry standard is making a claim that the work itself does not yet support.

For brands and media buyers evaluating agency AI claims ahead of Cannes, the WFA research serves as a calibration instrument. The question is not whether an agency uses AI but which category of AI use the claim covers: auditable infrastructure deployment or creative quality at scale. The industry is still early in developing the frameworks to distinguish between them.

Also noted

  • June 16, 2026: The UK government announced a ban on social media for under-16s, covering Snapchat, TikTok, Instagram, YouTube, Facebook, X, and select gaming and livestreaming platforms, with Spring 2027 regulatory implementation expected. MediaPost confirmed the announcement. The regulations introduce new compliance obligations for platforms serving the UK market and remove a segment of the current social audience from targeted advertising.
  • June 16, 2026: Databricks CustomerLake launched with IAS as a partner, linking over 300 billion daily IAS media signals to first-party audience profiles inside a natively embedded agentic CDP built on Unity Catalog and Lakehouse storage. The product positions Databricks as the data infrastructure layer where audience building, signal enrichment, and campaign activation converge without data replication.
  • June 16, 2026: The Oxford Reuters Institute for the Study of Journalism published its 2026 Digital News Report, finding that social media outperforms publisher websites as a news source in 30 of 48 markets surveyed and AI chatbot news use climbed from 7% to 10% year over year. The findings have direct implications for publisher advertising inventory and the first-party audience relationships that advertising models depend on.
  • June 16, 2026: Digiday reported that Publicis and The Trade Desk resolved their dispute through a joint statement issued June 12, ending a months-long conflict that began when Publicis pulled TTD from its recommended DSP list following an audit alleging fee stacking irregularities. The terms of resolution were not disclosed by either party.
  • June 16, 2026: Adweek reported that WARC's new global ad forecast, revised upward on June 15, lifts the worldwide ad growth consensus for 2026, with Joe Mandese at MediaPost citing a 1.2-point rise to plus 8.9% based on the latest estimates from WPP and Madison and Wall.