Q2 Digital Marketing Report: Search Agents, The Depth Score, and Marketing in the Age of Uncertainty

Let's Get Digital walks you through the most important developments from the past three months. Q2 raised the stakes again: Google rebuilt its search bar for the first time in 25 years, ChatGPT opened its ad platform to anyone with a credit card, and "agentic AI" graduated from conference buzzword to operational reality. Oh, and 90% of ad buyers are still worried about tariffs.

Let's get into it.

🤖 AEO (Answer Engine Optimization)

Traditional ranking and AI visibility are now two separate games, and Q2 made it impossible to treat them the same way.

• Google Rebuilt Search for the First Time in 25 Years. At Google I/O in May, Google introduced its biggest search overhaul since 1998: a search bar that now accepts text, images, files, videos, and open Chrome tabs as input, plus Search Agents that work autonomously in the background, surfacing answers around the clock. The result is showing up in the numbers. AI Mode has crossed one billion monthly users, with queries more than doubling every quarter. For content teams, the question is no longer how to rank. It's how to get cited.
  
  
• The May Core Update: Rankings and Traffic Are Now Two Different Things. With AI Overviews absorbing clicks above organic results, position-one CTR on AI-featured queries dropped from roughly 27% to as low as 11%. This means that even if you're winning on rankings, you may be losing on traffic. The update rewarded original research and hammered thin AI-generated pages. Google's simultaneous global launch of Preferred Sources gives brands a free lever to influence which content gets prioritized in AI responses, provided their audience is willing to leverage the tool.
  
  
• The Citation Gap Has Widened Dramatically. Top-10 rankers accounted for 76% of AI Overview citations in mid-2025, a figure that fell to roughly 38% by early 2026, which demonstrates that ranking and being cited are increasingly disconnected. What drives citation isn't position; it's structural clarity, consistency of information across independent sources, and claims that AI systems can verify and confidently surface.
  
  
• ChatGPT Traffic Converts Better Than Almost Every Other Channel. Similarweb's downstream impact study found that ChatGPT referral traffic converts at 7.1%, second only to paid search, with users spending 15 minutes on site versus 8 minutes from Google. And since May 7, when ChatGPT moved brand links from footnote citations to callouts placed directly inside responses, referral traffic jumped 157.7% week-over-week with 60%+ of clicks landing on brand homepages. The reframe here is important: ChatGPT sends fewer clicks than Google, but the ones it sends arrive already interested.

Top Takeaways for Marketers:

• Track AI Overview citation share alongside traditional rankings; the two no longer move together, and optimizing for one without the other is an incomplete strategy.
• Activate Preferred Sources for your site before competitors discover the same free lever.
• Reframe AEO's value internally around conversion quality, not click volume. AI-referred visitors convert better and stay longer, which is a stronger argument to leadership than visibility alone.

💬 Social Media

LinkedIn's algorithm has made its values explicit: depth over volume and earned engagement over easy engagement, and Q2 finally put hard numbers behind it.

• The "Depth Score" Is Now LinkedIn's Primary Distribution Signal. LinkedIn's 2026 algorithm weights comment threads, full-post reads, saves, and inbox shares over surface-level reactions, which in practice means a post earning 20 substantive replies from the right professionals now outperforms one with 200 emoji reactions: a structural shift that rewards community-building over reach-chasing.
  
  
• Native Documents Lead the Platform, While Video Has Hit a Wall. SocialInsider's 2026 LinkedIn Benchmarks Report (1.3M posts, 16K+ pages) found carousels and PDFs leading all formats at 7% engagement while video views fell 36% year-over-year. That's not because video is dead as a format; the polished corporate video playbook most brands are still running simply isn't connecting, while repurposed live session clips and lighthearted content significantly outperform.
  
  
• LinkedIn Is the Only B2B Ad Platform at Positive ROAS. Dreamdata found LinkedIn delivering 121% ROAS versus Google Search at 67% and Meta at 51%, alongside a B2B buyer journey that has extended to 272 days. Layer in Similarweb's finding that 35% of buyers now say AI is most useful at the discovery stage versus 13.6% for search, and the picture is clear: AI owns top-of-funnel, LinkedIn owns the middle, and your brand needs to be active in both.
  
  
• The Algorithm Is Now Flagging AI-Generated Content. LinkedIn's classifiers are actively deprioritizing posts showing signs of AI generation, particularly generic structure, hedging language, and flattened voice. If your content strategy relies on scheduling AI-generated posts at scale, you're not just risking lower engagement; the algorithm is now working directly against you.

Top Takeaways for Marketers:

• Shift budget and effort toward native documents. Carousels and PDFs remain the highest-performing format on the platform and are still underused by most B2B brands.
• Build a structured commenting framework to facilitate further discussion on your posts that gain organic interactions, since Depth Score rewards genuine conversation over passive reach.
• Treat LinkedIn and AEO as complementary, not competing, investments. AI is winning discovery; LinkedIn is winning consideration.
• With AEO and native formats on the rise, review and adjust your KPI set to appropriately track awareness program's effectiveness.

💸 Go To Market

Tariff uncertainty is still real, but the brands protecting budgets are the ones who've built the measurement to justify them.

• Fewer Buyers Are Actually Cutting Despite Tariff Fears. Per the IAB's 2026 ad spend analysis, the share of buyers who reduced spend in response to tariff concerns fell from 45% in 2025 to 30% in 2026, a meaningful shift that reflects something more than market confidence. Marketers who have built credible measurement frameworks are protecting budgets more effectively, and the mandate has quietly moved from "cut marketing" to "prove marketing."
  
  
• MMM (Mixed Media Modeling) Adoption Is Up, But Most Teams Are Still Underperforming on Measurement. Nearly 47% of US marketers plan to increase MMM investment this year, which makes sense given that 78% believe at least 10% of their spend is wasted and 75% say their current measurement is underperforming. But having MMM isn't enough; the new gold standard is Causal MMM, traditional modeling validated against incrementality experiments, so budget decisions rest on experimental evidence rather than historical correlation alone.
  
  
• Both ChatGPT and Google Just Put Ads Inside AI Answers. ChatGPT advertising hit $100M in annualized revenue by May after moving from a $200K minimum beta to a fully self-serve model with no minimum spend. Google followed at Marketing Live with Conversational Discovery Ads inside AI Mode, where users encounter sponsored results in Gemini's responses. Together, they're putting U.S. AI-driven search advertising on a trajectory from $1.1B in 2025 to a projected $26B by 2029.
  
  
• In-Person Events Are Getting Real Budget Again. EndeavorB2B found 49% of organizations increasing in-person event budgets, which reflects a data-backed response to buyer fatigue with algorithm-mediated content. Trade shows and small-group roundtables are where B2B deals move from "interesting" to "serious," and unscripted human interaction converts at rates no programmatic channel currently matches.

Top Takeaways for Marketers:

• If you're running MMM, validate it against incrementality experiments rather than treating the model as the final word.
• Test ChatGPT advertising now. If your buyers research there, competitors' ads will be too, and the platform rewards early movers.
• Audit your product messaging for specificity. The new AI ad formats require answer-first creative, not generic campaign briefs.
• Reintroduce events and community into your GTM budget; long-cycle B2B buyers convert at higher rates with an in-person touchpoint somewhere in the journey.

🚧 MarOps

The conversation has shifted from "AI adoption" to "AI orchestration," and the hard parts now are data infrastructure, governance, and what happens when your agents start interacting with your customers' agents.

• "AgentOps" Is Emerging as a New Organizational Function. Per McKinsey, 62% of organizations are still experimenting with agentic AI and only 23% are scaling. The enterprises pulling ahead aren't deploying agents tool by tool; they're building internal "Agent Factories," dedicated environments to design, test, and govern multi-agent workflows before those workflows ever touch customers or live systems.
  
  
• 90.3% of Marketing Organizations Are Now Using AI Agents. Scott Brinker's Martech for 2026 research found content production and audience discovery agents as the most widely deployed types, reflecting a broader shift from generative AI that creates content to agentic AI that orchestrates entire workstreams. Teams still relying on manual processes to connect tools and datasets aren't scaling; they're accumulating technical debt.
  
  
• Your Buyers' AI Agents Are Now Your Audience Too. McKinsey estimates 20–50% of traffic from traditional search is at risk as buyers shift discovery to AI assistants operating on their behalf. That means if your product information is inconsistent across your site, review platforms, and third-party publications, a buyer's agent will form an inaccurate impression of your brand.
  
  
• The Stack Is Consolidating Around Agent-Ready Platforms. Salesforce Agentforce 360, HubSpot's Breeze AI Agent APIs, and Intercom's Fin API Platform are pulling ahead by building the interoperability layer that makes it possible for AI agents to operate fluidly within their systems. Deloitte, citing Gartner, projects 35% of point-product SaaS tools will be replaced by or absorbed into AI agent ecosystems by 2030, making this a vendor selection conversation, not just a stack efficiency one.
  
  

Top Takeaways for Marketers:

• As we recommended in Q1, the time is now to map one governed agentic workflow end-to-end before Q3 planning, not to scale immediately but to surface integration gaps first.
• Audit brand information consistency across your site, G2, Reddit, and industry publications. This is largely invisible until it's wrong, and it's now shaping how AI represents you to buyers.
• Treat agent readiness as a required criterion when evaluating new martech, not a nice-to-have.

🛠️ Tool Time

New tools generating attention as we head into Q3:

• ChatGPT Ads Manager: OpenAI's self-serve advertising platform is now open to any business with no minimum spend, with CPC and CPM bidding and contextual targeting based on conversation history. Worth testing if your buyer starts their evaluation in AI chat rather than a search bar.
  
  
• Semrush One: The latest Semrush release adds dedicated AI visibility tracking across ChatGPT, Gemini, and Google AI Overviews, filling the gap for teams not yet tracking "Share of Model" alongside traditional share of search.
  
  
• Salesforce Agentforce Sales for ChatGPT: Now in open beta, this integration connects Agentforce CRM data directly to ChatGPT so sellers can query live Salesforce data through natural language, all governed by the Agentforce Trust Layer.
  
  
• Profound / Brandaxis: A new measurement category purpose-built to track brand visibility inside AI-generated responses, scanning outputs across major LLMs to monitor how often and accurately your brand appears. It's the reporting layer for AI presence that Search Console doesn't yet offer.

DaaS a wrap 👏

The AI transformation of marketing is the operating environment you're already in. The brands winning right now are the ones who've stopped treating AI as a feature and started treating it as infrastructure.

At The Ricciardi Group, we help B2B brands build the strategies and systems to stay ahead, from AEO audits to agentic workflow design to LinkedIn programs that actually move pipeline.