I’m thrilled to share that Profound Agents now offer direct integration with Contentful CMS. This integration brings native Contentful support right to your AEO automation stack, enhancing your strategy and capabilities.
With this development, I’m sure you’ll find managing content and automations far more streamlined and efficient. Having the power of Contentful within reach means we can align more closely with modern content management needs.
I’m eager to see how this integration will open up new avenues for optimizing our automated processes and elevating overall performance.
Do you want to take your Answer Engine Optimization (AEO) to the next level? Content siloing might just be the strategy you need. It’s a tactic that has transformed how I approach structuring topics to enhance authority and improve crawlability. Let’s delve into what content siloing is and how you can successfully implement it to boost AI citations.
Think of content siloing as creating a tightly knit topic network within your website, where each piece of content supports and strengthens the others. By organizing related content into isolated ‘silos,’ you not only streamline user navigation but also make it easier for search engines to index and understand the relevance of your content. This improved visibility can lead to better ranking in AI-powered search results.
Implementing content siloing involves a strategic approach to linking content. Begin by identifying your core topics and create subtopics that branch off these main areas. Each article within a silo should link to related content, reinforcing the overall theme and strengthening your site’s authority on the subject matter. This method ensures that your website becomes a trusted source of information in the eyes of both users and search algorithms.
I’ve noticed that when I leave Performance Max campaigns running without proper setup, they tend to focus on getting easy conversions, often leading to a rise in low-quality leads. While this can quickly rack up conversion numbers, the quality isn’t always great. Google tends to prioritize cheaper conversions, benefiting their revenue, but not necessarily my pipeline.
Many times, brands are surprised by these results after following Google’s sales advice too closely. Although low CPA metrics look tempting, they can often mask the fact that these new leads aren’t contributing to the real growth of my business.
That said, with the right adjustments, Performance Max can be optimized to generate high-quality leads. Building these ‘guardrails’ effectively is key to success, and I’m here to share what I’ve learned.
This guide will walk you through which strategies work for improving lead quality, tactics that don’t deliver desired results, and the notable differences between using Performance Max in Google versus Bing.
How to Improve Lead Quality in PMax Campaigns
Here are the actionable steps I’ve found to consistently impact lead quality:
Focus on conversion goals that align with higher quality targets. Try targeting metrics like closed-won leads or sales-qualified leads, which provide more valuable insights than just form fills. For this to work, ensure my CRM is accurately tracking offline conversions.
Utilize high-value audience signals. Target more specific behaviors, such as users who have ‘booked a meeting’ rather than just anyone who converts.
Concentrate on the correct audiences. Exclude irrelevant segments, and use Customer Match to help Google’s algorithms find users similar to my best customers.
Optimize campaign settings smartly. Examples include using brand exclusions, targeting high-performing geos, strategic scheduling, analyzing search themes, and employing site link extensions to channel traffic efficiently.
Refine forms for better lead filtering. Integrate reCAPTCHA to deter bots, implement field validation to block disposable domains, and include quality-check questions such as how they heard about my company or if they have budget allocations.
Some common optimizations don’t significantly enhance lead quality:
Switching bid strategies offers minimal impact.
Adding more assets or budget doesn’t inherently improve lead caliber.
I’ve learned to be cautious when seeking help from Google support, as results can vary.
Important Differences Between Google and Bing PMax Campaigns
Google and Bing both offer Performance Max campaigns, but they differ significantly. Google’s expansive network includes search, display, YouTube, discovery campaigns, and Gmail. If not carefully managed, this can lead to spam-driven conversions, particularly from display and YouTube.
Bing’s campaigns, on the other hand, focus on Bing search and their audience network, which covers display, Outlook, and MSN. I haven’t observed significant performance differences, but staying updated with platform changes is crucial.
Performance Max Isn’t Broken, but It Needs Control
Entering PMax for lead generation with caution is a wise approach. Although promising for ecommerce revenue, lead quality demands stringent campaign guidelines. For instance, preventing misaligned conversions for a luxury retailer requires effective PMax guardrails.
Considering Google’s shift towards automation and AI, it’s essential to continuously test and adapt. Recent updates like channel-level reporting and exclusion options offer new tools to shape my campaigns.
Achieving quality leads and a healthy ROI is possible by navigating the algorithm strategically. If past PMax efforts were paused due to poor returns, revisiting and applying lessons learned could significantly improve future outcomes.
Every day, millions turn to ChatGPT for answers, but have you noticed your brand isn’t included in those results? I’ve been there, wondering why my brand isn’t gaining visibility and how to change that. If you’re like me and want to understand what’s happening, I’ve gathered the seven main reasons why ChatGPT might be ignoring your brand.
Understanding these reasons is the first step to making a change. You’ll learn specific steps to enhance your visibility in AI searches, and I can tell you from experience, it’s worth the effort.
Perhaps you’re wondering: what can I do to ensure my brand stands out? Don’t worry, I’m here to guide you through actionable strategies for gaining prominence in AI search results.
Let me guess: I just spent three months meticulously crafting an optimized product taxonomy, complete with schema markup, internal linking, and standout metadata.
Then, out of nowhere, the product team decided to launch a site redesign without looping me in. Now half of my URLs are broken, the new templates have stripped away my structured data, and my boss is wondering why our organic traffic plummeted by 40%.
Sound familiar?
Here’s the thing: this isn’t an SEO failure, but a governance failure. It’s been costing us countless nights and weekends trying to fix problems that never should have occurred.
This article sheds light on why weak governance keeps breaking SEO, how AI advancements have raised the stakes, and how a visibility governance maturity model can help SEO teams transition from firefighting to prevention.
Governance isn’t bureaucracy – it’s your insurance policy
I know what you’re thinking. “Great, another framework that means more meetings and approval forms.” But hear me out.
The Visibility Governance Maturity Model (VGMM) isn’t about creating red tape. It’s about establishing clear ownership, documented processes, and decision rights that prevent your work from being accidentally destroyed by teams who don’t understand SEO.
Think of it this way: VGMM is the difference between being the person who gets blamed when organic traffic tanks versus being the person who can point to documentation showing exactly where the process broke down – and who approved skipping the SEO review.
This maturity model:
Protects your work from being undone by releases you weren’t consulted on.
Documents your standards so you’re not explaining canonical tags for the 47th time.
Establishes clear ownership so you’re not expected to fix everything across six different teams.
Gets you a seat at the table when decisions affecting SEO are being made.
Makes your expertise visible to leadership in ways they understand.
The real problem: AI just made everything harder
Remember when SEO was mostly about your website and Google? Those were simpler times.
Now I’m trying to optimize for:
AI Overviews that rewrite your content.
ChatGPT citations that may or may not link back.
Perplexity summaries that pull from competitors.
Voice assistants that only cite one source.
Knowledge panels that conflict with your site.
And I’m still dealing with:
Content teams who write AI-generated fluff.
Developers who don’t understand crawl budget.
Product managers who launch features that break structured data.
Marketing directors who want “just one small change” that tanks rankings.
Without governance, I’m the only person who understands how all these pieces fit together.
When something breaks, everyone expects me to fix it – usually yesterday. When traffic is up, it’s because marketing ran a great campaign. When it’s down, it’s my fault.
I become the hero the organization depends on, which sounds great until I realize I can never take a real vacation, and I’m working 60-hour weeks.
What VGMM actually measures – in terms you care about
VGMM doesn’t care about your keyword rankings or whether you have perfect schema markup. It evaluates whether your organization is set up to sustain SEO performance without burning you out. Below are the five maturity levels that translate to your daily reality:
Level 1: Unmanaged (your current nightmare)
Nobody knows who’s responsible for SEO decisions.
Changes happen without SEO review.
You discover problems after they’ve tanked traffic.
You’re constantly firefighting.
Documentation doesn’t exist or is ignored.
Level 2: Aware (slightly better)
Leadership admits SEO matters.
Some standards exist but aren’t enforced.
You have allies but no authority.
Improvements happen but get reversed next quarter.
You’re still the only one who really gets it.
Level 3: Defined (getting somewhere)
SEO ownership is documented.
Standards exist, and some teams follow them.
You’re consulted before major changes.
QA checkpoints include SEO review.
You’re working normal hours most weeks.
Level 4: Integrated (the dream)
SEO is built into release workflows.
Automated checks catch problems before they ship.
Cross-functional teams share accountability.
You can actually take a vacation without a disaster.
Your expertise is respected and resourced.
Level 5: Sustained (unicorn territory)
SEO survives leadership changes.
Governance adapts to new AI surfaces automatically.
Problems are caught before they impact traffic.
You’re doing strategic work, not firefighting.
The organization values prevention over reaction.
Most organizations sit at Level 1 or 2. That’s not your fault – it’s a structural problem that VGMM helps diagnose and fix.
VGMM coordinates multiple domain-specific maturity models. Imagine it as a health checkup that evaluates all your vital signs, not just one metric.
It evaluates maturity across domains like:
SEO governance: Your core competency.
Content governance: Are writers following standards?
Performance governance: Is the site actually fast?
Accessibility governance: Is the site inclusive?
Workflow governance: Do processes exist and work?
Each domain gets scored independently, then VGMM looks at how they work together. Because excellent SEO maturity doesn’t matter if the performance team deploys code that breaks the site every Tuesday or if the content team publishes AI-generated nonsense that tanks your E-E-A-T signals.
VGMM produces a 0–100% score based on:
Domain scores: How mature is each area?
Weighting: Which domains matter most for your business?
Dependencies: Are weaknesses in one area breaking strengths in another?
Coherence: Do decision rights and accountability actually align?
The final score isn’t about effort – it’s about whether governance actually works.
Most importantly, VGMM translates your expertise into language that leadership understands. It protects your work from accidental destruction, so you can focus on strategic, creative, growth-focused work that truly matters.
I recently came across an intriguing study by SALT.agency, focused on Google’s AI Mode and its citation practices. Contrary to popular belief, this analysis shows that AI Mode doesn’t have a preference for content placed “above the fold.”
After sifting through over 2,300 URLs cited by AI Mode, researchers discovered no link between a text’s vertical position on a page and its likelihood of being cited by Google.
Pixel depth is irrelevant. The study revealed that AI Mode pulls text from all over a page, even from content located thousands of pixels down.
Page layout vs. content visibility. While different layouts like large hero images or narrative formats might push text deeper down the page, this doesn’t impact whether it gets cited.
Subheadings make a difference. One key pattern identified was AI Mode’s tendency to highlight a subheading and the subsequent sentence. This suggests Google’s heading structures are crucial for content navigation.
Google’s approach. The assumption is that AI Mode employs fragment indexing technology, breaking pages into sections and pulling the most relevant fragment, irrespective of its position.
Dan Taylor, a partner at SALT.agency, confirms that there’s no secret formula for appearing in AI Mode citations. The focus should always be on crafting well-structured, authoritative content that meets customer needs.
Our takeaway. This study challenges the notion that specific AI-focused templates or rigid structures enhance content visibility in AI Mode. The real work lies in creating meaningful, structured content.
Research background. SALT scrutinized 2,318 URLs in AI Mode responses. The vertical pixel position of each cited fragment was meticulously recorded using a Chrome bookmarklet and a 1920×1080 viewport.
I realized relying solely on GA4 to assess the impact of AI SEO is like using a broken compass. While GA4 is a great starting point, it doesn’t paint the whole picture.
It’s crucial to look beyond Google’s tools to truly understand how audiences find and choose brands. SEO isn’t just about visits; it’s a journey shaped by algorithms and AI long before visits occur.
Focusing only on measurable visits hides parts of this journey, leaving potential customers adrift. Understanding user intent through share of voice and mapping brand visibility with AI analytics is key.
I’ve learned that measuring AI visits with GA4 begins with tracking sessions from various AI sources. Creating a custom exploration to track these is an important first step.
Despite its ease, GA4 struggles to fully capture AI’s impact. Many AI outputs can’t be distinctly tracked, making it crucial to explore other data sources to get a complete picture of brand impact.
Both Google Search Console and Bing Webmaster Tools don’t separate AI queries effectively, often mixing AI metrics with standard web traffic, making it challenging to gauge AI’s real impact.
I’ve found utilizing regex in GSC to identify conversational queries useful, but as query diversity grows, distinguishing synthetic from human becomes harder.
Exploring AI agent analytics through log files has been insightful. AI agents using text-based browsers evade traditional analytics, requiring SEOs to delve into bot logs for agent patterns without real human traffic miss them.
Following AI agent request paths, especially to conversion pages, reveals broken journeys and insights into improving user paths.
Reassessing traditional SEO reporting frameworks is essential for adapting to AI’s transformational role in search discovery.
We need tools that track in-chat brand mentions and citations beyond standard website links. AI search analytics must evolve, reflecting SEO’s expansion towards measuring meaningful marketing KPIs and increasing market share.
As an SEO, my goal is no longer optimizing just a website. It’s about building a robust digital brand—one that is visible and trusted across all organic surfaces.
Starting out in the B2B market, I quickly realized the power of making an impact right at the beginning of a buying decision. It’s surprising to learn that 86% of buyers have already picked their preferred vendors on Day 1. In this article, I’ll share how a strategic video approach can connect with buying groups and drive demand.
There’s a common misconception in B2B marketing: video is often seen merely as a tool for brand awareness. Many believe it either serves as a ‘viral’ content piece that gets views but no leads, or as a tedious demo that attracts leads but no engagement.
However, this black-and-white approach can actually harm your sales pipeline.
Being a part of LinkedIn, I have a unique perspective on the B2B buying ecosystem. The data clearly indicates that the most successful companies don’t confine video to one part of the sales funnel. Instead, they use it like a leverage for growth.
By integrating video across the entire buying journey, linking brand with demand, companies see a noticeable increase in lead generation—up to 1.4 times more leads.
Let’s delve into the framework that backs this success, guided by fresh insights into B2B buying behaviors.
The reality: The ‘first impression rose’
Many marketers underestimate how soon they need to influence a deal.
At LinkedIn’s B2B Institute, we refer to this critical window as the “first impression rose.” Much like in “The Bachelor,” not getting noticed early reduces your chances of winning at all.
Research by LinkedIn and Bain & Company shows that 86% of buyers’ decisions are practically made on Day 1, and 81% will eventually buy from the vendors on their initial list.
If your video strategy shows up only when buyers are actively looking, you’re left fighting for the remaining 19% who aren’t already committed. To truly compete, you need to be at the top of the list even before a request for proposal (RFP) is crafted.
This is where a three-play strategy becomes crucial.
Play 1: Reach and prime the ‘hidden’ buying committee
The goal: Reach the people who can say ‘no’
Many video strategies focus on the “champion” or the user, but often, they aren’t the decision-makers.
Picture this: After investing time in wooing the VP of Marketing, you find them enthusiastic about your solution and ready to proceed. But at the procurement meeting, the CFO questions, “Who is this company?” Due to a lack of recognition with those controlling the budget, you face unexpected hurdles.
Data shows you are over 20 times more likely to be chosen if the entire buying group is aware of you on Day 1.
The strategic shift: Cut-through creative
To capture this broader audience, mere visibility isn’t enough; you need to stand out. Reach and recall go hand in hand.
LinkedIn data highlights what makes content “cut-through creative”:
Be bold: Utilize bold, vibrant colors in video ads to boost engagement by 15%.
Be process-oriented: Simplify messaging into clear steps to enhance viewer retention by 13%.
The “Goldilocks” length: Videos running for 7-15 seconds hit the sweet spot for brand lift—outperforming both ultra-short and long-form ads.
The “Silent Movie” rule: Craft visuals that communicate without sound since 79% of LinkedIn users scroll soundlessly. If your video leans on spoken content initially, you’ve missed engaging 80% of your audience. Implement visual hooks and captions for instant engagement.
This is the stage where many B2B efforts fall short. Most content pushes capability—features and specs—while true buyability is often neglected.
Buyers are weighing personal and career risks when drawing up their list of vendors.
Our joint research with Bain & Company uncovered that buyers prioritize emotional assurance, with only two out of five primary considerations being centered around product capability.
The top priority (34%) was ensuring confidence in defending their decision if things went awry.
The strategic shift: Market the safety net
Video content should be more than a list of features; it should act as a safety net. What can this look like in practice?
Momentum is safety (the “buzz” effect)
Buyers gravitate toward leaders. By building a buzz, brands can increase leads by 10%.
You can generate buzz via cultural references, which increase engagement by 41% and even more significantly with memes, boosting it by 111%. This approach shows you’re in tune, relatable, and part of the conversation.
Authority builds trust (the “expert” effect)
If momentum draws them in, then expertise builds lasting trust. The presentation of that expertise is crucial.
Utilize video ads with executive experts for a 53% boost in engagement, and capture them on stage at conferences to increase this by 70%.
The implication of authority communicates a powerful message—”This person is insightful enough to be worth listening to.”
Consistency is credibility
Constant engagement, rather than sporadic bursts, is key. Maintaining an always-on campaign enhances conversions by 10% compared to brands that pause and restart their efforts. Trust is cumulative.
Have you heard the news about LinkedIn’s recent experiences with AI-powered search? It turns out that Google’s AI Overviews have significantly impacted our non-brand B2B awareness traffic, cutting it by up to 60% in some areas, even while rankings remained steady. This shift compels us to rethink our discovery strategies fundamentally.
I’ve noticed we’re transitioning from the traditional ‘search, click, website’ model to a more dynamic approach: ‘Be seen, be mentioned, be considered, be chosen.’ This new paradigm reflects a deeper understanding of modern digital visibility.
By the numbers. Early in 2024, our B2B organic growth team started researching Google’s Search Generative Experience (SGE). By the time SGE evolved into AI Overviews in 2025, the impact was undeniable. Our non-brand, awareness-driven traffic took a hit of up to 60% across specific B2B topics.
Yes, but. Many of the insights we’re gathering are reiterations of established SEO and AEO best practices. I’ve learned that LinkedIn’s guidance emphasizes strong headings, clear information hierarchy, improved semantic structure, and accessibility. It also stresses publishing authoritative, fresh content by experts and moving quickly to gain an early advantage.
Why we care. These strategies should be familiar to anyone versed in technical SEO and content-quality fundamentals. LinkedIn’s article may not present new tactics, but it highlights the relevance of modern SEO/AEO and AI-driven visibility.
Measurement is broken. A significant challenge we face is the ‘dark’ funnel—the difficulty of quantifying how visibility in LLM answers affects our bottom line when discovery occurs without a click.
LinkedIn has seen triple-digit growth in LLM-driven traffic to its B2B marketing websites. However, while we can track conversions from these visits, many websites are also experiencing similar growth. Although it’s an emerging channel, LLM-driven traffic still represents a small portion of overall traffic.
What LinkedIn is doing. To tackle these challenges, we’ve formed an AI Search Taskforce that spans SEO, PR, editorial, product marketing, and more. We’re correcting misinformation in AI responses, publishing new content optimized for AI visibility, and testing social content for AI discovery strength.
Is it working? It’s exciting to see our efforts yielding results. Our early tests are showing a meaningful increase in visibility and citations, particularly from our owned content. According to one external datapoint from Semrush, our structural advantage in AI search is significant, with Google AI Mode citing LinkedIn in 15% of responses.
Incomplete story. While LinkedIn’s developments are noteworthy, some details remain unclear. We’re still waiting on specifics like the exact topics behind the traffic decline, how much click-through rates have softened, sample sizes, and timeframes. These details could provide clarity on the broader industry impact.
Bottom line. I believe LinkedIn’s insights affirm that visibility is the new currency in digital marketing. However, there’s still much to prove if our playbook truly differentiates us from basic SEO practices.
I’m excited to share how combining SEO and AEO competitive research can reveal new opportunities, shape your strategic positioning, and enhance AI visibility before a click even happens.
Competitive research is like striking gold in organic discovery. Clients love seeing where they stand compared to rivals, and these insights pave the way for a multi-layered action plan on crucial topics.
This year, it’s time to integrate answer engine optimization (AEO) research—what I also call AI search—into your organic strategy. Whether or not your executives are already asking for it, the benefits are clear.
In this article, I’ll dive into the unique contributions of SEO and AEO competitive research, the tools at our disposal, and how these insights translate into actionable steps.
Traditional SEO excels at content planning and tackling specific keywords, but the landscape in 2026 demands more. Merging SEO with AI competitive research offers a holistic strategy for messaging, content creation, and even product marketing roadmaps.
Tools like Ahrefs and Semrush are invaluable for SEO, aiding demand capture and keyword mapping, but AI’s emergence in search means we need to pivot focus. SEO should now bolster AI strategies, refine content gaps for AI systems, and validate demand.
AEO tools address different customer journey stages, crafting demand, framing brands, and influencing decisions before a search result click. They synthesize insights like market perception, directly impacting how users see competitor visibility and perception.
With AI insights, I can pinpoint competitor feature expectations, spotlight emerging trends, and verify our strategies align with market explanations. This knowledge empowers us to lead in category perception and ensure our messaging resonates with users.
In tool selection, platforms like Profound, Ahrefs, and ChatGPT offer a diverse suite for both SEO and AEO, each contributing different insights and functionalities. These extend from classic ranking analysis to intricate AI-answer exposure.
Using AI tools alongside traditional methods helps offer a fuller understanding of competitive landscapes. Implementing these insights isn’t just academic—it’s crucial for clients and internal alignment on marketing action plans.
