As brands compete for market share across a whole range of AI platforms, each with its own way of presenting information, brands are on red alert.

The three pillars of presence, perception, and performance that I discuss in this article may help marketers navigate new times. This is especially true as search and AI undergo their biggest make-over ever.

What’s driving this change?

AI isn’t just retrieving information anymore – it’s actively evaluating, framing, and recommending brands before prospects even click a link.

It’s happening now, and it’s accelerating.

Think about it. Today, in many ways, ChatGPT has become just as synonymous with AI as Google was when it launched core search.

More and more users and marketers are experimenting with and utilizing Google AIO, ChatGPT, Perplexity, and more.

According to a recent BrightEdge survey, over 53% of marketers regularly use multiple (two or more) AI search platforms weekly.

AI Is Reshaping How Brands Are Presented And Perceived

Consider how buyers research options today: In Google AIO, a traveler planning a Barcelona vacation once needed dozens of separate searches, each representing an opportunity for visibility.

Now? They ask one question to an AI assistant and receive a complete itinerary, compressing what 50 touchpoints once took into a single interaction.

AI is no longer a passive search engine. It’s an active evaluator, interpreting intent, forming opinions, and determining which brands deserve attention.

In enterprise SEO and B2B contexts, the shift is even more pronounced. AI is effectively writing the request for proposal (RFP), establishing evaluation criteria, and creating shortlists without brands having direct input.

Take enterprise software evaluation, for instance. When a CIO asks an AI about the “best enterprise resource planning solutions,” the AI’s response typically features:

• A curated shortlist of vendors.
• Evaluation criteria that the AI deems relevant.
• Strengths and limitations of each solution.
• Recommendations based on various scenarios.

These responses don’t just inform decisions. They frame the entire evaluation process before a vendor’s content is visited.

The question isn’t whether this transformation is happening. It’s whether your brand is prepared for it.

Read more: 5 Key Enterprise SEO And AI Trends For 2025

The Triple-P Framework For AI Search Success

After analyzing thousands of AI search responses using our BrightEdge Generative Parser™, I’ve developed the Triple-P framework (Presence, Perception, and Performance) as a strategic compass for navigating this new landscape.

Let’s break down each component.

Presence: Beyond Traditional Rankings

While Google still commands 89.71% of search market share, the ecosystem is diversifying rapidly:

• ChatGPT: 19% monthly traffic growth.
• Perplexity: 12% monthly traffic growth.
• Claude: 166% monthly traffic surge.
• Grok: 266% early-stage spike.

(Source: BrightEdge Generative Parser™ April 2025)

Our research shows that the presence of AI Overviews has nearly doubled since June 2024, with comparison features growing by 70-90% and product visualization features by 45-50% in B2B sectors.

For enterprise marketers, Google is always your starting point. However, it’s not just about ranking on Google anymore; it’s about showing up wherever AI models showcase your brand.

For example, consider these industry-specific implications:

• For CPG brands: When consumers ask about product sustainability, AI doesn’t just list eco-friendly options; it evaluates authenticity based on consistent messaging across digital touchpoints.
• For SaaS companies: Buyers researching integration capabilities receive AI-curated assessments that either position you as a compatibility leader or exclude you entirely.
• For healthcare providers: Patient questions about treatment options trigger AI responses that cite the most authoritative content, not necessarily the highest-ranking websites.

We are in an era of compressed decision-making. Invisibility equals elimination.

Perception: When AI Forms Opinions

The most revealing insight from our research is that only 31% of AI-generated brand mentions are positive; of those, just 20% include direct recommendations.

This is a wake-up call for all marketers, especially those managing a brand.

Even when your brand appears in AI results, how it’s framed varies dramatically depending on the AI model, training data, and interpretive logic.

In some AI engines, your brand may appear as the industry leader. In others, you may be completely absent.

What The Data Shows:

• Brands with strong pre-existing recognition receive more positive mentions in AI responses.
• Consistent messaging across digital touchpoints makes brands more likely to be cited positively.
• AI systems appear to “average” brand signals across the web when forming perceptions.

When we analyzed sentiment distribution (April 2025) in AI responses by industry, we saw significant variation, which you could group-match to verticals. For example:

• Finance: Positive mentions aligned around good content on regulatory compliance and security.
• Healthcare: Positive mentions aligned around good content with accuracy and credibility as key factors.
• Retail: Positive mentions aligned around good customer experience and shopping.
• Technology: Positive mentions aligned around content on innovation and reliability as primary criteria.

The implications are clear: Perception management is now as crucial as presence.

How does this play out in practice?

When brands implement coordinated perception management strategies across multiple channels, they see improvements in AI sentiment within 60-90 days.

Performance: New Metrics That Matter

The final P (Performance) requires entirely new measurement approaches.

When AI overviews appear in search results, click-through rates often drop by up to 50% according to internal BrightEdge data. Yet, conversion rates typically remain strong, suggesting AI qualifies leads before they reach your site.

We’re entering an era where impressions will be high, click-through rates may drop, but conversions will increase.

I explained at our recent quarterly briefing. AI filters options and delivers buyers who are closer to decisions.

The impact varies dramatically by query type:

• Informational queries: Reduction in clicks, minimal conversion impact.
• Navigational queries: Reduction in clicks, negligible conversion impact.
• Commercial queries: Reduction in clicks, higher conversion rates.
• Transactional queries: Reduction in clicks, higher conversion rates.

This pattern suggests AI is most effective at qualifying commercial intent, delivering more purchase-ready traffic.

And impressions matter now – they are a new brand metric.

Five Essential AI Search Metrics:

1. AI Presence Rate: Percentage of target queries where your brand appears in AI responses.
2. Citation Authority: How consistently you are cited as the primary source.
3. Share Of AI Conversation: Your semantic real estate in AI answers versus competitors.
4. Prompt Effectiveness: How well your content answers natural language prompts.
5. Response-To-Conversion Velocity: How quickly AI-influenced prospects convert. Brands with strong pre-existing recognition will receive more positive mentions in AI responses.

Position within AI responses matters as much as position in traditional SERPs once did.

Monthly reporting cycles are becoming obsolete. AI-generated results can shift within hours, demanding real-time monitoring capabilities.

The DNA Of AI-Optimized Content

In my experience, content is more likely to be cited by AI with:

• Comprehensive coverage: Content addressing multiple related questions outperforms narrow content.
• Structured data implementation: Pages with robust schema markup see higher citation rates.
• Expert validation: Content with clear expert authorship signals receives more citations.
• Multi-format delivery: Topics presented in multiple formats (text, video, data visualizations) earn more citations.
• First-party data inclusion: Original research and proprietary data increase citation likelihood.

These patterns suggest AI systems are increasingly sophisticated in their ability to identify genuinely authoritative content versus content merely optimized for traditional ranking factors.

In my last article, I discussed how Google AIO, ChatGPT, and Perplexity differ and where they share some common optimization traits.

Five Actionable Strategies For Triple-P Success

Based on our extensive research, here are five implementation strategies aligned with this framework:

1. Adopt Entity-Based SEO

AI prioritizes content from known, trusted entities. Stop optimizing for fragmented keywords and start building comprehensive topic authority.

Our data shows that authoritative content is three times more likely to be cited in AI responses than narrowly focused pages.

Implementation Steps:

• Perform an entity audit: Identify how search engines currently understand your brand as an entity.
• Develop topical maps: Create comprehensive coverage of core topics rather than isolated keywords
• Implement entity-based schema: Use structured data to explicitly define your brand’s relationship to key topics.
• Build consistent entity references: Ensure name, address, and phone (NAP) consistency across all digital properties.
• Cultivate authoritative connections: Earn mentions and links from recognized authorities in your space.

Enterprise brands implementing entity-based SEO will see an uplift in AI citations.

2. Implement Perception Management

With 69% of AI brand mentions not explicitly positive, you must actively shape sentiment.

Brands that implement proactive sentiment management strategies will see success.

Implementation Steps:

• Monitor AI sentiment tracking: Establish baseline sentiment across AI platforms.
• Identify perception gaps: Compare AI perceptions against desired brand positioning.
• Address criticism proactively: Create content that honestly addresses common concerns.
• Amplify authentic strengths: Develop evidence-based content highlighting genuine advantages.
• Build consistent messaging: Align key messages across all digital touchpoints.

3. Integrate Real-Time Citation Monitoring

Tracking AI citations regularly is now vital to improve mention rates.

This requires capability beyond traditional rank tracking or Google Search Console analysis.

Implementation Steps:

• Deploy continuous monitoring: Track AI responses for priority queries across platforms.
• Implement competitor citation alerts: Get notified when competitors gain or lose citations.
• Conduct prompt variation testing: Analyze how different user phrasings affect your brand’s inclusion.
• Track citation position: Monitor where within AI responses your brand appears.
• Measure citation authority: Assess whether you’re positioned as a primary or secondary source.

4. Deploy Cross-Core Search And AI Platforms

Companies that take an integrated approach across traditional search and multiple AI platforms will see higher return on investment (ROI) on search investments.

The future belongs to unified measurement frameworks that connect traditional SEO metrics with emerging AI citation patterns.

Implementation Steps:

• Build unified dashboards: Integrate traditional search metrics with AI citation data.
• Map keyword-to-prompt relationships: Connect traditional keywords to conversational AI prompts.
• Analyze traffic source shifts: Track changing patterns between direct search and AI-referred traffic.
• Segment by AI platform: Monitor performance variations across different AI search environments.
• Connect to business outcomes: Tie AI presence metrics directly to conversion and revenue data.

5. Use AI To Win At AI

This isn’t theoretical. It’s delivering measurable results:

• BrightEdge Autopilot users averaged a 65% performance improvement.
• BrightEdge Copilot users saved 1.2 million content research hours.

The brands succeeding most in AI search leverage AI in their workflows.

Implementation Steps:

• Automate content research: Use AI to identify comprehensive topic coverage opportunities.
• Implement AI-driven schema markup: Systematically structure data for machine interpretation.
• Deploy prompt effectiveness testing: Continuously test how well content answers real user prompts.
• Create AI-optimized content briefs: Define exactly what comprehensive coverage means for each topic.
• Analyze AI citation patterns: Identify what characteristics make competitor content citation-worthy.

Teams using AI for AI optimization will benefit from higher productivity and improved performance to gain that must-have competitive edge in search and AI today.

What’s Coming Next: AI-To-AI Marketing

Looking ahead to two to three years, expect AI to evolve from an information assistant to a trusted advisor that buyers rely on for evaluation, comparison, and vendor selection.

We’re already seeing early indicators of AI-to-AI marketing, where procurement teams use AI agents to automate research and vendor vetting.

Emerging Trends:

• Digital twin marketplaces: Buyers will interact with simulated versions of B2B solutions before speaking with vendors
• Vertical-specific AI companions: Industry-specialized models for cybersecurity, manufacturing, and healthcare.
• AI agent purchasing: Autonomous systems are not just researching but also completing transactions on users’ behalf.
• Continuous entity validation: AI systems continuously monitor brand claims against real-world evidence.
• Multi-modal search experiences: Voice, image, and text-based AI interactions requiring omnichannel optimization.

Read more: As Chatbots And AI Search Engines Converge: Key Strategies For SEO

The Trust Premium In AI Search

Consumers are always more likely to trust brands they already recognize.

• AI functions as a trust bridge.
• When consumers delegate decision-making to AI, pre-existing brand familiarity becomes disproportionately influential.
• The impact is most pronounced in high-consideration purchases.

This creates both a challenge and an opportunity. Established brands must protect their advantage, while emerging brands must strategically build recognition signals detectable by AI.

Organizational Structure For AI Search Success

Leading organizations are already creating “collaborative intelligence” roles – specialists managing the interplay between human creativity and AI amplification.

Successful teams typically include:

• AI Search Strategists: Focus on overall presence, perception, and performance.
• Prompt Engineers: Specialize in understanding how users phrase requests to AI.
• Content Scientists: Develop evidence-based approaches to comprehensive coverage.
• AI Citation Analysts: Monitor and optimize for inclusion in AI responses.
• Schema Specialists: Ensure that the machine-readable structure enhances entity understanding.

These cross-functional teams integrate with traditional SEO, content marketing, analytics, and business intelligence functions.

The Bottom Line

In this new landscape, the question isn’t whether your website ranks. It’s whether AI recommends your brand when it matters most.

The Triple-P framework gives you the structure to navigate this future with confidence.

Here’s what I recommend getting started:

• Conduct an AI presence audit: Understand where your brand appears in AI responses across key platforms.
• Analyze sentiment distribution: Assess not just if you’re mentioned, but how you’re portrayed in AI-generated content.
• Connect AI metrics to business results: Start tracking the relationship between AI presence and conversion patterns.
• Identify entity perception gaps: Compare how AI systems understand your brand versus your desired positioning.
• Deploy real-time monitoring: Implement systems to track citation changes as they happen.

The branded AI search revolution isn’t coming – it’s already here.

The brands that embrace the Triple-P framework today will be the ones AI recommends tomorrow.

Note: In March 2025, BrightEdge surveyed over 1,000 of its customers who are marketers. Findings from this survey are referenced above.

More Resources:

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Featured Image: Moon Safari/Shutterstock

https://www.searchenginejournal.com/triple-p-framework-ai-search-brand-presence-perception-performance/545829/

Anecdotal reports and an SEO jobs study describe a search marketing industry undergoing profound changes, not only in the skills in demand but also in hiring practices that may be making it difficult for experienced SEOs to get the jobs they are well qualified for.

Short History Of SEO Jobs

Twenty five years ago getting into SEO and earning a living was relatively easy. Many top corporations across all industries were hiring freelancers and agencies for specialized SEO assistance. I suspect that marketing departments didn’t view SEOs as a subset of marketing and that many didn’t have SEO staff. That gradually changed as more organizations hired dedicated SEO staff with third party SEOs providing specialized assistance.

What’s Going On With SEO Jobs?

A recent report on the state of SEO jobs provided by SEOJobs.com shared the state of SEO jobs in 2024.

The following insights show that the job of SEO continues to evolve:

• SEO job openings declined in 2024
• Median SEO salaries dropped
• 65% of SEO jobs are in-house
• Remote SEOs jobs dropped
• SEO job titles related to content strategy and writing dropped by 28%
• SEO Analyst job titles dropped by 12%.
• Technical SEO and related titles dropped by a small percentage
• Senior level titles like manager, director, and VP had the strongest increases.

The report says that job titles related to Technical SEO dropped:

“Positions in the Technical SEO and related title group represented 5.8 percent of all SEO jobs during the first quarter of 2024, falling slightly to 5.4 percent by the end of the fourth quarter – a decrease of seven percent.”

But the report also states that Technical SEO is still an in-demand skill:

“…demand for skill in technical SEO grew at the fastest rate of any skill during the fourth quarter, rising to 75 percent from 71 percent the previous quarter.”

Experienced SEOs Having Trouble Getting Hired… By AI?

Keith Goode read the above referenced report and commented that he believes the reason many highly experienced SEOs are failing to get a job is because of a poor implementation of AI into the hiring process.

He shared his insights on a LinkedIn post:

“I have seen superior SEOs languish amongst thousands of candidates, immediately rejected for a lack of experience (??) or funneled through multiple rounds of interviews and work assignments, only to be rudely ghosted by the recruiters.

The cause? I guess you could blame AI if you wanted to shoot the messenger. But the reality is that companies have overinvested in an unproven technology to handle things that it’s not yet ready to handle. I get that recruitment teams are deluged with thousands of resumes for every opening, and I understand they need a way to streamline the screening process.

However, AI has proven to be more of an enemy within than a helper. Anecdotally, I’ve heard about a hiring manager who applied for their own job opening (presumably one they were more than qualified for) only to receive an immediate rejection from the AI-powered ATS. That person fired their hiring team.

(By the way, I’m not anti-AI. I’m anti-foolishness, and a lot of companies are acting like fools.)”

Experienced SEOs Are Getting Ghosted

It may be true that SEOs with decades of experience are being left behind by poor AI vetting. A glaring example is the one shared by Brian Harnish, an SEO with decades of hands-on experience.

Brian recently published the following on LinkedIn and Facebook:

“In this job market, for me it simply appears that nothing matters.

• You can apply at 6:15 a.m. the day the job posting pops up and be one of the first.
• You can change your resume 15 times like I have.
• You can use ResumeWorded. com for an ATS version of your resume.
• You can write your resume yourself until you’re blue in the face.
• You can follow up on the interview with thank yous immediately after.
• You can follow up on interview decisions later.
• You can agree to their salary ranges exactly. Even when it’s a pay cut for you.
• A/B testing long vs. short resumes yield the same results.
• You can tie in all of your achievements with task > impact > website statements on your resume.
• You write an entirely customized LinkedIn profile.
• You can know all the right people.
• You can network up the wazoo.
• You can have the greatest interview that you feel you’ve ever put forth.

But companies don’t provide feedback. It’s always the same form letter: “while your qualifications are impressive, we went with another candidate.” Or you’re ghosted.

This market is brutal. I really want a job. Not a handout. But nobody appears to want to hire me. At all. Despite doing EVERYthing right. I used to get hired on the spot. Now it’s just crickets.”

What The Heck Is Going On?

I know of other SEOs, also with decades of experience across all areas of SEO who should have just bounced to a new job in a matter of days but took months to get hired. I’m talking about people with SEO director level experience at top Fortune 500 companies.

How does this happen?

Are you experiencing something similar?

Featured Image by Shutterstock/Ollyy

https://www.searchenginejournal.com/is-the-seo-job-market-undergoing-a-major-shift/546433/

Feeling overwhelmed by AI in search?

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https://www.searchenginejournal.com/ai-search-strategy-with-limited-resources/545286/

Google took the unusual step of issuing a response to news reports that AI search engines and chatbots were causing a decline in traditional search engine use, directly contradicting testimony given by an Apple executive in the ongoing U.S. government antitrust lawsuit against Google.

Apple Testimony That Triggered Stock Sell-Off

Google’s stock price took a steep dive on the news that people were turning away from traditional search engines, dropping by 7.51% on Wednesday. What triggered the stock sell-off was testimony by Eddy Cue, Apple’s senior vice president of services, who testified that search engine use by users of Apple’s Safari browser declined for the first time last month, expressing his opinion that a technological shift is underway that is undercutting the use of traditional search engines.

Early AI Adopters Turning Away From Google?

There is a view in Silicon Valley that Google Search is legacy technology. A recent episode of the Y Combinator show featured the host sharing that their Google search traffic has dropped by 15% and that he attributes that to AI use in both Google and chatbots. He explained that if you want to see the future you look to the early adopters, commenting that everyone he knows in Silicon Valley uses ChatGPT to get answers and that Google Search is defacto legacy technology.

The host described how 25 years ago the early adopters were using Google but that now, Google Search feels weird to him.

He said:

“People are now switching their behavior to where your default action if you’re looking for information is, you know ChatGPT or perplexity, or one of these things, and even just, you know, observing my own behavior. I’ll use Google mostly for kind of navigational. Like, if I’m just looking for a specific website and I know it’s going to give the same thing, but it’s starting to have that weird kind of, like legacy website, like I’m using eBay or something.”

Google’s Statement

Google’s statement was short and to the point, with no accompanying images to make it look like a blog post. Google’s statement could even be seen as terse.

Here’s what Google published:

“Here’s our statement on this morning’s press reports about Search traffic.

We continue to see overall query growth in Search. That includes an increase in total queries coming from Apple’s devices and platforms. More generally, as we enhance Search with new features, people are seeing that Google Search is more useful for more of their queries — and they’re accessing it for new things and in new ways, whether from browsers or the Google app, using their voice or Google Lens. We’re excited to continue this innovation and look forward to sharing more at Google I/O.”

AI Revolution: What Nobody Else Is Seeing

Here’s the video of the Y Combinator show that offers a peek at how people in Silicon Valley relate to Google Search. The part I quoted is at about the 24 minute mark.

[embedded content]

Featured Image by Shutterstock/Framalicious

https://www.searchenginejournal.com/google-disputes-news-that-search-traffic-is-falling/546233/

Apple is reportedly planning to redesign Safari to focus on AI search engines.

According to recent testimony in the Google antitrust case, this comes as the company prepares for possible changes to its profitable Google deal.

Apple Signals Shift In Search Strategy

Eddy Cue, Apple’s senior vice president of services, testified that Safari searches dropped for the first time last month.

He believes users are choosing AI tools over regular search engines. This change happens as courts decide what to do after Google lost its antitrust case in August.

Per a report from Bloomberg, Cue testified:

“You may not need an iPhone 10 years from now as crazy as it sounds. The only way you truly have true competition is when you have technology shifts. Technology shifts create these opportunities. AI is a new technology shift, and it’s creating new opportunities for new entrants.”

AI Search Providers May Replace Traditional Search

Cue believes AI search providers such as OpenAI, Perplexity AI, and Anthropic will eventually replace traditional search engines like Google.

“We will add them to the list — they probably won’t be the default,” Cue said, noting Apple has already talked with Perplexity.

Currently, Apple offers ChatGPT as an option in Siri and plans to add Google’s Gemini later this year.

Cue admitted that these AI search tools need to improve their search indexes. However, he said their other features are “so much better that people will switch.”

“There’s enough money now, enough large players, that I don’t see how it doesn’t happen,” he said about the shift from standard search to AI-powered options.

Context: Google’s Antitrust Battle Timeline

This testimony comes during a key moment in the case against Google:

• August 2024: Judge Mehta ruled Google broke antitrust law through exclusive search deals
• October 2024: DOJ proposed remedies targeting search distribution, data usage, search results, and advertising
• December 2024: Google offered counter-proposals to loosen search deals
• March 2025: DOJ filed revised proposals, including possibly forcing Google to sell Chrome

The $20 Billion Question

The core issue is Google’s deal with Apple, worth a reported $20 billion per year, that makes Google the default search engine on Safari.

While expecting changes to this deal, Cue admitted he has “lost sleep over the possibility of losing the revenue share from their agreement.”

We learned about this payment during the trial. In 2022, Google paid Apple $20 billion to be Safari’s default search engine.

Last year, they expanded their partnership to add Google Lens to the Visual Intelligence feature on new iPhones.

Proposed Remedies & Responses

The DOJ’s latest filing suggests several significant changes:

• Making Google sell off Chrome
• Limiting Google’s payments for default search placement
• Stopping Google from favoring its products in search results
• Making Google’s advertising practices more transparent

Google has criticized these proposals, calling them a “radical interventionist agenda” that would “break a range of Google products.”

Instead, Google suggests letting browser companies deal with multiple search engines and giving device makers more freedom about which search options are preloaded.

What This Means

If Apple shifts Safari toward AI, prepare for significant changes in search.

It’s not a stretch to say the outcome could reshape search competition and digital marketing for years.

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Featured Image: Bendix M/Shutterstock

https://www.searchenginejournal.com/apple-may-add-ai-search-engines-to-safari-as-google-use-drops/546220/

Sometimes, SEO success isn’t about technical factors, content, or backlinks – or even about adapting to the changes prompted by AI.

Many times, companies unknowingly have their SEO investments or efforts sabotaged by internal silos.

At best, silos can cause slow implementation and, at worst, missed opportunities and budget that is wasted on the effort overall.

I admit: There were times, two decades ago, when I was doing SEO for over a dozen clients, that I enjoyed the level of control that I had over content, technical factors, website updates, and more. Clients were fine handing off these tasks, which gave me more direct influence on rankings, traffic, and conversions.

Today, though, I’m good with the fact that SEO requires multiple disciplines and a much bigger focus on the end user rather than the search engine itself.

One of the biggest barriers to SEO success today is internal silos which can impact strategy, integration, speed, and focus that can negatively impact the return on investment (ROI).

I’m going to unpack five specific silos that I see often within organizations of varying sizes and focus on helping you improve SEO collaboration to see your efforts and investments through to success.

1. Compartmentalization Of Strategy

For a number of reasons, SEO can be put into a silo or looked at as a tactic and not a channel within the broader mix of digital marketing, or marketing overall for a company or organization.

It can be an extra “hat” that someone wears. Or, you can have a habit of looking at it as if you’re going to apply SEO to something.

When SEO is something you ‘apply’ to something, a tactic, or a split focus, it isn’t going to work well or often.

To be effective, it requires a strategic and goal-driven approach. There is too much complexity to it for it to be applied to something at the end or sprinkled into things.

SEO strategy development is critical and should be directly linked to broader digital marketing and overall marketing strategy so it is efficient, results-focused, and given a proper level of investment with an expectation of return on that investment.

2. Lack Of Channel Integration

In larger teams with larger agency partners, and even with a single person wearing multiple hats, digital marketing channels can find their ways into silos.

Whether it is a lack of integration of paid search with SEO or broader issues of not connecting other digital channels with similar goals, customer journeys, or funnels, we can find more hidden silos.

Paid search is a good example here, as both SEO and PPC focus on attracting the same audience – searchers who land on a search engine results page.

The real estate is a little different on that page, and the targeting might be as well. Still, if we’re not sharing research, analytics, content, and insights, then we’re likely duplicating efforts somewhere and creating strategies and tactics in parallel that could be done more effectively in an integrated way.

More broadly, other digital marketing channels like email marketing and social media which are pointing prospects and customers to the website have overlapping needs and efficiency opportunities as well when we blow up the silos and walls between them.

3. Content Strategy Disconnect

I tell someone weekly that content is fuel for the digital marketing channels and platforms we engage with.

A content strategy that is siloed is one of the biggest challenges in an organization.

Back in the day, I would make content decisions and work with SEO copywriters to create content just for SEO needs and purposes.

Social media emerged and did the same. Email marketing was already doing it, too.

I learned quickly how we could all work together from a higher level strategy not to just find new levels of efficiency and cost effectiveness, but also to make sure we were consistent and on-brand in messaging so we weren’t wasting our efforts with inconsistent voice, tone, offers, and value propositions in front of our target audiences.

A unified content strategy is crucial for creating content once, on brand, and aligned with the overall marketing goals.

It then provides the specific formats and needs for various channels, such as SEO, to ensure proper prioritization and maximize effectiveness.

4. Data Isolation

When living daily life “in the weeds,” or deep in the details of subject matter, it is easy to look at the specific metrics and key performance indicators (KPIs) that matter at that level.

Organic traffic performance might be what you’re evaluating or are graded on if you’re an SEO. On the other side, if you’re a CMO, you might be handed a report or linked to a dashboard showing very detailed SEO results.

Does your organization have integrated data? Can you see top-level digital marketing metrics and drill all the way down to SEO results? Can you ladder up from SEO to the ultimate impact it is having on digital marketing ROI?

One of the biggest frustrations I hear from executives and business owners is that they struggle to connect the dots between the SEO reporting they’re seeing and the company’s bottom line. That’s a problem.

If a CFO or someone unfamiliar with SEO is trying to make the connection, then you have a data isolation problem and need to better integrate your data across channels, teams, and functions to map digital marketing performance to business outcomes.

5. Web Development Bottleneck

If those responsible for SEO aren’t also responsible for website development and updates, then this can be a very real silo for you and maybe not one that is all that hidden.

Early in my career, working with a national restaurant chain, I had a set of recommendations and needs to move the brand forward in each local market.

I had the unique content for each location ready, along with a dynamic system for implementing it from a database (before open-source CMS platforms were a thing).

It was estimated to take three days for the development team to complete the update. After a few months of pulling it all together, we encountered a roadblock.

The client’s IT team wasn’t able to get to it for six months! They were in the middle of a core system update for their restaurants and couldn’t spare a minute to address it, as they didn’t have the budget or infrastructure to allow an outside entity into their environment.

I can tell you countless stories of in-house resources and third-party resources that are similarly booked up, aren’t read into the impact, or aren’t prioritized around the needs of SEO strategies and goals. This is an important silo to break down.

Wrapping Up

Maybe you feel like your SEO efforts are hitting on all cylinders. I hope that’s the case.

The insights I unpacked in this article are simply a set of important reminders or things to be mindful of and make sure don’t become silos and roadblocks in your organization.

Maybe something here struck a nerve or hit directly on what you’re experiencing. If that’s you, then please don’t give up.

I have talked with many CMOs, marketing directors, business owners, and others over the years who were convinced that SEO doesn’t work and that it isn’t for them.

While in some edge cases that’s true, I often dig a level or two deeper to find hidden silos or barriers that were challenges from the start that weren’t addressed and were the root cause holding them back.

More Resources:

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Featured Image: Pixel-Shot/Shutterstock

https://www.searchenginejournal.com/internal-silos-are-overlooked-problem-can-hurt-search-performance/544919/

Google’s Search Liaison explained limitations in Google’s ability to return web pages from a prior date, also noting that date-based advanced search operators are still in beta. He provided one method for doing this but omitted discussing an older, simpler method that almost accomplishes the same thing.

How To Find Articles By Older Published Date

The person asking the question understood how to find articles published from the previous year, month, and twenty four hours. But didn’t know how to find articles published before a specific date.

The post on Bluesky asked:

“Is there a way to search for articles OLDER than a certain date?

I know advanced search can guarantee in the past year, month, 24h, but I want to specifically be able to find articles published BEFORE X historical event happened, and I can’t find a way to filter. Help?”

Search Liaison posted this way to do it which can be difficult to memorize if you’re a busy person:

“We have before: and after: operators that are still in beta. You must provide year-month-day dates or only a year. You can combine both. For example:

[avengers endgame before:2019]
[avengers endgame after:2019-04-01]
[avengers endgame after:2019-03-01 before:2019-03-05]”

Another Way To Do Time-Based Search

In my opinion it’s a lot easier to just use Google’s search tools:

Tools > Any Time > Custom Range

From there you just set whatever time range that you want, nothing to memorize. However, you can’t search before a certain date, you have to set the starting date and ending date you’re searching for.

Caveat About Time-Based Search

Search Liaison shared an interesting insight about how the advanced search operators for time work:

“Just keep in mind it can be difficult for us to know the exact date of a document for a variety of reasons. There’s no standard way that all site owners use to indicate a publishing or republishing date. Some provide no dates at all on web pages. Some might not indicate if an older page is updated.”

Related: Google: How to Use Search Operators for SEO

Takeaways:

The time-based advanced search operators are still in beta, which means that Google is testing to see how many people find it useful. Google might at some time in the future remove the search operators if it’s not popular or useful.

The other takeaway is that it’s hard for Google to know the exact date that a document is published.

Read the discussion on Bluesky.

https://www.searchenginejournal.com/google-shares-insight-about-time-based-search-operators/545963/

Yelp’s antitrust case against Google just survived a critical test.

While a judge tossed several claims, she allowed Yelp’s core challenge – focused on Google’s alleged monopoly in local search – to move forward. The broader battle over Big Tech’s power is far from over.

The central claims that Google unfairly used its dominance in the local search and local ad markets are now headed toward a jury trial.

If Yelp prevails, the case could significantly reshape the structure of local search in the U.S. and beyond.

Even if it doesn’t, the discovery process alone may offer an unprecedented window into Google’s internal thinking around local search.

Last week, Judge Susan Van Keulen of the U.S. District Court for Northern California denied in part Google’s motion to dismiss the case.

She ruled that Yelp’s key allegations – that Google monopolized and abused its control over local search and local advertising – were plausible enough to proceed.

Statute Of Limitations Doesn’t Apply

Google argued that its conduct, such as changes to search results design and integration of local content, dated back to at least 2007 (e.g., Universal Search) and that Yelp’s claims were therefore filed too late.

The judge disagreed, holding that for claims under Section 2 of the Sherman Act, the clock starts ticking not when the conduct occurred, but when the defendant both:

1. Possessed monopoly power in the relevant market.
2. Engaged in exclusionary conduct that injured the plaintiff.

The judge noted that “Because the governing statute here concerns an exercise of monopoly power, the qualifying ‘act’ must involve Google’s alleged monopoly; exclusionary conduct on its own, in the absence of market power, is insufficient.”

She also noted that Yelp had not definitively alleged when Google obtained monopoly power in local search or local search advertising, and that the timeline wasn’t clear enough from the face of the complaint to justify dismissal and went to say that “The timing of when Google crossed the 65% threshold of market power is simply not clear from the face of the Complaint.”

Where Google’s Motion To Dismiss Succeeded

The judge did, however, dismiss Yelp’s claims that Google used its general search monopoly to force users into its local search services (tying) and to gain dominance in local search advertising (monopoly leveraging).

She agreed with Google that the tying claim was time-barred and that Yelp hadn’t properly shown unfair expansion into new markets. However, the court granted Yelp the opportunity to amend its tying claim.

Yelp appeared pleased with the results, stating to Near Media that the ruling “marks an important step forward in Yelp’s case against Google. As we argued in our opposition to Google’s motion, and as the Court recognized, Google’s anticompetitive behavior deserves to be examined.”

The judge also agreed that Yelp’s argument – that local search and local ads are distinct markets – is a valid and plausible claim.

She allowed the case to proceed to determine whether these markets are entitled to antitrust protection and whether Yelp is entitled to damages.

Additionally, the court accepted Yelp’s allegations that Google has a long history of exclusionary acts.

Key questions remain: When did Google achieve monopoly status in local search and advertising, whether the four-year statute of limitations applies, and – more critically – whether Google has committed new, unique exclusionary acts that could restart the statute of limitations clock.

These cases unfold on their own timeline. Next steps include whether Yelp amends its tying claims, a discovery phase, and an attempt at alternative dispute resolution.

This process is likely to take about 18 months. Given that Google is unlikely to dramatically change its local search behavior – and that Jeremy Stoppelman, Yelp’s CEO, is unlikely to settle for anything less – resolution outside of court seems improbable. A trial could occur around the end of 2026.

Why This Case Matters

This is the first time anyone has examined Google’s behavior in local search, including how it won its monopoly and the impact that has had on local search and local ads, both within Google and across the broader local ecosystem.

If the court finds Google’s practices unlawful, it could force changes:

• Local search, as we know it, could dramatically change. It could spell the end of the Local Pack.
• Local ads, particularly Local Service Ads (LSAs), exemplify the kind of new, exclusionary behavior Google has leveraged to dramatically reduce organic and local opportunities (Yelp argues). This could become a target of any settlement.
• The outcome could also influence the EU’s interpretation of Google’s monopoly under the newly implemented DMA regulations.
• Any decision could also impact Google’s ability to introduce new AI features to local search, particularly features like local AI Overviews or “Learn something specific” that could be construed as a form of exclusionary local behavior.

What We May Discover

As with the U.S. government cases against Google, discovery is likely to uncover fascinating details about how Google positions local search – and, hopefully, some algorithmic insights into how local search and ads actually function.

Even if Yelp ultimately loses, the discovery process could still offer an unprecedented look inside Google Local and LSAs, giving us the first definitive glimpse into the world in which we live, work, and breathe.

Eighteen months may seem like a lifetime in internet marketing and Google local developments, but this is one that is worth keeping an eye on.

You can read a full timeline of the events here.

And read the original documents here:

More Resources:

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Featured Image: Phanphen Kaewwannarat/Shutterstock

https://www.searchenginejournal.com/yelp-vs-google-antitrust-case-survives-first-big-test/545781/

Reddit’s first-quarter 2025 earnings report shows strong growth in traffic and user engagement, particularly among logged-out users. Although the announcement and shareholder letter did not mention search engines or the temporary decrease in traffic in February, the increase in logged-out traffic suggests year-over-year growth from external referrals from search engines and social media.

The shareholder letter indirectly referenced search traffic:

“For seekers, Reddit’s open nature is essential—it allows our content to surface across the open web and be easily found in search. We remain one of the last major platforms that doesn’t require you to sign in to learn something because we believe that by giving everyone access to knowledge, we are helping fulfill the purpose of the internet. This openness broadens visibility, drives awareness, and brings us new users— but it also means that some of our traffic from external sources is variable. “

TL/DR

• Over 400 million people visit Reddit weekly, and total revenue reached $392.4 million for the quarter, representing a 61% year-over-year increase.
• More users are logged-in, improving Reddit’s value for ad targeting and audience engagement, which is good news for digital marketers.
• Growth in logged-out users suggests increased external referrals from search and social, a trend that may concern publishers and SEOs

Platform Growth and User Activity: Daily Active Unique Visitors

Reddit refers to their daily active uniques as DAUq. The Reddit quarterly report defines Daily Active Uniques (DAUq) as:

“We define a daily active unique (“DAUq”) as a user whom we can identify with a unique identifier who has visited a page on the Reddit website, www.reddit.com, or opened a Reddit application at least once during a 24-hour period.”

Reddit reported 108.1 million Daily Active Uniques (DAUq), a 31% increase compared to the same quarter last year. Weekly Active Uniques (WAUq) reached 401.3 million globally, also up 31% year-over-year.

Daily Active Uniques: U.S. Versus International

Daily Active Uniques for both U.S. and International saw significant increases compared to the same period last year, with international visits post nearly double the gains for the United States.

• U.S. DAUq was 50.1 million, up 21%,
• International DAUq rose to 58.0 million, up 41%.

This contrast highlights that Reddit’s fastest user growth is occurring outside the U.S., signaling expanding global reach and rising visibility in international markets. This trend may indicate growing discovery opportunities through non-U.S. referral sources and increased relevance in regions where Reddit has historically had lower reach.

Logged-in Daily Active Uniques

Logged-in users can comment, moderate, start discussions, and vote. A bottom line significance is that being logged-in allows for better behavioral tracking and a higher ad targeting value. Thus, logged-in users are an important metric of the viability of the Reddit community.

Logged-in Daily Active Uniques (DAUq) were up in both the U.S. and internationally, with international growth outpacing the U.S. on a year-over-year basis:

• Logged-in U.S. DAUq: 23.0 million (up 19% year-over-year)
• Logged-in International DAUq: 25.8 million (up 27% year-over-year)

Logged-Out Daily Active Uniques (DAUq)

The rise in overall Daily Active Uniques (DAUq) extended to logged-out users, with that segment experiencing strong year-over-year growth. This suggests that Reddit continues to be a popular destination for reading opinions and reviews from real people. It may also suggest that search engines and social media are sending more visitors to Reddit, as those users are more likely to arrive via external referrals, although the quarterly report did not mention search traffic or referral sources.

Logged-out users increased in both the U.S. and internationally, with international growth more than double that of the United States.

• Logged-out U.S. DAUq: 27.1 million (up 22% YoY)
• Logged-out International DAUq: 32.2 million (up 54% YoY)

Revenue and Monetization

Reddit’s total revenue reached $392.4 million, an increase of 61% compared to Q1 2024. Advertising revenue accounted for $358.6 million, also up 61%. Other revenue totaled $33.7 million, a 66% increase year-over-year.

Average Revenue Per Unique (ARPU) also increased:

• U.S. ARPU: $6.27, up 31%
• International ARPU: $1.34, up 22%

These increases in Average Revenue Per Unique (ARPU) suggest that Reddit is improving its monetization of user activity.

It also reported $115.3 million in adjusted EBITDA. EBITDA stands for earnings before interest, taxes, depreciation, and amortization. The adjusted version excludes certain non-recurring or non-cash expenses. This figure is often used to show how profitable a business is from its core operations.

• Net income: $26.2 million
• Adjusted EBITDA: $115.3 million
• Operating cash flow: $127.6 million
• Free Cash Flow: $126.6 million
• Gross margin: 90.5%

Takeaways

Platform Usage Growth

• Total Daily Active Uniques (DAUq) rose 31% year-over-year to 108.1 million.
• Weekly Active Uniques reached 401.3 million globally, also up 31%.
• Growth among international users (41%) outpaced U.S. growth (21%).
• Logged-out users grew faster than logged-in users, especially internationally (+54% YoY).

Logged-In vs. Logged-Out Behavior

• Logged-in users are critical for Reddit’s ad targeting and engagement features.
• Logged-in DAUq rose in both U.S. (+19%) and international (+27%) markets.
• Logged-out DAUq showed steeper growth: +22% U.S. and +54% internationally.
• The rise in logged-out traffic suggests Reddit may be benefiting from increased exposure via search engines and social media, despite the report not directly mentioning search.

Revenue and Monetization

• Total revenue grew 61% YoY to $392.4 million.
• Advertising revenue: $358.6 million, also up 61%.
• Other revenue grew 66% to $33.7 million.

ARPU (Average Revenue Per Unique)

• U.S. ARPU: $6.27 (up 31%)
• International ARPU: $1.34 (up 22%)
• ARPU growth suggests improved monetization per user, especially through ad impressions in international markets.

Profitability and Financial Health

• Net income: $26.2 million
• Adjusted EBITDA: $115.3 million
  (Reflects earnings before interest, taxes, depreciation, and amortization, excluding non-cash or one-time costs)
• Operating cash flow: $127.6 million
• Free Cash Flow: $126.6 million
• Gross margin: 90.5%

Reddit’s Q1 2025 earnings report highlights strong year-over-year growth in both logged-in and logged-out user activity, with usage rising significantly in the U.S. and even higher internationally. The company also reported a 61% increase in total revenue and positive cash flow, showing that Reddit is becoming more effective at monetizing its growing user base, which is useful information for digital marketers.

The report reflects growth in usage, revenue, and Average Revenue Per Unique (ARPU). Reddit’s expanding reach and monetization suggest it remains a relevant platform for users and remains a destination for referral traffic.

Featured Image by Shutterstock/gguy

https://www.searchenginejournal.com/reddit-q1-report-what-it-means-for-digital-marketing-and-seo/545897/

A study found that 33% of Google users continued to use Bing after trying it for two weeks. This challenges the prevailing notion about search engine preferences and Google’s market dominance.

The research, published by the National Bureau of Economic Research, suggests Google’s market share isn’t just because it’s better. Many users haven’t tried alternatives.

The study was initially published in January but flew under our radar at the time. Hat tip to Windows Central for surfacing it again recently.

After reviewing the study, I felt it deserved a closer examination. Here are the findings that stand out.

Google’s Market Power: More Than Just Quality

Researchers from Stanford, MIT, and the University of Pennsylvania tested 2,354 desktop internet users to understand why Google holds about 90% of the global search market.

They looked at several possible reasons for Google’s dominance:

• Better quality
• Wrong ideas about competitors
• Default browser settings
• Hassle of switching
• Users are not paying attention
• Data advantages

While many think Google wins purely on quality, the research shows it’s not that simple.

The researchers challenge these claims with their findings:

“Google, however, maintains that its success is driven by its high quality, that competition is ‘only a click away’ given the ease of switching, and that increasing returns to data are small over the relevant range.”

The “Try Before You Buy” Effect

One key finding stands out: after being paid to use Bing for two weeks, one-third of Google users continued to use Bing even after the payments stopped.

The researchers found:

“64 percent of participants who kept using Bing said it was better than they expected, and 59 percent said they got used to it.”

The study further explains:

“Exposure to Bing increased users’ self-reported perceptions of its quality by 0.6 standard deviations.

This represents “a third of the initial gap between Google and Bing and more than half a standard deviation.”

This suggests people avoid Bing not because it’s worse, but because they haven’t given it a fair shot.

Challenging Common Beliefs

When Google users were asked to choose their search engine (making switching simple), Bing’s share grew by only 1.1 percentage points.

This suggests that default settings affect market share mainly by preventing users from trying alternatives.

The authors state:

“Our results suggest that their perceptions about Bing improved after exposure. Default Change group participants who keep using Bing do so for two reasons. First, like Switch Bonus group participants, their valuation of Bing increases due to experience. Second, some participants may continue to prefer Google but not switch back due to persistent inattention.”

Analysis of Bing’s search data showed that even if Microsoft had access to Google’s search data, it wouldn’t dramatically improve results.

The researchers concluded:

“We estimate that if Bing had access to Google’s data, click-through rates would increase from 23.5 percent to 24.8 percent.”

The EU requires Google to display users with a choice of search engines, but this study suggests that such measures won’t be effective unless users try the alternatives.

The researchers add:

“Driven by the limited effects of our Active Choice intervention, our model predicts that choice screens would increase Bing’s market share by only 1.3 percentage points.”

How They Did the Research

Unlike studies that ask people questions, this one used a browser extension to track real search behavior over time.

The researchers split users into groups:

• A control group that changed nothing
• An “active choice” group that picked their preferred search engine
• A “default change” group paid to switch to Bing for two days
• A “switch bonus” group paid to use Bing for two weeks

They also measured how users’ opinions changed after trying different search engines. Many users rated Bing higher after using it.

What This Means

These findings suggest Google’s advantage comes from exposure, not just from being technically superior.

Current legal cases against Google may not have a significant impact unless they encourage more people to try alternatives.

The researchers conclude:

“Our results suggest that regulators and antitrust authorities can increase market efficiency by considering search engines as experience goods and designing remedies that induce learning.”

This research comes as Google faces legal challenges in both the US and the EU, with courts considering ways to increase competition in the search market.

For search marketers, the study suggests that Google’s position may not be as secure as many think, although competitors still face the challenge of persuading users to give them a try.

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Featured Image: gguy/Shutterstock

https://www.searchenginejournal.com/33-of-google-users-stuck-with-bing-after-a-two-week-trial-study/545878/