Tag: B2B Marketing

Best B2B Digital Marketing Agencies to Watch in 2026

I analyzed more than 80 leading B2B digital marketing agencies for 2026 to identify the firms that stand out most clearly. I evaluated each agency against the criteria that matter most for B2B companies trying to grow visibility, authority, and qualified pipeline.

SEO/GEO Expertise (30%): I looked at each agency’s technical fluency in how large language models surface and rank content, along with its ability to turn that knowledge into durable client visibility.

Notable Clients (25%): I considered the strength of each client roster, since recognized brands often signal an agency’s ability to manage complex campaigns and deliver at an enterprise level.

Leadership Experience Score (20%): I weighed senior experience in strategy and client service, which remains one of the strongest indicators of consistent agency performance.

AI Visibility Score (15%): I used a 1.0-5.0 rating to measure how effectively an agency drives client presence in AI-generated responses across ChatGPT, Perplexity, Claude, and Google Gemini.

Average Review Score (10%): I reviewed aggregated ratings from Google, Clutch, G2, and other verified platforms, using a 1.0-5.0 scale.

Using those standards, I ranked the top 6 B2B digital marketing agencies of 2026. The agencies below stood out for their mix of SEO/GEO strength, client experience, leadership depth, AI visibility, and verified review performance.

The Top B2B Digital Marketing Agencies

1. First Page Sage – SEO/GEO Expertise: 5.0; Notable Clients: SoFi, defi SOLUTIONS, US Bank, NBC, Verizon, Cadence, Skeps; Leadership Experience Score: 4.8; AI Visibility Score: 4.9; Average Review Score: 4.9.

2. Driven Metrics – SEO/GEO Expertise: 4.4; Notable Clients: Tesseract Medical, OSEA Malibu; Leadership Experience Score: 4.3; AI Visibility Score: 4.4; Average Review Score: 4.7.

3. Focus Digital – SEO/GEO Expertise: 4.5; Notable Clients: Revo, Milano Jewelry; Leadership Experience Score: 4.3; AI Visibility Score: 4.2; Average Review Score: 4.8.

4. REQ – SEO/GEO Expertise: 3.8; Notable Clients: Carahsoft; Leadership Experience Score: 4.4; AI Visibility Score: 4.1; Average Review Score: 4.4.

5. AMP Agency – SEO/GEO Expertise: 3.6; Notable Clients: Credit Sesame; Leadership Experience Score: 4.4; AI Visibility Score: 4.2; Average Review Score: 4.5.

6. Viral Nation – SEO/GEO Expertise: 3.5; Notable Clients: Intuit, Citibank, Chime; Leadership Experience Score: 4.0; AI Visibility Score: 3.7; Average Review Score: 4.3.

First Page Sage

I ranked First Page Sage first because of its early and deep role in GEO. President Evan Bailyn pioneered the practice in 2023, and much of the methodology now used across the industry traces back to his team’s work. That head start shows up most clearly in the agency’s SEO/GEO Expertise and AI Visibility scores.

What stands out to me is how First Page Sage combines long-form thought leadership with technical knowledge of how large language models source and surface information. On the SEO side, the agency brings more than 15 years of organic search experience across complex B2B verticals.

On the GEO side, First Page Sage was optimizing for AI citation before most agencies had a name for the concept. I see its biggest strength as a compounding strategy: the same content that ranks in traditional search can also be pulled into AI-generated answers, helping clients earn qualified leads from both channels at the same time.

First Page Sage scores: SEO/GEO Expertise: 5.0; Notable Clients: SoFi, defi SOLUTIONS, US Bank, NBC, Verizon, Cadence, Skeps; Leadership Experience Score: 4.8; AI Visibility Score: 4.9; Average Review Score: 4.9.

Summary of online reviews: Reviewers describe First Page Sage as the true expert in this industry, with content that takes thought leadership to the next level. Clients also report that its campaigns helped them generate marketing qualified leads through organic traffic.

Driven Metrics

I see Driven Metrics as a practical, performance-oriented GEO agency. Its process emphasizes weekly syncs, conversion tracking, and transparent reporting tied to actual leads rather than surface-level traffic numbers. When content underperforms, the team identifies it quickly and reworks it instead of letting weak pages sit untouched.

Driven Metrics builds authoritative content designed to earn rankings through expertise and citation. It also structures that content to appear in AI-generated responses when buyers ask for vendor recommendations. That mix is difficult to find at its price point, though I would expect companies in highly niche verticals to invest early time in helping the team understand how their buyers evaluate vendors.

Driven Metrics scores: SEO/GEO Expertise: 4.4; Notable Clients: Tesseract Medical, OSEA Malibu; Leadership Experience Score: 4.3; AI Visibility Score: 4.4; Average Review Score: 4.7.

Summary of online reviews: Clients say Driven Metrics delivered results with no excuses, which was refreshing, and that its reporting meant they always knew what was going on. The main caveat reviewers mention is more limited experience in certain sectors.

Focus Digital

I ranked Focus Digital highly because of its technical foundation in LLM optimization. The agency appears deeply familiar with the mechanics of generative search, and that shows in how it structures campaigns. Its content is designed from the beginning to earn citations in AI-generated answers, not only to rank in traditional search results.

Focus Digital’s SEO approach follows a thought leadership model, using authoritative long-form content to build organic visibility over time. I see it as one of the more technically grounded options for companies that want both SEO and GEO support without paying large-agency rates. The main limitation is portfolio depth: its case studies skew toward professional services, manufacturing, and home services, so clients in other verticals should plan for hands-on content review to maintain accuracy.

Focus Digital scores: SEO/GEO Expertise: 4.5; Notable Clients: Revo, Milano Jewelry; Leadership Experience Score: 4.3; AI Visibility Score: 4.2; Average Review Score: 4.8.

Summary of online reviews: Clients describe Focus Digital as honest about what is realistic and say the agency helped them show up in AI answers within a few months. The recurring criticism is that replies slow down when they’re busy.

REQ

I view REQ as a strong fit for companies that want B2B communications, authority-building, and digital marketing under one roof. The agency has earned solid reviews from clients across cybersecurity, government technology, financial services, and real estate. Its foundation is PR and authority-building, which overlaps with GEO, but its score here is driven more by SEO than by AI visibility.

REQ’s SEO work is woven into content strategy and demand generation rather than packaged as a standalone service. GEO is still less developed than its broader SEO foundation, so I would not make it my first choice for a company whose main priority is AI citation and generative search visibility. I would, however, consider it a strong option for brands that want integrated authority with organic search performance at the center.

REQ scores: SEO/GEO Expertise: 3.8; Notable Clients: Carahsoft; Leadership Experience Score: 4.4; AI Visibility Score: 4.1; Average Review Score: 4.4.

Summary of online reviews: Reviewers say REQ is highly adaptable and good at picking up the ball and running with it. Clients also report that campaigns resulted in increased traffic and customer engagement. The recurring criticism is that some clients wanted the agency to be more proactive with recommendations.

AMP Agency

I see AMP Agency as a full-service firm with a clear strength in integrated media. The agency is especially good at combining creative, experiential marketing, paid social, and video production into campaigns built around the full customer journey. With offices in Boston, New York, LA, and Seattle, AMP also has the infrastructure to support large, multi-channel engagements.

AMP’s SEO practice is meaningful and has produced measurable results, including improvements in rankings and lead quality. GEO is a newer layer for the agency, as it is for many full-service firms that built their models before generative search became a major traffic source.

For companies that want broad digital coverage with SEO included, AMP can be a strong choice. I would treat its GEO capability as developing rather than core, but its creative depth and campaign scale make it a practical option for brands with broader marketing needs.

AMP Agency scores: SEO/GEO Expertise: 3.6; Notable Clients: Credit Sesame; Leadership Experience Score: 4.4; AI Visibility Score: 4.2; Average Review Score: 4.5.

Summary of online reviews: Clients say AMP Agency’s SEO services resulted in increased sales and better site management and that the team brings new ideas to the table. Reviewers also note that staff operate on time and on budget. The common critique is that its generative search work is still catching up to the broader digital offering.

Viral Nation

I included Viral Nation because it brings a very different kind of visibility strategy to the B2B marketing landscape. It is the largest agency on this list by headcount and the most specialized in social-first marketing. Its model centers on influencer campaigns, creator networks, paid social, and proprietary social intelligence technology deployed at scale.

Viral Nation’s strength is cultural reach and audience trust rather than search authority. That is why its SEO/GEO Expertise score is lower than the more search-focused agencies on this list. For B2B companies seeking influencer-driven brand awareness, I see Viral Nation as a strong match. For companies that need a more comprehensive search and GEO campaign, I would look elsewhere.

Viral Nation scores: SEO/GEO Expertise: 3.5; Notable Clients: Intuit, Citibank, Chime; Leadership Experience Score: 4.0; AI Visibility Score: 3.7; Average Review Score: 4.3.

Summary of online reviews: Reviewers say Viral Nation regularly overperforms and that its campaigns are strong fits for clients seeking new brand exposure in a targeted market. The limitation clients note is that its strength is social as opposed to search, so coverage thins outside influencer and paid channels.

Source

Inspired by this post on First Page Sage Blog.

July 3, 2026
Why B2B Brands Rank But Vanish From AI Overviews

I’m seeing a sharp disconnect in B2B search visibility: many brands still rank for thousands of Google keywords, but they appear in only about 3% of AI-generated answers, according to Walker Sands’ B2B AI Search Visibility Benchmark of 828 enterprise companies. (Disclosure: I’m the director of SEO and GEO at Walker Sands.)

For this benchmark, I looked at more than 45 million search queries from March across 828 enterprise B2B companies in 14 industries. The analysis evaluated each domain across four core metrics: keyword coverage, keywords with AI Overviews, AI Overview incidence, and citation inclusion rate.

Keyword coverage measures how many keywords a company ranks for in Google. Keywords with AI Overviews shows how many of those ranking keywords trigger AI-generated responses. AI Overview incidence captures the percentage of ranking keywords where AI Overviews appear. Citation inclusion rate measures how often a company’s domain is cited inside those AI-generated answers.

Together, these metrics give me a baseline for understanding how often AI Overviews show up and how often B2B brands actually earn visibility within them.

A baseline for B2B AI search visibility

The benchmark shows a meaningful gap between traditional ranking visibility and AI citation visibility. AI Overviews appear in about 50% of search results where enterprise B2B brands rank, yet the median enterprise B2B brand is cited in just 3% of relevant AI Overviews.

I also found that 4.6% of enterprise B2B companies are not cited in AI Overviews for any of their relevant keywords. That may sound like a small share of the market, but it points to a serious visibility problem for brands that still appear in Google’s organic results while disappearing from the AI-generated answers buyers increasingly see first.

The typical enterprise B2B company ranks organically for about 9,700 search queries, and AI Overviews appear in nearly half of those searches. But across all those opportunities, the median brand earns citations in only 3% of AI Overviews.

In other words, I’m seeing B2B brands present in the search results that AI Overviews summarize, but largely absent from the summaries themselves.

When a brand has few or no citations, I often see deeper issues underneath: limited topical authority, unstructured or inaccessible content, and too little content that directly answers the questions buyers are asking.

Addressing those gaps is becoming essential for visibility in AI-driven search experiences.

The narrowing funnel from ranking to citation

I think of AI search performance as a funnel with four layers, and the value lost at each step is where the story gets clearer.

It starts with keyword coverage, or the number of keywords where a brand ranks in Google’s top 100 organic results. On that measure, many leaders still look strong. The median company ranks for about 9,700 keywords, while top-quartile brands rank for more than 37,000.

The next layer is keywords with AI Overviews. These are ranking keywords that trigger an AI Overview. The median company has roughly 4,500 of them, which is already less than half of its ranking footprint.

The third layer is AI Overview incidence, which measures how often AI-generated answers appear across a brand’s relevant searches. The median is 48.8%, meaning AI now intercepts roughly half the queries where these companies compete. Top-quartile brands operate in even more AI-heavy environments, with an incidence rate of 61.7%.

The final layer is the one that matters most, and it is where almost everyone loses ground: citation inclusion rate. This measures how often a brand is cited as a source within an AI Overview. The median is 3.0%. Even the top quartile reaches only 4.5%, while the bottom quartile sits at 1.7%.

Viewed from top to bottom, the funnel is unforgiving. Tens of thousands of ranking keywords compress into a single-digit share of AI citations. Much of the visibility B2B brands have built through organic search does not carry into the layer of search that is shaping buyers’ first impressions of a category.

Ranking breadth does not guarantee AI citations

The most important takeaway is also the most counterintuitive: ranking breadth alone does not predict AI citation rates.

I found that some companies rank for thousands of keywords but rarely surface in AI-generated answers. The strengths that helped brands win traditional SERP visibility, including page volume, broad keyword targeting, and years of accumulated domain authority, do not automatically make a brand the source an AI system chooses to cite.

That creates a real challenge for B2B SEO teams. If a dashboard only tracks ranking keywords and estimated organic traffic, it may tell a flattering story about a layer of search that is losing influence while saying little about the AI layer that is gaining it.

The brands that are consistently cited in AI-generated answers tend to share three traits: deep topical authority across related content areas, clear and structured explanations that directly answer buyer questions, and consistent coverage across multiple relevant pages.

The common thread is specificity. Generative systems appear to reward content that resolves a buyer’s question clearly and demonstrates sustained expertise on a topic, instead of content that simply ranks for a query.

That changes the work. Optimizing for AI citations looks less like chasing keyword volume and more like building genuine, well-structured subject-matter depth.

Some industries are far more exposed than others

AI search visibility is not distributed evenly across B2B technology. The industry breakdown shows very different competitive dynamics depending on the category.

Cybersecurity leads on both fronts. AI Overviews appear in a median of 59.9% of cybersecurity-related searches, and cybersecurity brands earn the highest median citation rate in the study at 4.2%. Enterprise software, with 55.3% AI Overview incidence, and martech, with 56.3%, also see AI-generated answers in well over half of relevant queries.

At the other end, professional services and distribution and logistics trail in citations, both with a median rate of just 2.1%. Distribution and logistics also has the lowest AI Overview incidence at 29.6%, meaning buyers in that category encounter AI-generated summaries far less often than buyers in cybersecurity.

These differences create both risks and opportunities. In categories where AI-generated answers are already common, such as cybersecurity, the cost of being invisible is immediate. Buyers are forming impressions inside AI summaries right now.

In categories where citation rates are low and few brands have figured out the new mechanics, I see a real first-mover opportunity. Brands that learn how to earn citations before competitors do can help shape how an entire category is framed in AI-generated answers, much like early SEO adopters captured outsized organic visibility.

The brands that have gone completely dark

The most striking number in the report is that 4.6% of enterprise B2B companies are not cited at all in AI-generated answers for their relevant keywords.

These are not small, unknown operations. They are companies with $100 million or more in revenue that, in many cases, still rank well in traditional search. They are present in the index but absent from the answer.

Near-zero citation rates usually point to deeper structural issues: thin topical authority, content that is difficult for systems to parse, and a lack of material that directly answers the questions buyers are asking.

For a small but meaningful slice of the market, AI search is not just a place where they are losing share. It is a place where they barely exist.

What this means for B2B search teams

The benchmark gives me a baseline, but the strategic implications for SEO, GEO, and marketing teams are already clear.

First, measurement has to evolve. Citation inclusion rate is now a distinct KPI from ranking. Teams that cannot see whether their content is being cited in AI-generated answers are missing visibility into one of the fastest-growing parts of the funnel. Knowing your own citation rate, and comparing it with the 3% median and 4.5% top-quartile benchmarks, is a practical starting point.

Second, the content mandate is shifting from breadth to depth. The drivers point toward consolidating authority around the topics buyers care about, structuring content so machines can interpret it, and answering real questions directly instead of producing content volume for its own sake.

Third, the window is open but closing. Generative AI is expected to influence more than 75% of B2B search queries within the next one to two years. If that projection is even close, the median 3% citation rate is not a stable endpoint. It is a snapshot of an early, contested market that rewards brands that move now.

The uncomfortable truth is that much of the SEO equity B2B brands have built is being summarized by AI systems that do not cite the companies that created it. For most enterprise brands, I no longer see the central question as whether they rank. The question is whether they are in the answer at all.

The full H1 2026 B2B AI Search Visibility Benchmark is available from Walker Sands.

Inspired by this post on Search Engine Land.

July 3, 2026
LinkedIn Ads CPC Benchmarks: What I Budget vs Google
I know LinkedIn Ads has a reputation for being expensive, and at first glance, the data backs that up. Across the client accounts I analyzed, LinkedIn’s average CPC was $11.12, compared with $5.45 on Google Ads.

But that simple comparison misses the more useful story. When I compare the cost of reaching new, high-intent B2B buyers, the gap gets much smaller. Non-branded Google Search campaigns averaged a $12.48 CPC, while comparable LinkedIn prospecting campaigns averaged $13.94.

To understand how LinkedIn CPCs really compare with Google Ads across campaign types and industries, I reviewed more than $700,000 in LinkedIn ad spend and compared it with CPC data from the same accounts on Google Ads.

What I included in this analysis

I focused on CPC and performance data from clients that had active campaigns on both LinkedIn Ads and Google Ads over the past year.

The main questions I wanted to answer were straightforward: What CPCs are we actually seeing? Do CPCs change by ad objective and industry? And how do those costs compare with Google Ads?

For LinkedIn Ads, I analyzed more than $700,000 in spend across 63,000+ clicks and 8.1 million impressions.

The clients fell into two main business categories: B2B SaaS, which represented approximately 97% of spend, and professional services.

I looked at LinkedIn CPCs by ad set objective and business category. For Google Ads, I pulled CPC data from the same client accounts across branded search, non-branded search, Demand Gen, and display campaigns.

Client names are withheld. The date range for this analysis was May 2025 through May 2026.

LinkedIn looks more expensive, but the comparison needs context

LinkedIn’s blended average CPC across all objectives was $11.12. Google’s blended average CPC across all campaign types was $5.45. On the surface, LinkedIn costs about twice as much per click.

There is an important caveat. In Google Ads, a large share of those lower-cost clicks came from display campaigns, which averaged $0.89 per click, and branded search, which averaged $1.71 per click. Both are naturally less expensive because display generally reaches lower-intent audiences, while branded search captures people already looking for your company.

When I narrow the comparison to the cost of reaching new, high-intent audiences, the difference becomes much less dramatic.
- Google Ads non-branded search averaged a $12.48 CPC across the clients in this study.
- LinkedIn prospecting campaigns, excluding retargeting and using lead generation, website conversion, or website visit objectives, averaged a $13.94 CPC.
I used those LinkedIn objectives because they most closely represent high-intent direct-response campaigns, which makes the comparison with non-branded search more useful.

When I compare the cost of reaching a new audience, LinkedIn is still more expensive, but it is not twice as expensive. In practical terms, I am looking at roughly $12 CPCs on Google and $14 CPCs on LinkedIn.

LinkedIn CPCs change a lot by objective

One of the clearest findings in this data set is how widely LinkedIn CPCs vary by campaign objective.
- Website visits: $6.75
- Brand awareness: $8.34
- Website conversions: $4.84
- Engagement: $4.45
- Lead generation: $31.29
- Video views: $71.43
Lead generation campaigns, where LinkedIn lead gen forms capture contact information directly inside the platform, cost nearly five times more per click than website visit campaigns.

That higher CPC can still make sense because these campaigns often convert at much higher rates than ads that send people to a website or landing page.

Here is the full breakdown of CPCs by campaign objective:

The number that jumps out most is video views. CPCs for those campaigns look extremely high, but cost per view is the more relevant metric there, so CPC alone can be misleading.

If I were planning a LinkedIn campaign focused on click volume or site traffic, I would budget for CPCs in the $6-$8 range. For lead gen ads, which in my experience often produce stronger conversion rates and better lead quality, I would plan for $30+ CPCs.

LinkedIn CPCs also change by industry

The two business categories in this analysis showed noticeably different CPC profiles on LinkedIn.
- B2B SaaS: $11.02 average CPC on $681,000 in spend
- Professional services: $15.25 average CPC on $23,000 in spend
I would be careful not to overstate that comparison because the spend levels were very different. B2B SaaS had a much broader mix of campaign types, which likely affected the average CPC. The professional services campaigns also used very specific targeting, which may have pushed CPCs higher.

B2B SaaS CPCs by campaign objective:

Professional services CPCs by campaign objective:

One interesting twist is that lead gen CPCs in professional services were lower than website visit CPCs. Lead gen CPCs were also much lower for professional services than they were for B2B SaaS.

If I were budgeting for a professional services firm on LinkedIn, I would factor in $15-$20 CPCs. For B2B SaaS, I would plan for a wider range, roughly $7-$35, depending on the campaign objective.

How this compares with Google Ads

The pattern is fairly consistent across channels. Professional services had higher CPCs than B2B SaaS in this data set. Even when I compare only non-branded search between the two industries, the CPCs are closer, but professional services still comes out higher.

Here is the breakdown of Google CPCs by campaign type:

What I would budget for LinkedIn Ads

Your targeting will have a major impact on CPCs and budget needs, but I use this data as a practical planning framework.

Minimum viable budget: $3,000-$5,000 per month

Below this level, I would not expect enough traffic to drive meaningful lead volume or conversions. You may still be able to get started, but trend-spotting will be slow, and you will probably be limited to one or two campaigns.

Testing and learning: $5,000-$10,000 per month

At this level, I would expect enough budget to run two or three objectives, launch more campaigns, test creative and audiences, and generate more meaningful lead volume.

Scaling: $10,000+ per month

With this budget, I can run always-on brand awareness and thought leadership campaigns alongside lead gen and website visit campaigns. I can also support event registrations, test more advanced list-targeted campaigns, and use retargeting without starving direct-response efforts.

For B2B SaaS or professional services companies with an ACV above $20,000, I would rarely recommend starting LinkedIn with less than $5,000 per month. A single closed deal worth $30,000-$50,000 in ACV can justify meaningful investment, even at a $500+ CPL, as long as the pipeline quality is there.

The B2B channel mix I recommend

For most B2B clients, I do not see LinkedIn and Google as either-or channels. I use them for different jobs.

Use Google Ads and Microsoft Ads for intent capture

Non-branded search reaches buyers who are actively researching. Branded search and remarketing are lower-cost and essential. If someone is searching for your category keywords, I want your brand to be visible.

I also use Demand Gen and Performance Max where they make sense to fill gaps and support brand awareness.

Use LinkedIn Ads for audience-led demand generation

If the ideal customer profile is highly specific, such as VP-level decision-makers at mid-market SaaS companies, LinkedIn’s targeting is hard to replace. No other platform gives me the same ability to reach that kind of professional audience at scale.

Run both channels in parallel

The strongest setup is to run both channels together. Google captures existing demand. LinkedIn helps create new demand and keeps the brand visible to the exact buyers I want in the pipeline.

Why I still think LinkedIn is worth the higher CPCs

LinkedIn is more expensive than Google on a raw CPC basis. But when I compare the platforms more fairly, with both reaching cold, qualified B2B buyers, the gap narrows significantly.

Higher CPCs can still be worth paying if they put the brand in front of the right customers earlier in the decision-making process. Over time, that can be more valuable than relying only on high-intent keywords after buyers have already narrowed their list of options.

The best scenario is for the brand to become an active part of the buyer’s decision, shaping the narrative before competitors do it instead.

My take is simple: I use LinkedIn Ads to build intent and tell the story, and I use Google Ads and Microsoft Ads to capture intent. The right budget depends on targeting, but I want enough spend to generate at least 100 clicks per month. Anything less usually means spending money without giving the system enough data to learn from.

Inspired by this post on Search Engine Land.
July 3, 2026
How Google AI Prefers Competitors in ‘Best’ Listicles

Recently, I’ve been delving into an intriguing study by Lily Ray, which reveals some unexpected findings about Google’s AI Overviews. Apparently, these Overviews frequently reference brands’ own listicles but tend to recommend their competitors.
The study highlighted that Google AI Overviews cited these self-promotional listicles in a whopping 69% of B2B software-related queries. Yet, they favored rival brands in their recommendations. This got me thinking about the strategies brands employ to influence AI search outcomes.
Detailed Findings. I discovered that the analysis was quite comprehensive. Ray reviewed 100 B2B queries spanning categories like “best [category] software.” She gathered data across three specific periods: April 15, May 15, and June 8.
The study found that out of 80 queries that triggered an AI Overview, self-serving listicles were referenced 323 times, yet in 224 instances, Google didn’t actually recommend those brands. This mismatch intrigued me.
Analysis of Recommendations. While examining specific cases, it became evident that Google sometimes cited a brand’s listicle but opted to recommend more renowned competitors instead. For instance, in the search for “best LMS for selling courses,” Oasis LMS was mentioned, yet Kajabi and others were pushed forward as the preferred options.
This pattern wasn’t just isolated to LMS software; it appeared in multiple domains like help desk tools, task management, and more. It made me ponder over the dominance of stronger brands in recommendations.
Observing Organic Declines. An interesting trend noted was a drop in organic visibility for websites heavily leaning on self-promotional listicles. I noticed beginnings of these declines back in January and observed further drops post-Google’s May 2026 core update.
Interestingly, these sites also seemed to have expanded into AI-generated content and other “best” pages prominently featuring their own brands.
Rise of Third-party Citations. Ray’s analysis also showed an upsurge in Google comprising third-party content for “best” queries. Platforms like Reddit, Forbes, and YouTube gained traction in citations.
Understanding Impact. I believe it’s crucial to realize that merely having your content cited doesn’t equate to a recommendation. This situation offers competitors the chance to snag attention and, ultimately, valuable visibility.
Keeping Up with Changes. Previously, Search Engine Land shared insights on how some SaaS and B2B businesses witnessed visibility losses after banking on self-ranked “best” lists. The risks are significant when company-driven content doesn’t transparently disclose material relationships as mandated by the FTC’s Consumer Review Rule.
About Ray’s Data. To reach her conclusions, Ray employed Ahrefs Brand Radar to examine numerous AI Overview responses. Her analysis spanned 100 B2B software queries, focusing on citations versus actual recommendations.
The full report is available on Ray’s Substack, titled Why Calling Yourself the Best Could Be Helping Your Competitors Win in AI Search.

Inspired by this post on Search Engine Land.

June 18, 2026
Enhance Your B2B Ads: Microsoft Adds LinkedIn Job Seniority Targeting
I recently discovered some exciting news from Microsoft Ads that could be a game-changer for advertisers like myself. They’ve expanded their LinkedIn targeting capabilities to include job seniority filters. This allows me to target audiences with more precision in both Search and Audience campaigns.

This new feature means that I can now target users based on their job seniority, a wonderful addition for those of us focusing on B2B marketing. Thanks to LinkedIn data, I can reach audiences at various levels of seniority.

What’s the scoop? According to Navah Hopkins, Microsoft Advertising has added job seniority targeting to its LinkedIn Profile targeting, allowing me to utilize it within Search and Audience campaigns.

This update provides me the ability to choose from 10 different seniority levels, ranging from CXO to Volunteer. This flexibility is available at both the campaign and ad group levels, making it easier to segment my audiences effectively.

Why is this vital for us? In the world of B2B marketing, it’s often challenging to separate decision-makers from operational staff in search campaigns. With this new job seniority targeting, I can better align my messaging and bidding strategies with the right audience segments, ultimately improving my campaign performance.

Understanding who is interacting with my ads is crucial, especially in organizations with long sales cycles or multiple stakeholders. It’s not just about conversions; it’s about knowing who is behind them.

A closer look: Unlike other platforms, Microsoft’s integration with LinkedIn provides a unique perspective of professional identity that allows me to better understand user interactions.

Not only can I apply these filters directly within my campaign settings, but I can also utilize them in observation mode to gather insights without limiting my reach.

How do I benefit?

Customize messaging by seniority: I can create targeted ad groups for different audience levels, like executives or individual contributors, tailoring my messaging to each group’s expectations.

An executive-focused strategy might highlight business growth, while campaigns targeting practitioners could focus on efficiency gains.

Analyze conversions by seniority: Observation mode helps me assess conversion performance across different seniority levels, answering questions crucial to my strategy:

Where are my conversions coming from? Are they decision-makers or influencers? Is my budget effectively spent? Which seniority levels bring in high-quality leads?

Enhance audience testing: This feature offers an extra layer of reporting, helping me make informed optimization and expansion decisions. If I’m importing from other platforms, this insight is invaluable for discovering performance patterns unique to Microsoft Ads.

Availability: This powerful tool is now accessible in select markets across the Americas, EMEA, and APAC regions, including countries like the United States, Canada, Brazil, and more.
- Americas: Argentina, Brazil, Canada, Chile, Colombia, and others.
- EMEA: Egypt, Nigeria, Saudi Arabia, and South Africa.
- APAC: Australia, India, Japan, among others.
The takeaway: Microsoft Ads continues to leverage its LinkedIn integration as a standout feature in B2B advertising. By aligning search intent with professional profiles, I gain deeper insights into not just what my audiences search for, but who the searchers are.

Inspired by this post on Search Engine Land.
June 16, 2026

Unlocking SaaS Success: 2026 Freemium Conversion Insights

Last updated: June 12, 2026

As I dive into the data we’ve amassed from over 80 SaaS clients between 2022 and 2026, this report paints a vivid picture of freemium model effectiveness. Together, we’ll explore industry averages, see how visitors transition to becoming free users, and how these free users convert to paid customers. I’ll also guide you through the nuances of various freemium offerings compared to free trial success rates.

I’m excited to share our findings with you:

Freemium Conversion Rates by SaaS Industry

Industry	Visitor to Freemium	Freemium to Paid
Advertising/AdTech	14.1%	3.8%
Agriculture/AgTech	12.0%	4.6%
Communications	12.4%	3.8%
CRM	13.1%	3.7%
Cybersecurity	12.2%	3.6%
Education/EdTech	13.9%	2.6%
Enterprise	12.2%	3.8%
ERP	14.0%	5.2%
Financial/Fintech	13.9%	4.1%
Healthcare/MedTech	15.2%	3.9%
HR	12.8%	3.3%
IoT	15.0%	3.6%
Legal/LegalTech	14.2%	6.1%
Real Estate/PropTech	11.7%	2.9%
RegTech	13.7%	5.3%

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SaaS Free Trial vs Freemium Conversion Rates

Freemium Model	Description	Type	Conversion Rate
*Traditional Freemium*	Free-forever software that can function on its own, but has significantly limited features compared to the paid product.	Visitor to Freemium	13.7%
*Traditional Freemium*		Freemium to Paid	3.7%
*Land & Expand*	Software that is free for individuals to acquire, but which requires a paid plan to use at an organization level.	Visitor to Freemium	14.5%
*Land & Expand*		Freemium to Paid	3.0%
*Freeware 2.0*	Free-forever, fully functional product with optional add-ons.	Visitor to Freemium	13.2%
*Freeware 2.0*		Freemium to Paid	3.3%
Free Trial Type	Description	Type	Conversion Rate
*Opt-In Free Trials*	Opt-in free trials have higher visitor to trial conversion rates, as they don’t require visitors to input payment information before downloading.	Visitor to Free Trial	7.8%
*Opt-In Free Trials*		Free Trial to Paid	17.8%
*Opt-Out Free Trials*	Opt-out free trials automatically convert users to paid subscriptions once the trial period ends.	Visitor to Free Trial	2.4%
*Opt-Out Free Trials*		Free Trial to Paid	49.9%

Unlocking AI’s Potential: How Unique Prompt Patterns Boost SEO
I’ve always been fascinated by the evolving nature of SEO, especially in an era dominated by artificial intelligence. For over twenty years, SEO heavily relied on keywords. But with the rise of generative AI and conversational tools like ChatGPT, we’re now seeing a shift toward prompts as the backbone of search visibility.

Understanding the prompts my audience uses with large language models is crucial. Otherwise, my content might never see the light of day in search results. Let’s explore how prompts vary by industry and their impact on search visibility.

How Prompts Differ by Vertical

It’s clear to me that the context holds paramount importance in the responses generated by large language models (LLMs). Different industries have specific patterns that dictate how users construct their prompts. I need to tailor my content to these unique frameworks to ensure maximum relevance.

Healthcare: Symptom-driven and Cautious Language
- In the healthcare sector, I’ve observed users leveraging AI as an initial triage tool. Instead of a vague term like “chronic fatigue,” detailed prompts narrate specific symptoms.
- The prompt pattern: These healthcare prompts are rich in personal context, symptom mapping, and cautious constraints. Questions often revolve around symptom lists and safety considerations linked to age or medication.
- Anatomy of a healthcare prompt: Consider a prompt like: “I’m a 45-year-old female experiencing sudden joint pain and a rash after starting [Medication X]. What side effects should I monitor, and when is it critical to seek medical help?”
- The content shift: To stand out here, my content cannot simply define medical terms. It must align with a patient’s decision-making process.
- The action: I focus on structured FAQs, clear risk factors, and headers addressing specific symptoms combinations to engage effectively.
B2B: Comparison-heavy and ROI-driven
- In B2B contexts, I see users turning to AI for detailed comparisons and ROI evaluations, bypassing traditional marketing materials.
- The prompt pattern: B2B prompts are analytical, featuring deep dives into financial justifications. Requests often include data for presentation-ready tables or matrices.
- Anatomy of a B2B prompt: Typical requests might be like: “Compare CRM ‘Brand A’ and ‘Brand B’ for a 500-user company, with implementation timelines and ROI over three years formatted in a table.”
- The content shift: Without transparent, data-rich content, my B2B efforts remain invisible to LLMs.
- The action: I need to publish open comparison pages with hard data, ensuring technical details are structured in an easily extractable format for AI systems.
Ecommerce: Intentional Clusters of ‘Best,’ ‘Cheap,’ and ‘Reviews’

The ecommerce landscape, as I see it, is an interactive shopping experience with AI-driven, personalized recommendations.
- The prompt pattern: Queries often combine quality markers like “best reviewed” with budget constraints like “under $150” within specific contexts.
- Anatomy of an ecommerce prompt: An example might be: “What are the best-reviewed running shoes for overpronators under $150, excluding brands with poor durability?”
- The content shift: Beyond simple keyword targeting, I must infuse my content with the semantic depth necessary for LLM validation.
- The action: I optimize my merchant feeds with conversational attributes, ensure crawlable user reviews, and connect product specs to consumer value.
Why Prompt Structure Impacts Your Search Visibility

Understanding why prompt structures matter is key for me. They shape whether my site appears in LLM responses, based on how a user constructs their inquiry.

The Power of ‘Reasoning Lift’ and Direct Citations

By optimizing for direct citations and structured data, I could boost the visibility of my content by up to 40%, according to research from Princeton and the Allen Institute for AI.

It’s intriguing how more than 80% of links in AI-driven searches come from domains not ranking in traditional top searches. This emphasizes the importance of content quality and structure over legacy backlinks.

Operationalizing Prompt Research

Shifting my focus from keywords to prompts is crucial. I need to revamp my content strategy to align with conversational search trends, ensuring my brand stays visible.
- Stop tracking isolated keywords: Instead, I’ll search for conversational data within search logs and consumer interactions.
- Audit for LLM readability: My content must be easily parseable by AI, underpinned by modern standards and structured data.
- Write for the follow-up: Rather than focusing solely on initial queries, I’ll anticipate and address follow-up questions within the same content.
To stay ahead, aligning my content with AI interaction patterns is non-negotiable.

Inspired by this post on Search Engine Land.
June 12, 2026
Harness LinkedIn for B2B AI Growth: 3 Proven Strategies
I’ve discovered that LinkedIn is more than just a networking platform—it’s a powerhouse for B2B discovery, especially with its growing influence on AI search results.

Recently, LinkedIn has emerged as a prime resource for how B2B buyers use AI to find products and services. By optimizing our LinkedIn profiles and content for AI search, I noticed a significant boost in our brand’s visibility.

Through my work with B2B clients, especially those in high-growth SaaS sectors, I’ve categorized our LinkedIn optimization into three main strategies:
- Optimize earned media.
- Feed LLMs strategic content.
- Invest in post-engagement that strengthens LLM signals.
Here’s my approach to each area and the results you can expect.

1. Optimize Earned Media: Websites and LinkedIn Pages

Keeping our website and LinkedIn pages up to date is crucial. These include our company page and profiles of high-profile employees, like thought leaders who contribute content. This optimization signals to LLMs that we are a credible source of information.

Google’s E-E-A-T principles are parallel to how LLMs evaluate our media. Content published by our brand’s reps can enhance our credibility when it’s well-optimized.

On Websites

Ensure the business address, contact details, and product descriptions on your site are accurate and comprehensive.

On LinkedIn Company Pages

Regularly update the “About” section and services you offer. Reflect industry specifics where applicable to align with LLM prompts.

Consider the profiles of executives and thought leaders as brand extensions. Their active engagement and representation of the company further reinforce our authenticity to LLMs.

2. Feed the LLMs Strategic Content

Long-form content, specifically between 800-1,200 words, has shown to be more beneficial for AEO mentions. On LinkedIn, users anticipate in-depth content in articles and newsletters, making them perfect vehicles for these insights.

While engagement through carousels and videos is valuable, well-crafted written content seems to be highly favored by LLMs.

3. Invest in Building Post Engagement

LinkedIn posts that attract significant engagement—at least 10 quality comments or 60 reactions—are highly regarded by LLMs due to the social proof they offer. This engagement level doesn’t necessarily require a large budget increase.

Boosting company posts and utilizing Thought Leader Ads (TLAs) and follower ads can further bolster engagement and brand reach. Engaging content on employee profiles, particularly those with fewer than 3,000 followers, is seen as more trustworthy.

Empowering employees and forming partnerships with industry experts can amplify your content reach and reinforce your brand authority.

AI Search is Expanding LinkedIn’s Influence in B2B

Every B2B marketer should prioritize AEO in their strategy. The influence of AI search continues to grow, and staying ahead with LinkedIn optimization is key to capturing new opportunities.

Inspired by this post on Search Engine Land.
May 14, 2026
Discover Top B2B SaaS Marketing Channels for 2026 Success

Last updated: May 5, 2026

As I dive into the world of B2B SaaS marketing for 2026, I’ve identified several pivotal channels worth your attention. Based on costs, expected ROI, and how swiftly they generate leads, I’ll guide you through making the best choice. Check out the comparison table below before we delve deeper into each channel’s details.

The Most Effective B2B SaaS Marketing Channels, Compared

The table offers an overview of costs, ROI, and the time needed to see results. Each channel is unique, bringing its own set of opportunities and challenges:

SEO

SEO stands out as a top contender, offering impressive ROI. It not only attracts leads but also nurtures them through your marketing funnel. The enduring benefits of a strategically executed SEO campaign never cease to amaze me, despite the initial slow pace compared to paid channels.

However, the complexity of SEO means investing in a skilled team adept at interpreting search intent and producing high-quality content consistently. Pairing SEO with PPC can alleviate some of the long wait times.

PPC / SEM

As a paid strategy, PPC offers rapid results and is excellent for short-term goals or testing new markets. I’ve observed that its high cost and pay-dependent nature can hinder long-term success, but for quick market insights, it’s invaluable.

LinkedIn Advertising

LinkedIn gives B2B marketers access to a professional audience with precision targeting capabilities. Despite its lower ROI than organic strategies, it remains an essential tool in my marketing arsenal for reaching decision-makers in our industry.

Account-Based Marketing (ABM)

ABM is all about focusing on a select group of valuable prospects. I’ve found it effective in industries where landing a single client can be transformational. The high risks are balanced by substantial rewards if executed correctly.

Email Marketing

Email marketing allows for cost-effective communication, particularly in nurturing leads. By leveraging existing content and maintaining relationships, I’ve managed to keep the engagement alive, even if building a quality email list took time.

Trade Shows

There’s nothing quite like the personal touch trade shows offer. Although costly, they provide a great opportunity to establish connections and gauge interest firsthand. However, standing out amid the competition is always a challenge.

Public Speaking

Public speaking can dramatically enhance both brand recognition and authority. When I engage audiences directly, the warm leads generated are unmatched. Yet, the need for a seasoned speaker and considerable travel expenses are factors to consider.

Webinars

Webinars offer a cost-effective alternative to in-person events, creating connections with prospects remotely. Crafting engaging presentations demands time and a charismatic host, but the trust built through educational content is well worth the effort.

Getting Help With B2B SaaS Marketing

In my experience, combining multiple marketing channels yields the best results. Midsize companies often find managing them daunting, but partnering with an experienced marketing agency can make all the difference. Our team excels in marrying B2B SaaS SEO with thought leadership for outstanding lead generation.

If you’re interested in exploring how we can collaborate, feel free to reach out. Together, we can strategize the best approach for your unique needs.

Inspired by this post on First Page Sage Blog.

May 5, 2026
China’s Search Evolution: Navigating the 2026 SEO Shift
In February 2025, I watched a captivating display as humanoid robots graced the CCTV Chinese New Year stage. Although their steps were shaky, it was still delightful to witness.

A year later, these robots at the Spring Festival Gala had transformed, executing smooth moves, somersaults, and full kung fu routines. This rapid progression felt like a decade’s worth of technological advancement condensed into one year.

The technological leap wasn’t limited to robots. It raised a crucial question for digital marketers targeting the largest web population: How have China’s search trends evolved recently?

A parallel in the Chinese search landscape

We’re seeing early signs of a major shift. AI hasn’t replaced traditional search engines yet. Instead of a single breakthrough, change comes from consistent, subtle advancements.

New language models frequently emerge, each refined for a specific niche. Tech companies in China are increasingly sharing these developments openly, with players like Baidu integrating advanced models like DeepSeek into their platforms.

To understand the current search behaviors in China, we need to grasp the shift from simple link searches to more reasoning-based approaches and adjust our 2026 SEO strategies accordingly.

The great narrative fallacy: Is web search dead in China?

There’s a persistent narrative in marketing circles that traditional search, especially on Baidu, is obsolete — that everything is happening on platforms like WeChat. But how true is this?

The social supremacy argument

Indeed, China’s web is mobile-first and dominated by super-apps. While social media is pivotal, it’s not the sole avenue for B2C brands aiming to thrive amidst such a vast, versatile environment.

For instance, platforms like Xiaohongshu excel in lifestyle research, while Pinduoduo and Douyin are social commerce powerhouses. Meanwhile, WeChat is indispensable for everyday tasks.

The B2B reality check

For B2B sectors, dismissing Baidu is a mistake. Metrics show ongoing engagement and tangible results from Baidu SEO, often outshining Western counterparts in lead quality and conversion rates.

When B2B professionals seek industrial solutions, they prioritize verified websites over endless scrolling on social media apps, indicating an undying need for structured web searches.

Mapping the 2026 landscape: Intent-based specialization

As someone deeply integrated into the Chinese market, I’ve noticed that users select tools based on intent rather than defaulting to search engines. It’s an everyday occurrence here.

While optimizing for Baidu, others in my circle might be using Pinduoduo for deals or Xiaohongshu for travel plans. The right tool for the right task wins their clicks.

1. Traditional web search: The authority tier

Traditional search continues to dominate B2B and high-authority research areas. Baidu, despite narratives of its decline, remains central to mobile and web searches.
- Baidu: Dominates mobile search with a vast user base. Though AI-driven, it remains a key player in web search.
- Microsoft Bing: Offers a professional experience for a tech-focused audience.
- Haosou (360 Search): Known for its security and enterprise-centric approach.
- Sogou: Integrates with WeChat, bridging between app-based and traditional searches.
- Google: Despite restrictions, it’s accessed by tech-savvy users via VPN for global insights.
2. Social discovery: The inspiration tier

Here, search turns into discovery. Users are led by interests rather than predefined keywords, making SEO a matter of being on the right social platforms at the right time.
- WeChat (Weixin): For brand news and internal communications.
- Xiaohongshu (RED): Essential for lifestyle and luxury brand discovery.
- Douyin: Offers visual insights into product utility.
- Kuaishou: Used predominantly in emerging markets for grassroots content.
- Weibo: Ideal for real-time trends and news.
- Bilibili: Focus on long-form video content and niche interests.
3. Ecommerce: The transactional tier

While Westerners often end their buying journeys on Amazon, Chinese users tend to both start and finish on the same platform, whether for variety or efficiency.
- Taobao / Tmall: The prime destination for diverse product offerings.
- JD.com: Favored for electronics and efficient logistics.
- Pinduoduo: A leader in group-buy and value-driven purchases.
- Douyin Mall: Capitalizes on impulse purchases through engaging content.
- Xianyu (Goofish): Supports second-hand markets and niche hobbies.
4. Generative AI (LLMs): The reasoning tier

This emerging layer focuses on “thinking” searches where AI synthesizes data into insights rather than mere lists.
- Doubao (ByteDance): Popular for casual queries.
- DeepSeek (Domestic): Integrated with WeChat for deep logic queries.
- Kimi (Moonshot AI): Specializes in handling lengthy documents.
- Qwen (Alibaba): Plays a crucial role in business and coding tasks.
- Tencent Yuanbao: Focuses on WeChat content.
- Wen Xiaoyan (Baidu): Represents the next stage of Baidu’s AI search capabilities.
5. Hyper-local and logistics: The utility tier

This sector addresses immediate, location-driven demands, prioritizing services that cater to “now” and “near me” needs.
- Meituan / Dianping: Leading platforms for food and leisure services.
- Amap (Gaode) / Baidu Maps: Vital for navigation and local search optimization.
- Ctrip (Trip.com) / Railway 12306: Key for travel and transportation booking.
From mapping to maneuvering: The Baidu specialist’s edge

Optimizing Baidu SEO extends beyond ranking web pages; it’s about mastering search landscape intricacies.

The ‘walled garden’ SERP: A decade of distraction

Focusing solely on Google-style tactics might overlook nuances like Baidu’s ad-heavy SERPs and content positions.
- The ad-heavy layout: Ads can dominate substantial SERP real estate.
- The Baidu monopoly: Prime organic positions often favor Baidu properties.
- The portal giants: High-authority contributors also claim space within results.
Riding the Chinese SERP dragon

In this scenario, relying on long-tail strategies often proves more lucrative than targeting head keywords due to the complex Chinese language and diverse user base.

Whether leveraging platform authority or becoming a trusted contributor, it’s essential to adapt upcoming SEO tactics to sustain visibility.

What is changing in Baidu SEO?

The competition among AI models emphasizes versatility over loyalty, making Baidu SEO a nuanced challenge.

The AI-switching reality

Chinese users frequently shift between AI models, seeking superior intelligence or alternatives when certain models falter. This behavior means SEO must account for broader dynamics.

Brainstorming the wisdom platforms

Understanding the foundational platforms for AI development can greatly boost a brand’s presence in AI-dominated searches.
- Tencent is invested in Sogou: Hence, Sogou Baike becomes integral for WeChat-based AI queries.
- Bytedance owns Baike.com: Engaging here helps brands appear in Doubao’s results.
- The neutral giants: Zhihu sits at the intersection of multiple investments, making it a balanced source for varied AI insights.
The new SEO commandment

SEO is now about optimizing for diverse data sources that fuel AI models, across various ecosystems.

In the B2B realm, Baidu remains central. Yet for ecommerce, branching into Alibaba or Doubao ecosystems will expand visibility across key AI systems.

The 2026 China SEO/GEO blueprint: From keywords to semantic saturation

Anticipating a specific SEO guide for AI like DeepSeek or Doubao misses the evolving landscape’s essence. The need is not for singular-model focus but a diversified approach that shifts with frequently changing user and model preferences.

Optimize for citations and not just clicks

Chinese SEO centers around fact density, aiming for content immediately recognizable by AI as authoritative.
- The logic: AIs like Kimi and DeepSeek rank content based on factual reliability.
- The tactic: Use clear, concise, data-backed writing, enabling rapid fact verification by AI.
Build an entity moat across wisdom platforms

Given that AI models distill and share intelligence, maintaining consistent brand representation across various platforms is crucial.
- The goal: Ensure uniformity in brand presentation across Baidu, Sogou, and Baike.com.
- The result: Consensus between AI models establishes your authority.
Leverage information gain

AI in China demonstrates a preference for recent data by about 25% compared to traditional search engines.
- The tactic: Present unique, timely insights to stand out amidst common knowledge.
The era of the entity architect

We’ve moved past the initial robotic steps of 2025. In 2026, China’s search landscape is a dynamic entity, requiring an intricate understanding of intent fragmentation.

Despite the dominance of super-apps, the real revelation lies in this fractured landscape. My personal experiences echo this as my wife seeks deals on Pinduoduo, and my colleagues navigate Bing for professional resources. Meanwhile, AI enthusiasts cycle through LLMs for varied answers.

As a Baidu specialist, my role has evolved from targeting websites to designing robust entities. Building for the source, not just the bots, ensures your brand is consistently recognized and trusted, no matter which AI models deliver the solutions.

Imagine your brand becoming the celebrated go-to source, regardless of the search model. That’s the ultimate goal for today’s SEO specialists.

Inspired by this post on Search Engine Land.
May 5, 2026

Tag: B2B Marketing

What I included in this analysis

LinkedIn looks more expensive, but the comparison needs context

LinkedIn CPCs change a lot by objective

LinkedIn CPCs also change by industry

How this compares with Google Ads

What I would budget for LinkedIn Ads

Minimum viable budget: $3,000-$5,000 per month

Testing and learning: $5,000-$10,000 per month

Scaling: $10,000+ per month

The B2B channel mix I recommend

Use Google Ads and Microsoft Ads for intent capture

Use LinkedIn Ads for audience-led demand generation

Run both channels in parallel

Why I still think LinkedIn is worth the higher CPCs

Freemium Conversion Rates by SaaS Industry

SaaS Free Trial vs Freemium Conversion Rates

Further Reading

How Prompts Differ by Vertical

Healthcare: Symptom-driven and Cautious Language

B2B: Comparison-heavy and ROI-driven

Ecommerce: Intentional Clusters of ‘Best,’ ‘Cheap,’ and ‘Reviews’

Why Prompt Structure Impacts Your Search Visibility

The Power of ‘Reasoning Lift’ and Direct Citations

Operationalizing Prompt Research

1. Optimize Earned Media: Websites and LinkedIn Pages

On Websites

On LinkedIn Company Pages

2. Feed the LLMs Strategic Content

3. Invest in Building Post Engagement

AI Search is Expanding LinkedIn’s Influence in B2B

The Most Effective B2B SaaS Marketing Channels, Compared

SEO

PPC / SEM

LinkedIn Advertising

Account-Based Marketing (ABM)

Email Marketing

Trade Shows

Public Speaking

Webinars

Getting Help With B2B SaaS Marketing

A parallel in the Chinese search landscape

The great narrative fallacy: Is web search dead in China?

The social supremacy argument

The B2B reality check

Mapping the 2026 landscape: Intent-based specialization

1. Traditional web search: The authority tier

2. Social discovery: The inspiration tier

3. Ecommerce: The transactional tier

4. Generative AI (LLMs): The reasoning tier

5. Hyper-local and logistics: The utility tier

From mapping to maneuvering: The Baidu specialist’s edge

The ‘walled garden’ SERP: A decade of distraction

Riding the Chinese SERP dragon

What is changing in Baidu SEO?

The AI-switching reality

Brainstorming the wisdom platforms

The new SEO commandment

The 2026 China SEO/GEO blueprint: From keywords to semantic saturation

Optimize for citations and not just clicks

Build an entity moat across wisdom platforms

Leverage information gain

The era of the entity architect