B2B Marketing Round Up

AI councils over chaos, Claude Skills for ops, founders who post win bigger, AI beats humans, three tiers of AI selling.

Lucas Pawlik @ ZestScout.com — Thu, 23 Oct 2025 05:55:10 GMT

Dear Readers, in today’s edition:

Index

Your “Go Experiment With AI” Memo Is a Waste of Time
AI Search Collapsed the B2B Funnel - Here’s the New Playbook
Claude Skills: Bridging Chatbots to AI Agents
Your Founder’s LinkedIn is a Sales Engine (You’re Just Not Using It)
GPT-4 Beats Professionals in Social Media Engagement
Your B2B Sales Team Is Using AI Wrong
Subscribe now

Your “Go Experiment With AI” Memo Is a Waste of Time

Last time, we talked about AI adoption. I don’t want to leave any stone unturned, so here’s the playbook you actually need.

Telling your team to “go experiment” is a recipe for chaos. Snowflake’s marketing team - where 90% are daily AI users - proves there’s a better way. It’s not about magic; it’s about a brutally effective structure.

First, kill the free-for-all.

Your team doesn’t need permission to play. They need a mandate and a system. Unstructured experimentation creates duplicate efforts and zero shared knowledge. It’s a waste of time and money.

It’s Not Nearly Enough to Tell Everyone to “Go Experiment With AI”
The companies winning with AI share one critical trait: a culture of curiosity combined with executive mandate. It’s not enough to tell everyone to “go experiment with AI” - that creates chaos and duplication.
Snowflake’s approach: identify the naturally curious folks who lean in, formalize them into an AI council (30 people at ~20% time allocation across all marketing functions), and have them test, learn, and share quarterly with the broader organization. But if the CEO doesn’t make AI a top strategic priority, employees won’t treat it as one either. You need both top-down leadership and bottom-up innovation.

Steal Snowflake’s AI Council model.

You don’t need 30 people. You need a process.

Identify the Curious. Find the 1-2 people on your team who are already playing with AI. They’re your vanguard.
Formalize Their Role. Give them an official, 10-20% time allocation to test tools and workflows.
Mandate Them to Share. Their job isn’t just to test, but to document and teach the rest of the team what works. A quarterly demo is mandatory.
Get Executive Buy-in. If leadership doesn’t care, nobody else will. This must be a stated priority.

Focus on task automation, not sci-fi.

The fastest wins aren’t from building custom agents. They’re from eliminating grunt work. Snowflake’s team saw 90% time savings on real-world marketing tasks.

Start here:

Content First Drafts: Video scripts, interview prep, social media copy.
Localization: AI delivers massive efficiency for translating content.
Meeting Prep: Summarizing notes and creating action items.

Here’s the hard part. Every tool must answer one question: Is it making us more money or saving us more money? If the answer isn’t obvious, kill it. “Cool” doesn’t pay the bills.

AI Search Collapsed the B2B Funnel. Here’s the New Playbook.

In our last newsletter, we touched on how AI is rewiring B2B buying habits. A new piece in MarTech crystallizes that shift and provides a clear strategy for what to do now.

The traditional buyer journey is officially obsolete. AI search delivers synthesized answers, not a list of links. The goal is no longer driving traffic - it’s becoming the citable authority that AI platforms quote directly.

The old funnel is gone.

AI collapses awareness, consideration, and decision into a single, conversational query. Instead of clicking through ten blue links, a buyer gets a complete summary of solutions, reviews, and comparisons without ever leaving the results page.

The hard truth? This shift will be brutal for brands that don’t adapt.

Gartner predicts that by 2028, 60% of B2B seller work will take place through conversational interfaces powered by generative AI.

Your new job is to feed the machine. Here’s how:

Optimize for conversation, not keywords. Create content that directly answers the nuanced, long-tail questions your customers ask. Think detailed FAQs and how-to guides.
Weaponize E-E-A-T. Your content must scream Experience, Expertise, Authoritativeness, and Trustworthiness. AI prioritizes verifiable proof, not just well-written fluff.
Structure for machines. Use schema markup and structured data. If an AI can’t easily parse your product features, comparisons, and case studies, your brand is invisible.

The game has changed. Stop chasing clicks and start building an information moat AI has to cite.

Claude Skills: Bridging Chatbots to AI Agents.

Most of us are still wrestling with ChatGPT. We’re fighting for consistency, hoping for a decent output. We aren’t building real AI agents yet.

But what if there’s a bridge between clumsy chats and full automation?

Anthropic’s Claude Skills might be it. This isn’t just another feature. It’s a fundamental shift in how you can automate and scale marketing work without writing a single line of code.

This is your marketing process, codified.

Claude Skills are custom workflows you teach the AI in plain English. They turn your repeated processes into reusable, shareable playbooks that Claude executes on command.

Think bigger than just content generation.

Turn webinar transcripts into a full content package: blog draft, social snippets, and email recap.
Summarize customer research into core messaging pillars.
Generate sales enablement assets that actually match your company’s tone of voice.

Before, this required complex prompting or developer help. Now, any marketer can build it. Rakuten reported that tasks which once took a full day now take about an hour using Claude Skills.

The real problem this solves is consistency at scale.

Anyone can get one great post out of an AI. The challenge is repeating that success across every channel and team member without losing your brand’s intent. Skills fix that gap.

It means your AI assistant can now act like an extension of your marketing operations system instead of a random content generator.

This lets you store and enforce your brand voice, systematize SEO frameworks, and automatically format assets for any platform. You’re no longer just creating, you’re operating.

Build your first Skill in minutes.

The process is brutally simple.

Enable Skill Creator in your Claude settings.
Describe your workflow in plain English.
Answer Claude’s setup questions about inputs, tone, and deliverables.
Activate and test your new repeatable process.

From there, you simply state the goal. Ask it to “Build a campaign landing page,” and Claude can automatically stack multiple skills - brand guidelines, copy frameworks, and SEO optimization - to deliver the final outcome.

Here’s the hard part.

Claude Skills are still new.

Access: You need a Pro, Team, or Enterprise plan.
Quality: Community-built skills vary in accuracy.
Security: The sandboxing is still improving.

These aren’t dealbreakers. They are the early tradeoffs for a system that turns your AI from a creative assistant into a marketing operations engine.

Your Founder’s LinkedIn is a Sales Engine (You’re Just Not Using It)

Most founders treat LinkedIn like a press release feed. It’s a monumental waste. The data is clear: startups whose founders post consistently see 33% more leads and up to 3.7x higher deal sizes.

Your founder’s voice isn’t a vanity project - it’s a pipeline driver. Stop broadcasting and start building relationships.

Lead with perspective, not product. Nobody cares about your features. The less you talk about your product, the more people want to buy it. People buy from people they trust, and trust is built with stories.

“First, [people] listen to you, they feel like they’re deeply connected, they love the ideas you put out, they trust you, and then they have to check out what you do.”

Use three story types:

Customer Priority: Show you understand the market, don’t just sell to it.
Transformational Shift: Help people navigate industry change.
Personal Journey: Build credibility through vulnerability. Share mistakes.

Turn daily interactions into content gold. Your calendar is a content buffet. Every customer call is a potential post.

After each call, ask yourself:

What surprised me? (That’s your contrarian take.)
What bothered me? (That’s your polarizing hook.)
What lesson would save others pain? (That’s your high-resonance post.)

Pack a punch with every post. Your hook is everything. If it doesn’t stop the scroll, you’ve already lost.

And forget brevity. LinkedIn data shows posts between 400-800 words generate nearly 3x more engagement. Go deep. Solve a real problem. Your audience will thank you for it.

GPT-4 Beats Professionals in Social Media Engagement

Think your social media team is top-tier? A new three-part study shows GPT-4 consistently generates more engaging content than both original corporate posts and those rewritten by incentivized professionals. The secret is a new linguistic framework.

Here’s the playbook AI is using.

Introducing the FIIT Model: Researchers analyzed GPT-4’s optimized posts from Fortune 500 companies to derive the FIIT (Fluency-Interactivity-Information-Tone) model. This is the set of linguistic principles behind high-engagement content.
AI Superiority is Consistent: In controlled tests, AI-generated posts outperformed not just the original corporate tweets but also versions rewritten by paid, trained human professionals.
It’s Not Just Bad Human Content: The study confirms this isn’t simply because corporate accounts are poorly managed. Even when professionals were tasked with improving posts, GPT-4’s output still proved more effective at driving engagement.

Your B2B Sales Team Is Using AI Wrong

Everyone is talking about AI in sales. Most are using it for tactical wins - drafting emails, summarizing calls. That’s a failure of imagination.

The real shift isn’t about giving your reps a new tool. It’s about building them a new team of autonomous AI agents that fundamentally re-engineers how you sell.

The gap between vision and reality is a chasm.

A recent BCG survey found that while seven in ten sellers use general-purpose AI, the impact is weak. Why? Because the approach is broken.

More than four out of five sellers cite inaccuracy and poor data integration as major roadblocks. They’re spending time double-checking AI output, which kills the efficiency gains. This is what happens when you treat a strategic weapon like a tactical gadget.

Stop thinking in tools. Start thinking in tiers.

The future of B2B sales operates on three levels of AI integration. Each level hands off more complexity, freeing up humans for high-value work.

Augmented Selling: AI provides the script. It recommends talking points, collateral, and the next-best action.
Assisted Selling: AI becomes a real-time partner. It listens to calls, offers prompts, and drafts follow-ups while the seller focuses on the customer.
Autonomous Selling: AI runs the show. It prioritizes leads, nurtures accounts, and handles standard tasks across every channel, from email to video.

For massive strategic accounts, humans stay in control with AI assistance. But for smaller, transactional sales, autonomous agents can manage outreach at a scale no human team could profitably achieve.

The breakdown of successes and challenges in our survey validated BCG’s 10/20/70 rule: 10% of a company’s efforts should be focused on algorithms, 20% on technology and data, and the remaining 70% on people and processes, which produce most of the value of an AI transformation.

Here is your five-step execution plan.

This isn’t a pilot program. It’s a full-scale transformation.

Define a bold North Star. Move beyond vague efficiency goals. Target concrete KPIs like conversion rates and territory coverage.
Chart a purposeful course. Don’t just buy more tools. Sequence the deployment of high-impact use cases to build momentum and trust.
Build an integrated tech stack. Fragmented data is the enemy. Enforce data quality and make deliberate choices on platforms versus custom builds.
Strengthen AI governance. Establish clear guardrails for what agents can and cannot do. Unify data standards and build feedback loops.
Drive adoption relentlessly. Get top-down buy-in. Redesign roles, align incentives, and upskill your talent. The technology is only 10% of the battle.

Rethink, Rebuild, Reprice: The New B2B AI Stack

Lucas Pawlik @ ZestScout.com — Thu, 09 Oct 2025 07:10:17 GMT

Dear Readers, in today’s edition:

OpenAI Enters SaaS — Quietly but Decisively
Your B2B SaaS Funnel Is Obsolete
Your Brand Voice Is Probably Slop. Here’s the Fix.
Why Admitting Your Flaws Is a Marketing Superpower
Stop Chasing Keywords. Start Building a Knowledge Graph
AI Research Isn’t a Shortcut. It’s a Trap.
Subscribe now

OpenAI Enters SaaS — Quietly but Decisively

Last week, attention was on e-commerce features inside ChatGPT. Then came another wave: Apps SDK and Agent Kit. But almost unnoticed between these headlines was the most strategic move yet- OpenAI’s direct step into software applications targeting the marketing and sales stack.

On October 1, 2025, HubSpot (NYSE:HUBS) fell 7.2 %, joined by declines across the SaaS sector - Klaviyo - 12 %, Braze - 11 %, DocuSign - 12 %. Investors reacted to a simple fact: OpenAI, long seen as an infrastructure provider, is now competing in their category.

From Infrastructure to Applications

Until recently, OpenAI sold the tools others built on. Now, it is releasing its own. The first two are already operational inside the company:

Inbound Sales Assistant – an agent trained on OpenAI’s internal knowledge base that answers tens of thousands of inbound messages each month. After a few training loops with sales reps, accuracy improved from 60 % to 98 %, unlocking millions of dollars in annual recurring revenue.
GTM Assistant – a Slack-based copilot that generates briefs and Salesforce summaries ahead of meetings. Early internal data shows around 20 % productivity gains in sales teams.

For now, both remain internal proofs of concept, but they reveal the direction clearly: AI-native SaaS built on OpenAI’s own platform - sales, marketing, support, analytics.

Market Repricing

The October sell-off wasn’t about quarterly results; it was a repricing of competitive dynamics.
For years, SaaS companies sold the interface to business data. Now OpenAI is positioning itself as the intelligence layer that operates directly on top of it.

The company’s roadmap points to applications spanning:

Front office – CRM, inbound marketing, support
Middle office – analytics and pipeline management
Back office – finance and internal reporting

What’s emerging is a full-stack platform built around agents, not traditional users.

Four Pillars of the Strategy

1️⃣ SaaS Tools (The Bait)
Products like GTM Assistant and Sales Assistant demonstrate what “AI-native” can look like in practice. They serve as internal case studies ahead of wider release—proof that OpenAI can deliver finished software, not just APIs.

2️⃣ Apps SDK (The Ecosystem)
Embedding third-party apps inside ChatGPT positions it as a daily workspace. If CRM and analytics functions move inside that environment, the platform effectively becomes the operating system for digital work.

3️⃣ Agent Kit (The Engine)
A developer framework for building and managing custom agents. It lowers the barrier for enterprises to create in-house assistants while keeping them tied to OpenAI’s model infrastructure.

4️⃣ Commerce Layer (The Monetization Stack)
By facilitating transactions triggered by those agents, OpenAI can participate in downstream value creation rather than charging only for usage.

Together, these pillars form a blueprint for an AI-native enterprise layer that could sit above today’s software vendors.

A Structural Shift

OpenAI’s expansion represents more than product diversification; it marks the beginning of AI entering the application layer directly.
Each major technology wave has followed this pattern: infrastructure players climb the stack once the base matures. Amazon extended cloud infrastructure into retail operations, Microsoft evolved from operating systems to productivity clouds. OpenAI’s ascent follows the same logic—but on AI’s compressed timeline.

Its “AI Sales Agent,” quietly deployed as early as February 2025, suggests the company has been preparing this transition for months before public disclosure.

The Interface Becomes the Product

For two decades, SaaS competed for screen space inside browsers. Now the interface itself is changing. ChatGPT- with its SDKs and agent frameworks- may become the gateway through which most knowledge work begins.

In that world, competitive advantage shifts from owning the database to owning the dialogue. The decisive question isn’t which CRM users open first, but which assistant they talk to first.

Early, but Telling

This is still a proof-of-concept stage, not a new market equilibrium. Yet it points clearly to where momentum is moving: from individual SaaS products toward integrated, conversational systems that coordinate entire workflows.

The next frontier of enterprise software may be built inside the model, not around it.

Your B2B SaaS Funnel Is Obsolete. From Linear Stories to Compounding Loops

Why classic funnels break in B2B SaaS

The AIDA model—Awareness, Interest, Desire, Action—was built for straightforward, one-decision sales. SaaS doesn’t work that way.

“Buying SaaS isn’t a straight line—it’s a committee sport.”

The process is long, political, and cyclical: users feel pain, managers justify spend, executives sign. In this environment, AIDA’s neat progression collapses. The moment of purchase isn’t the end—it’s the midpoint. SaaS revenue is earned in usage, not checkout. The funnel must reflect that.

When AARRR isn’t enough

The Pirate Funnel (AARRR—Acquisition, Activation, Retention, Revenue, Referral) was meant to fix AIDA’s limitations by adding post-sale loops. It’s useful for metrics and growth experiments but still too linear for B2B SaaS.

“Acquisition” lumps every channel together. “Revenue” appears as a stage, when in practice it’s an outcome. And none of it accounts for multi-role buying committees or the long tail of customer success.

“No single funnel can explain SaaS. But some frameworks help you design it more intentionally.”

Enter the AEICIEA model

Impression Digital proposes a framework that better mirrors how SaaS buying really happens—Awareness, Education, Interest, Consideration, Intent, Evaluation, Action.

Each stage serves a distinct function:

Awareness surfaces the problem before the buyer names it. It’s educational, not promotional.
Education happens before any sales contact—buyers are learning the landscape and defining their terms.
Interest turns curiosity into structured search as teams start comparing approaches.
Consideration brings vendors into view: features, ROI evidence, customer stories.
Intent is when prospects give permission—requesting demos, signing up for trials, or sharing internal approval.
Evaluation digs into security, integration, pricing, and legal.
Action is the contract—but only the beginning of value realization.

“Every SaaS company loves to celebrate the sale, but that’s when your customer starts testing whether you can deliver what you promised.
”

Adding the missing stage: Adoption

The article’s most important addition comes after Action: Adoption. Turning customers into active users and internal advocates is the only true way SaaS compounds.

“In SaaS, the loop isn’t Awareness → Action. It’s Action → Advocacy.”

When Adoption feeds new Awareness and Education, your funnel becomes a flywheel. Customer success becomes marketing fuel.

Designing content that matches buyer intent

A major recommendation: stop mapping content to channels and start mapping it to intent. Instead of asking “What should we post on LinkedIn?”, ask “Which stage are we serving, and who’s the buyer at that moment?”

Awareness: tell stories that make the pain visible—industry data, relatable examples, or macro trends.
Education: teach frameworks and mental models—guides, webinars, or “how this works” explainers.
Interest & Consideration: offer comparisons—benchmark reports, case studies, or ROI breakdowns.
Evaluation: provide reassurance—security documentation, pricing transparency, integration walkthroughs.
Action & Adoption: design seamless onboarding, tutorials, community resources, and product updates that turn first users into advocates.

“Each piece of content should make someone inside your target company look smart in the next meeting.”

That’s the B2B equivalent of emotional appeal.

Measuring what matters

Metrics should follow intent, not hierarchy.

“If a blog post drives returning visits and longer reads, it’s working—even if no demo forms appear.”

Top-of-funnel assets succeed when they build recognition and revisit behavior. Mid-funnel pieces should be judged on engagement and sales-assist overlap, while late-stage content should accelerate deal velocity and improve close rates.

Alignment beats hand-offs

Ownership doesn’t belong to departments—it belongs to stages.

“A funnel isn’t a baton pass—it’s a relay where everyone runs overlapping legs.”

Product marketing informs Education. Customer success contributes to Evaluation. Marketing stays involved after the sale to capture stories of successful adoption. That overlap creates continuity—and credibility.

When to rebuild your funnel

All funnels expire. The signals are familiar: high traffic but few demos, poor MQL-to-SQL conversion, slow deal cycles, or inconsistent attribution.

“Most friction sits in stages your funnel doesn’t name.”

If your data looks broken, it may not be performance—it may be structure. The remedy starts with customer interviews, not landing page redesigns. Ask what content shaped their decisions and where they stalled. The answers often reveal blind spots between your existing stages.

From funnels to systems

“Funnels are useful fictions. What matters is the system you build around them.”

That system includes shared metrics, unified messaging, and a single source of customer insight across marketing, sales, and success. The strongest B2B SaaS teams treat the funnel as choreography—each stage feeding, learning, and improving the next.

The inspiration layer

The mindset shift is simple but profound: marketing isn’t persuasion; it’s acceleration. Every asset should shorten the distance between curiosity and conviction.

“Stop trying to move people through your funnel. Start designing experiences they want to move through.”

In SaaS, growth doesn’t come from pushing harder. It comes from aligning better—one stage, one story, one buyer at a time.

Your Brand Voice Is Probably Slop. Here’s the Fix.

Everyone wants a memorable brand voice. But most companies end up with generic “slop”—personality without a purpose, tone without a thesis.

The problem isn’t your style. It’s your lack of a real point of view.

Think your “human-centric” voice is cutting through the noise? It’s likely just more noise. Most brand voice guides are recipes for slop, focusing on quirky adjectives instead of substance.

Slop is brand voice without a point of view. It’s personality without a purpose. It’s the brand equivalent of a conversation with a person who won’t stop talking about themselves but never actually says anything.

Voice is the vehicle, not the cargo.

The fatal mistake is confusing how you speak with what you say. Your voice is the delivery mechanism. Your Point of View (POV) is the actual message.

Without a strong POV, your voice is an empty vessel. It’s forgettable because it has nothing to anchor to.

Your point of view is what you say. Your voice is how you say it. Most brands get this backwards. They start with voice and never find their point of view.

Here’s the hard part: A real POV is uncomfortable. It means having an opinion and standing against something.

The Anti-Slop Playbook

Ready to stop sounding like everyone else? The fix is a three-step process.

1. Find Your POV First. Before you write a single word, define what you believe. What’s your controversial take on your industry? What hill will you die on? This is your non-negotiable foundation.
2. Build Voice on Top of POV. Once your message is locked, the “how” becomes an amplifier. Your tone exists to serve your POV, not substitute for it.
3. Create a “Slop Filter.” Ruthlessly ban the fluff. Forbid empty adjectives (”passionate,” “innovative”), corporate jargon, and self-congratulatory intros. If it says nothing, cut it.

The goal isn’t to sound different. It’s to have something different to say.

Why Admitting Your Flaws Is a Marketing Superpower

The default marketing playbook is a lie. It tells you to project perfection, hide every weakness, and scream your strengths from the rooftops.

It’s a strategy built on insecurity. And your customers can smell it a mile away.

The most powerful way to build trust isn’t to pretend you’re flawless. It’s to admit you’re not.

This isn’t theory. Look at Volkswagen’s legendary 1960 “Lemon” ad. They found a tiny scratch on a new car and publicly branded it a “lemon,” unfit for sale. The ad openly discussed their obsessive quality control.

The result? It became one of the most famous campaigns in history and cemented the VW Beetle as a symbol of honesty and reliability.

This strategy has a name: the “blemishing effect.” It’s a psychological judo move that uses your audience’s skepticism against them.

When you lead with a minor negative admission, you non-consciously signal to people that you’re honest and trustworthy. As a result, they’re more likely to believe the positive things you say next.

By pointing out a small flaw yourself, you disarm the cynical part of the buyer’s brain. You’ve proven you’re not hiding anything. Now, when you talk about your strengths, they actually listen.

But there are rules.

Here’s the hard part. This isn’t a free pass for a bad product. Self-deprecation is a scalpel, not a wrecking ball. Get it wrong, and you just convince people you suck.

Use this playbook:

1. Your core offering must be strong. The VW Beetle was a fundamentally great car. Self-deprecation only works as a frame for genuine quality.
2. The flaw must be minor. Volkswagen highlighted a cosmetic scratch, not a faulty engine. Listerine admitted its taste was bad, not that it failed to kill germs.
3. The timing must be right. Reveal the flaw after the customer has already registered your key value propositions. Let the good news sink in first.

The Hans Brinker Budget Hotel in Amsterdam built its entire brand on this. They proudly call themselves “The Worst Hotel in the World.”

Their ads promise terrible service, no amenities, and general misery. It’s hilarious, honest, and it perfectly filters for their target audience: young travelers who just need a cheap bed. It sets expectations so low they can only be exceeded.

Stop chasing the myth of perfection. Your audience already knows it doesn’t exist.

Find your “lemon”–that small, forgivable flaw. Own it. Then pivot to what actually makes you great. It’s the fastest path to earning the one thing that matters: trust.

Stop Chasing Keywords. Start Building a Knowledge Graph.

The one-keyword, one-page SEO strategy is a relic. AI Overviews and chatbots don’t care about your carefully optimized H1s. They care about synthesis.

They build answers by pulling from multiple sources. The only question left is whether your content is structured to be one of them. If you’re still playing the old game, you’re already losing.

AI search engines are becoming answer engines, synthesizing information from various sources to provide a single, comprehensive answer.

This isn’t just another algorithm update. It’s a fundamental shift from information retrieval to knowledge synthesis. Your site is no longer a collection of documents. It’s a dataset waiting to be queried.

The old model is dead. You need to think like a database.

Forget about isolated articles. Start thinking in interconnected concepts. Your job is to create a logical, hierarchical structure that an AI can parse instantly.

Your website must become its own knowledge graph.

This means organizing content so an AI understands the relationships between ideas. It needs to see your domain as an authoritative, single source of truth.

The goal is to structure your content in a way that an AI can easily parse, understand the relationships between different pieces of information, and see your website as an authoritative source on the topic.

How do you do that? With a framework built for this new reality.

Introducing the TSEA Framework: Topic, Subtopic, Entity, Attribute.

This isn’t theory. It’s a content architecture. It organizes your expertise into a machine-readable hierarchy.

Topic: The universe. Your broadest subject area (e.g., “Cloud Computing”).
Subtopic: The galaxy. A major pillar within that universe (e.g., “Serverless Architecture”).
Entity: The star system. A specific, definable noun within the subtopic (e.g., “AWS Lambda”).
Attribute: The planet. A specific property, feature, or question about the entity (e.g., “AWS Lambda pricing models”).

This model forces you to map out your entire domain. It moves you from creating random posts to building a comprehensive knowledge base, piece by piece.

Your Action Plan: From Chaos to Clarity.

This framework requires discipline, not just more content. It’s about being strategic, comprehensive, and interconnected.

Map Your Universe. Define your core Topic. Break it down into Subtopics, Entities, and Attributes. This is your content blueprint.
Build Foundational Pillars. Create comprehensive, long-form guides for your main Topics and Subtopics. These are the hubs.
Create Atomic Content. Develop specific pages or sections for each Entity and Attribute. Answer one question, perfectly. These are the spokes.
Link with Intent. Use internal links to connect the hierarchy. Attributes link to Entities. Entities link to Subtopics. Subtopics link back to the main Topic. You are literally building the web for the web crawler.

By organizing your content this way, you’re essentially creating a knowledge base that AI can easily query. This structured approach... positions you as a comprehensive resource, making it more likely that you’ll be cited in AI-generated answers.

Here’s the brutal truth.

This is not a quick fix. It’s a fundamental re-architecture of your content strategy. It requires a full audit, ruthless pruning of thin content, and a long-term commitment.

Most won’t do the work. They’ll keep chasing keyword vanity metrics off a cliff.

The reward for doing it right? Becoming the definitive source AI turns to for answers. The alternative is becoming invisible.

AI Research Isn’t a Shortcut. It’s a Trap.

Everyone thinks AI will supercharge their research. The opposite is true. It’s a productivity sinkhole disguised as an efficiency tool, turning simple fact-finding into a frustrating maze.

The myth of the AI research assistant.

The sales pitch was simple: instant, accurate sources. But the reality is a mess of digital ghosts. AI confidently hallucinates academic papers, invents quotes, and serves up dead links. It’s not just unreliable; it’s actively misleading.

“I’d been using AI to help me track down sources for articles. It was supposed to be a fast track. But it turned into a funhouse of mirrors.”

Each citation is a new rabbit hole.

What does this mean for your workflow? Instead of writing, you’re forced to become a digital detective, hunting down phantom sources. Every AI-generated reference demands a manual audit.

This isn’t an upgrade. It’s a time-suck that kills momentum and introduces a dangerous layer of potential error. You’re not saving time; you’re just shifting it to tedious, low-value verification.

The hard truth: Trust nothing.

This isn’t a call to abandon AI. It’s a reality check on its current limitations. The machine is a powerful tool for brainstorming and summarizing known information. It is not a librarian.

“For now, the human fact-checker is not just valuable; they are indispensable.”

Treat every AI citation as a clue, not a fact. The final authority is still you.

Read more in Forbes

For Those Still in the Zone

A curated batch of sharp reads—frameworks, operator lessons, and data-driven takes worth bookmarking.

Why B2B marketers can’t just ‘buy demand’ in the age of AI - by Chief Marketer
How to turn B2B outreach from noise into nurture with human-led sequences - by Acceligize
What 65 B2B marketing leaders are really solving right now - by Matt Heinz
The surprising technical lessons from 1 million conversations with AI clones of tech leaders - by SaaStr

That’s a wrap for this edition. If something here sharpened your thinking, forward it to a marketer who’s building with AI—not just talking about it.

Thanks for reading B2B Marketing Round Up! This post is public so feel free to share it.

AI Buyers, AI Natives, and the New B2B Playbook

Lucas Pawlik @ ZestScout.com — Thu, 25 Sep 2025 07:12:21 GMT

Dear readers, in today’s edition:

AI Is Rewriting the B2B Buying Process – Are You Ready?
The AI skills gap: why 50% of roles may vanish within 18 months
B2B marketing in the AI era: the curator advantage
The AEO Shift: The SEO Deep Dive Worth Your Time
Newsletters beat social: own your audience and design for AI triage

Subscribe now

AI Is Rewriting the B2B Buying Process – Are You Ready?

In making decisions and designing marketing strategies and processes, I’ve always leaned on a principle I must have heard countless times from Szymon Negacz: “start with how the client buys.” That principle is even more crucial now - because the way clients buy is shifting under our feet.

Both Szymon Negacz in his podcast episode on AI in B2B sales and marketing (in Polish), drawing on years of experience with Polish industrial and service companies, and Sydney Sloan, CMO of G2, reflecting the U.S. tech market - arrive at the same conclusion: AI is no longer just a tool for sellers. It has become a co-pilot for buyers.

The biggest shift? Autonomous client research, powered by AI, happening long before we even know the client exists. A buying process we once influenced through education and relationship-building now unfolds inside the black box of LLMs. Clients approach us later, better informed, and far less susceptible to our narrative.

Szymon Negacz observes:

“AI… will be the early advisor. Instead of calling a friend or browsing LinkedIn, executives already type the question into ChatGPT to diagnose their problem.”

This reframes the first stage of every buying journey. Instead of discovering a pain point in conversation with a vendor, buyers increasingly arrive already briefed, already comparing options. Sydney Sloan sees the same on the other side of the Atlantic:

“They’re going to LLMs first for research and discovery. They trust it. The second step is peer reviews, then websites. SEO was about clicks; now it’s about answers.”

For marketers, this means the familiar playbook of demand generation gets rewritten. Education still matters - but much of it happens in dialogue with an AI agent, not a blog or a sales deck. As Sloan notes, marketers must think in terms of Generative Engine Optimization (GEO) (or as another expert prefers: AEO) – creating content that LLMs can parse, trust, and recommend.

Negacz warns that the implications go further. AI doesn’t just surface problems - it proposes solutions, simulates ROI, and even compares offers:

“On the stage of concepts… AI already generates multiple strategic options with costs in minutes. That used to take weeks of vendor presentations.”

And at the moment of decision, he emphasizes:

“AI will be the comparison engine. The firm that hides behind vague claims - ‘we’re high quality, we’ve existed for year ’ - will lose. Models don’t care about fluff.”

Both experts underline a universal truth: trust becomes the decisive factor. Buyers will rely on AI to flag risks, aggregate peer experiences, and highlight brands with credible social proof. That’s why Sloan emphasizes:

“Trust starts with brand. Marketers must invest again in brand building, influencers, and the voice of the customer - because that’s what LLMs index as credible.”

Whether you sell software in San Francisco or industrial systems in Katowice, the message is clear: the client’s buying journey is mediated by AI, not you. Your strategy has to adapt - structuring content for algorithms, investing in brand trust, and preparing sales teams for far more educated, AI-briefed buyers.

If the buying process is changing this fast, the real question is: how quickly will your marketing adapt?

Watch the full content here: Sydney Sloan video and Szymon Negacz podcast (in Polish)

The AI skills gap: why 50% of roles may vanish within 18 months

Many leaders know they must adapt their organizations to AI but are hesitant to start. The scale of the change is enormous, and organizational transformation is inherently difficult. Compounding this fear is the lack of proven, off-the-shelf frameworks; the technology is simply evolving too quickly for best practices to emerge.

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The stakes of inaction, however, are higher than the discomfort of change. Jason Lemkin’s framework for team performance distribution reveals the uncomfortable truth about where the impact will be felt first:

The tough, honest start-up truth:
1% of your team is epic
5% of your team is great
15% of your team gets sh*t done
50% of your team does OK-to-solid work
30% of your team adds little value at all
This has honestly always been true. It’s just in 2021, there was so much organic demand for everything in business software, it masked things. And the 50% and midpack could, e.g., still be decent closers.
Not today.
AI is coming for the last two groups. Faster than most want to be honest about.

This isn’t a secret that can be ignored until the next planning cycle. The pressure to adapt is coming from every direction.

Your board is going to figure this out. Your investors already have. Your competitors definitely will.

The solution begins with re-segmenting the team based on their intrinsic attitude toward AI. This new framework reveals three distinct archetypes, providing a clear lens through which leaders can view their workforce:

The Three Types of People You’ll Discover
The AI Natives (20%): They pick up AI tools instantly. They’re already experimenting with ChatGPT, Midjourney, and automation workflows on weekends. These folks will 10x their output.
The Reluctant Adopters (50%): They’ll use AI tools if forced to, but they’re not innovating with them. They see AI as something that threatens their job security rather than amplifies their capabilities.
The Resisters (30%): They actively avoid AI tools. They have philosophical objections, or they’re just overwhelmed by the pace of change. These are your biggest retention risk.

While the common refrain is to “reskill” the existing team, the author issues a stark warning against this optimistic but often flawed strategy. He points to an interview with Marc Benioff of Salesforce as an example of this disconnect.

Benioff is right that reskilling is possible.
But he’s wrong about the timeline and success rate. Most reskilling programs fail. Not because the technology isn’t there, but because people fundamentally resist changing how they work. And reskilling for AI has to happen faster, with bigger results, than prior transitions.

Shortly after this interview, Salesforce laid off 4,000 employees, reskilling only several hundred of them - reinforcing the author’s point about the profound difficulty and often low success rate of large-scale, rapid reskilling initiatives.

Instead of a top-down, one-size-fits-all training mandate, the author proposes a simple, bottom-up strategy for leaders to drive change and discover their true AI Natives. This approach naturally filters out those who cannot adapt while creating a sense of ownership among those who can.

Here’s what I tell every CEO I advise: Bring in a new AI tool each week if you can, each month at a minimum. And see who rises to the occasion and leverages it. And who stares blankly at the Zoom.
AI is evolving at breakneck speed. What took 6 months to build last year now takes 6 days. The tools that seem impossible today will be table stakes next quarter.
I know a VP of Marketing who introduced a different AI tool every Friday for 3 months. Video editing AI. Social media schedulers. Content generators. Email optimization tools.
The results were brutal and revealing:
3 people dove in immediately, started experimenting over weekends, came back Monday with creative use cases
5 people tried them halfheartedly, used basic features, didn’t see the point
4 people literally ignored every new tool introduction

This simple diagnostic test provides the data needed to execute a more formal transformation. Lemkin provides a concrete framework that leaders can use to navigate the change over a single quarter.

The 90-Day Action Plan
Month 1: Audit every role. What percentage of their time is spent on tasks AI could handle?
Month 2: Start the transformation. Give your team AI tools. Measure output changes. Identify who adapts quickly.
Month 3: Restructure around human+AI hybrid roles. Double down on your adapters. Have tough conversations with those who can’t make the leap.

Your agenda is no longer just about managing projects and people; it’s about executing a deliberate plan to identify and empower the AI Natives who will define your company’s future.

The B2B Marketing Skills You Need to Win in an AI World

AI won’t replace marketers - but it will expose who actually adds value. The article frames the divide not as human vs. machine, but as how strategically humans use the tools.

In this reality, the winning skill isn’t raw creation - it’s curation (remember, ZestScout is the tool for that). Marketers who can filter noise, contextualize, and surface what matters will stand apart. That means reskilling away from mechanical production and doubling down on distinctly human strengths:

Taste and judgment: AI can output a hundred ideas; only you can sense which one resonates six months from now.
Context and purpose: Great marketing isn’t just aesthetics; it’s about timing, audience, and cultural signals AI can’t read.
Strategic integration: Know when AI accelerates iteration vs. when human oversight drives connection.
Storytelling: The timeless differentiator. Narratives rooted in psychology and culture still cut deeper than any algorithm.

The reskilling challenge here is clear: marketers must evolve from creators to curators, from executors to editors. AI democratizes production; humans must elevate discernment.

In short: your new edge isn’t faster output - it’s sharper judgment.

The AEO Shift: The SEO Deep Dive Worth Your Time

We’ve shared plenty of articles about SEO, whether it’s dead, and the rise of GEO/AEO. But if you read or listen to just one deep dive - make it this one. Ethan Smith (CEO of Graphite), my go-to expert on SEO after 18 years in the trenches, lays out the clearest playbook I’ve seen. The conversation with Lenny Rachitsky is the definitive guide to understanding how AI is reshaping search.

Smith has been at the forefront of what’s now called AEO (Answer Engine Optimization) - getting your product to appear in ChatGPT, Claude, Gemini, or Perplexity answers. His data is striking: traffic from ChatGPT converts six times better than traffic from Google search. The funnel is still much smaller than traditional search, but it’s growing quickly, and most companies aren’t even aware of the opportunity.

The Playbook

1. See AEO as a new funnel, not a replacement. Search is still dominant, but answer engines are a fast-rising channel. Winning here means being cited, referenced, or recommended in those AI-generated answers.

2. Optimize for citations, not just rankings. Structure your data, mark up FAQs, and link entities so LLMs reliably connect your brand to the right concepts.

3. Engineer for training, not just readers. Brutal truth: a lot of your content may never be read by humans. Its value is in training the engines that decide what answers people get.

4. Track new KPIs. Beyond SERPs, measure:

Reference rate (how often engines mention you).
Attribution depth (whether your product is explained, not just dropped in).
Citation quality (are you listed as a source?).

5. Build AEO loops. The new flywheel: structured mentions → model training → engine recommendations → more citations. Done right, it compounds alongside SEO rather than replacing it.

Reality Checks

If you’re only optimizing for Google, you’re missing a parallel channel that converts better.
LLMs are becoming a new homepage. Being cited there matters, even if volumes are smaller today.
AEO is compounding. Early movers will be hardest to unseat.

The Content Flood Problem

One of the sharpest sections is their discussion of AI-generated spam flooding the web. Ethan Smith shares a practical framework to separate signal from noise:

Valuable content = Information Gain + Authority + Experience

Information Gain: Does it add something new to the conversation?
Authority: Is it published or referenced by a trusted, high-signal source?
Experience: Is there real expertise or context, not just word salad?

At ZestScout, this hit home. Curation is our job, and the hardest part is weeding out AI-generated junk while surfacing content with real info-gain and authority. We love Smith’s framework because it’s the closest thing we’ve seen to a practical filter for the new content ecosystem.

Bottom line: SEO isn’t dead, but the rules have changed. AEO is a smaller funnel today - but one that’s growing, converts better, and compounds fast. Ignore it, and you risk being invisible where tomorrow’s buyers are searching.

Newsletters outperform social: 295x value

Email beats algorithmic rent-seeking. It is permission, identity, and durability in one channel. In a coming AI-filtered inbox, only clear structure and authentic voices survive. Build the list now, design it right, and own your reach.

Own the channel – permission-based, open protocols, high ROI; U.S. firms now spend more on paid email subscriptions than newspapers; Substack hosts 61% more paid newsletters than Medium.
Design for UX – minimal sign-up, instant welcome, clear From and subject, scannable layout, image alt text, one-click unsubscribe, with opt-down choices to cut churn.
Control cadence – offer frequency and topic preferences; 59% unsubscribe due to too many emails, 51% due to sender frequency.
Optimize for AI – craft subjects and preheaders, structured headings, authenticated sending, and unique data that assistants elevate, not discard.

My 25,000 newsletter subscribers generate 44 times more page views than my 166,000 LinkedIn followers. This means that each newsletter subscriber is worth an astronomical 295 times more than a LinkedIn follower. When it comes to reliably reaching your audience, newsletters’ signal-to-noise ratio is hard to beat.

Newsletters: Pipeline Generation, Audience Building, Authentic Engagement

Lucas Pawlik @ ZestScout.com — Fri, 12 Sep 2025 10:50:13 GMT

Here’s a story I see every so often. A founder or a B2B marketer gets a burst of energy: “We need a newsletter.” They launch. They ship one issue. Then a second. Then… silence. The idea fizzles out, relegated to the strategy doc graveyard.

The problem isn’t the effort. It’s the feedback. Early newsletter growth feels like shouting into the void. The numbers are so small, the progress so slow, that it’s easy to get discouraged and quit.

This issue is the antidote. It’s a complete playbook dedicated to proving why sticking with it is the highest-leverage move you can make. We’ll cover why it works, how to build an audience from scratch, what real results look like, and show you that—when done right—it’s not a chore. It’s the most rewarding part of your marketing stack.

Subscribe now

In today's edition:

The most underrated B2B channel: newsletters that build trust and performance
Founder-led newsletters that print pipeline: 40-60% opens and a $1M ARR playbook
4,879 subscribers in 8 months: LinkedIn-to-newsletter growth that prints ROI
Newsletter engagement that compounds: 2x CTR and ~50% opens with plain text and segmentation
The biggest B2B newsletter mistake: all-about-us content
Stop generic AI emails with a 3-part formula
Exit Five’s 45K B2B newsletter: how it wins attention and loyalty
Twice-weekly cadence: cutting items to 6-8 drove 179%-577% more clicks

The most underrated B2B channel – 71% use newsletters, 50% say they drive performance

Your sales team is fighting over 5% of the market. The other 95% aren’t buying, and they’re ignoring your ads. The newsletter is the only channel that earns their attention while they’re idle.

It’s not a sales tool; it’s a trust engine running on a six-month delay. While competitors chase clicks, you build relevance. The payoff isn’t a conversion today. It’s being the only name on the shortlist when they finally are in-market.

The goal isn't to close a deal this quarter. It's to be the only company they think of next year.

Curated newsletters also can be the lever – and ZestScout exists to make them easy for small B2B teams, so your newsletter delivers value consistently through sharp, point‑of‑view curation.

These are more like roundups. You’re sharing both your own content and helpful third-party content that supports your audience’s needs.
Curated newsletters tend to be a bit more designed, so readers can easily scan and find what’s relevant to them. The user experience of this type of newsletter is critical. And while they’re often built around distribution, that doesn’t mean they should be devoid of perspective.

Curated newsletters aren’t a shortcut; they’re a filter. Readers subscribe to avoid noise and borrow your judgment. Curation is the value. Don’t just drop links—add context and tell me why it matters now.

That’s exactly why we’re building ZestScout: to make high‑quality, POV‑driven curation radically easier for small B2B teams.

Selling to the 95%: How Newsletters Build Future Pipeline

Picture the moment your buyer finally enters the market. Who do they think of first? Not the brand with the loudest ad spend, but the founder or team that has been in their inbox twice a month with useful, specific insights. That quiet consistency beats sporadic campaigns and builds a line of credit you can draw on when timing clicks.

A few operators break down exactly how this works in practice — from starting tiny to engineering conversions — and their data lines up with what we see across B2B.

Most founders build a product, then hire salespeople to hunt the 5-10% of the market that’s actively buying. They spend fortunes on ads, cold outreach, and demos, fighting competitors for the same sliver of attention. The other 90%? Ignored. They’re not in a buying cycle, so they’re invisible to the sales quota.

This is where the founder-led newsletter becomes an unfair advantage. It’s a tool for selling to the majority—the silent, in-market-next-year audience - without ever sending a pitch. It’s not a sales tool; it’s a trust engine running on a six-month delay. The goal isn't to close a deal this quarter. It's to be the only company they think of next year.

The playbook isn't about volume; it's about trust. Nathan May, frames it as owning your most valuable asset — and shares practical, step‑by‑step guidance on how he did it:

• 90% of your ICP isn’t in the market to buy TODAY. But when they will be, you’ll be the first person they think of.
• You can meet only once per quarter on a sales call with your prospects —
miss it, and you wait for 3 months. But a newsletter lets you talk to your ideal customers 2-4X a month.
• Newsletters help you go from "pushy salesperson" to "thought partner" if you focus on consistently providing value (more on that below)
• <20% of your social followers are likely to see your content, but 40-60% of your subscribers will open/read your newsletter

The playbook isn't about volume; it's about trust. Nathan May, frames it as owning your most valuable asset: He built a $1M ARR business in 11 months,

If your deal cycles run months, a newsletter keeps you present in the “quiet moments” when trust is made. People buy when they are ready, not when you are; a weekly email keeps you top‑of‑mind so “maybe later” turns into inbound.

Owned distribution is the moat. While competitors rent reach from algorithms, you build a channel that compounds trust and recall — immune to platform risk.

And when that 90% of the market is finally ready to buy, you’re not one of the options. You’re the only option.

Max Bidna summarizes

“A weekly newsletter isn’t just ‘nice to have.’ It’s your silent sales machine.”

Sources and further reading (credit to the authors):

Long sales cycles? Weekly newsletters are your silent sales machine — Max Bidna link
Own the distribution, guide the journey — newsletter as the missing conversion layer — Daniel Bustamante link
Founder newsletter → $1M ARR in 11 months — 4 principles that convert — Nathan May link

What is a newsletter without subscribers? This story proves the compound effect, the joy of building, and the practical moves that grow a list fast.

The Subscriber Growth Playbook: From 0 to 5,000 Subs with No Budget

Everyone wants a list of 5,000 subscribers. Almost no one wants to do the work to get the first 50. Andrew Mewborn’s journey from 0 to 4,879 subscribers in 8 months—with no ad spend—is a masterclass in the unglamorous reality of growth. His start wasn’t a viral myth; it was a brutal grind:

The first month? 12 subs.
Second month? 84 subscribers.
Third month? 378 subscribers.
Then something magical happened...

The magic wasn't a growth hack. It was consistency. But effort alone isn't enough. You can show up daily and still talk to an empty room if you make one fundamental mistake: making the newsletter about you.

This is where most newsletters die. They become a megaphone for company updates. Michelle Pitcher puts it bluntly: the mindset has to shift from “what do I want to say?” to “what do they need to hear?” It’s about giving, not asking.

→ Forget what you want to say and think, 'what do they want to hear?'
An easy trick is to write down every question someone asks you.
Check your call recordings.
Social media comments.
Conversations with clients.
And notice what they're after...
→ Stop worrying about impressing and focus on connecting
Who cares about what recent awards or achievements you've made...
Sure, it's good for credibility, but you don't have to talk about it all. the. time.
Instead of trying so hard to impress people with your - knowledge - status - accolades. Focus on connecting.

So, the formula seems simple: brutal consistency (Mewborn) + radical reader-focus (Pitcher). But how do you execute that without burning out? You need a system. Amanda Goetz, who grew her list to over 60,000 subscribers, offers a practical playbook for starting smart and staying the course. Two rules stand out:

➡️ 1. Inject Yourself to Build Connection
Many newsletters miss the opportunity to build an emotional connection with their audience. They deliver information, but not personality. Goetz argues for injecting yourself into the narrative through images, life updates, and stories. It’s the difference between a report and a relationship.
➡️ 2. The 90/10 Value Rule
Most of you are starting a newsletter as a sales vehicle to your products…. And that’s OK but I’m starting to see newsletters that don’t add any value. They just sell. Focus on 90% value. 10% sales. This increases your referrals because no one refers commercials but they do refer documentaries.

In the end, the playbook is simple, but not easy. It’s a machine built from consistency, empathy, and a system. As Mewborn puts it:

You can start with 0 followers. You can start with 0 budget. You just can't start with 0 effort.

Sources and further reading (credit to the authors):

The Subscriber Growth Playbook: From 0 to 5,000 Subs with No Budget — Andrew Mewborn
5 Mindset Shifts to Grow Your Email Newsletter — Michelle Pitcher
How I'd Build a 60,000+ Subscriber Newsletter From Scratch — Amanda Goetz

Email newsletters have been declared dead more times than I can count. Too crowded, too noisy, too transactional. And yet—Exit Five has 45,000+ marketers eagerly waiting for every send. How? This story isn't about growth hacks. It's about a fundamental shift in mindset—from distribution to relationship—that every marketer needs to understand.

Exit Five’s 45K B2B newsletter: how it wins attention and loyalty

Email newsletters have been declared dead more times than I can count. Too crowded, too noisy, too transactional. And yet—Exit Five has 45,000+ marketers eagerly waiting for every send. Replies flood in. People actually look forward to it. How?

Ann Handley once said: “The most important part of the newsletter is the letter, not the news.” Danielle Messler, Head of Content at Exit Five, has built the newsletter on that principle. Where most B2B brands push out blog links, Danielle treats every send like a personal note: conversational, fun, sometimes confessional.

“It matters who the newsletter comes from. It matters what you’re saying. It matters that you respect people’s time.”

That shift—from distribution to relationship—explains why subscribers talk about Exit Five as the only business newsletter they always read.

Another differentiator: transparency. Instead of hiding behind an email wall, Exit Five publishes all past issues openly. Danielle calls it a “try before you buy” approach:

“Our inboxes are already packed with unwanted senders. To invite someone in, you’ve got to prove why you deserve it.”

This openness removes risk, builds trust, and self-selects the right audience. If you like what you see, you subscribe knowing exactly what you’ll get.

The content itself is sharp because each issue carries one clear takeaway. Danielle puts it simply:

“Make sure there’s something in your newsletter readers can learn today. Something they can implement in some way.”

That could mean unpacking a strategic framework or pulling a tactical hack from a community thread. When Dave Gerhardt interviewed Mutiny CEO Jaleh Rezaei, the newsletter didn’t just summarize. It showed how to apply her growth strategy immediately—a concrete play, not a recap.

Measurement also looks different. Exit Five isn’t chasing vanity CTRs. Danielle obsesses over replies, sometimes getting 30–40 to a single email—numbers almost unheard of in B2B.

“From the strategy side, replies boost deliverability. They tell email clients people want you in their inbox. But more importantly, they drive real conversation and connection.”

Here’s the kicker: Danielle reads and replies to every single one. Dave Gerhardt described her approach as “super unscalable.” That’s exactly why it works.

Subject lines follow the same logic. No clickbait—just curiosity gaps that promise value. One example: “Here’s what to do when you’re not the subject matter expert.” If you’re not an expert, you want to know what’s inside. If you are, curiosity still pulls you in. The difference is trust: Exit Five always delivers on the tease.

And when it comes to starting, Danielle has a blunt rule:

“You’ve got to get at least 10 newsletters in before you actually know what the format is going to be and what works. Don’t worry if it changes by issue 10. No one cares. Just keep getting the reps in.”

The lesson: stop polishing drafts that never ship. Consistency beats perfection. For Exit Five, that discipline turned a newsletter into the single most loved B2B media product in its niche.

Stop generic AI emails with a 3‑part formula

AI writes “correct,” not compelling. If your message could go to anyone, it lands with no one. The fix is surgical: codify who you write to, who is speaking, and why it matters now.

Define personas with Jobs–Pains–Gains. Use live data from surveys, CRM, and support to keep segments current and specific.
Codify the author’s style. Analyze actual team writing to extract tone, vocabulary, rhythm, and signature moves, then reuse as rules.
Inject company context. Values, product differentiators, target regions, and voice markers keep outputs on‑brand across campaigns and locales.
Operationalize the stack. Context = Persona + Author style + Company profile; then BrandKit + Context + Prompt → draft, human post‑edit for fit.

Real personalization = Contact + Context + Value.

Read this to build emails that scale without sounding machine‑washed. You’ll get faster drafts that still read unmistakably like you.

Twice-weekly cadence, 12–13 items cut to 6–8, drove 179%–577% more clicks

OI split a bloated weekly into two lean sends. Two extra house ad slots and smarter batching. Opens dipped slightly, yet CTR rose and monthly reach broadened.

Cut clutter to lift focus: Reduced per-issue load from 12–13 links to 6–8, improving visibility for mid-pack items.
Double cadence, measure outcomes: Q4 2023 weekly vs Q4 2024 twice-weekly. Unique open rate fell slightly, unique CTR increased materially.
Prioritize total traffic: Monthly outbound clicks grew 179%–577% after the change, sending far more visitors to featured sites.
Track reach rate: Share of subscribers who click at least once per month rose, indicating broader engagement, not just heavier activity from a few.

More frequent sends + less crowded issues = more engagement.

Content System Blueprints, GetResponse Benchmarks, Substack ROI, Agentic Workflows

Lucas Pawlik @ ZestScout.com — Tue, 26 Aug 2025 10:58:31 GMT

The conversation around AI in marketing is getting an upgrade. A year ago, it was about using ChatGPT to write a blog post. Now, it’s about building multi-agent systems that handle the entire content pipeline, from research to distribution.

This isn’t just a new tactic; it’s a fundamental shift in operations. The line between a simple tool and an autonomous workflow is blurring, and the teams that build systems will outpace those who are still just prompting.

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This week’s issue is about making that leap. We'll cover:

Agentic workflows vs. AI agents: the data on quality and efficiency
A 6-step playbook for building your own content agent system
How to fully automate a weekly newsletter (the DIY version of ZestScout)
Forrester’s prediction: how agents will gut SaaS and kill search
And more...

Let's get into it.

After 200+ hours of tool tests, the verdict is in. Workflows win for scalable, publish-ready content. Agents are fine for speed, not for outcomes that rank, convert, or survive QA. Here is the operating truth.

Agentic workflows beat AI agents: SEO 88 vs 58, edit time −78%, factual errors −65%

Quality and SEO: A 20-article run averaged an SEO score of 82 vs. 56, readability Grade 8 vs. 11, with 6 verified sources and 5 internal links baked into the workflow process.
Reliability: Standalone agents produced factual errors in 60% of drafts; workflows cut errors by 65% with a separate fact-check step.
Efficiency: For the same topic, edit time was 10 vs. 45 minutes, with consistent headers, layout, and meta handled automatically.
Scaling: SOPs and templates took output from 3 to 20 posts per week. Use agents for outlines and summaries; use workflows for publishable content.

Build a 6‑agent content system in under 60 minutes – cut draft time while keeping your voice

Most AI blogs are generic. This workflow turns simple markdown personas into a modular pipeline that preserves point-of-view and accelerates research, drafting, and publishing with enforced checkpoints.

Specialize your agents: Six core roles: Idea→Outline, Researcher, Devil’s Advocate, SEO, Editor, and Google Doc Formatter.
Exploit the time delta: The average blog post takes 3h 48m. This system can be built in under an hour, producing drafts in minutes. 36% of marketers using AI already finish long-form content in under 1 hour.
Design the workflow: Map steps, flag bottlenecks, set human approvals, and write master instructions coordinating the agent handoffs.
Use tools, not crutches: Claude or ChatGPT Plus is all you need. The ~$20/month cost is repaid if you save just two hours of work.

Automate Your Weekly Newsletter

This guide turns curation and sending into a factory. It’s a masterclass in building a robust pipeline with daily RSS pulls, a content pool in Sheets, human-in-the-loop review, and AI summaries. Less keystrokes, more signal.

Build a scalable pipe: Aggregate 10+ RSS feeds, standardize fields, store in Google Sheets, and avoid duplicates with URL lookups.
Insert human control: Route drafts to Google Docs or Airtable, require an “Approved” status, and resume the workflow via webhook.
Add AI where it pays: Use OpenAI for summaries, segment-specific subject lines, and CTA rewrites to lift CTR.
Engineer reliability: Use cron scheduling, threshold checks, retry logic, and error alerts in Slack to ensure it never fails silently.

GetResponse Review: 350,000 Users, Strengths, and Hidden Costs

Built for e-commerce more than bloggers. Think funnels, webinars, and strong automation, with pricing that climbs as you add power.

Exploit the funnel suite: Build landing pages with 30+ scenarios, track sales, and run webinars. The free plan allows 1 page with 1,000 visits; full funnels start on the Marketer plan.
Model e-commerce workflows: Use abandoned cart triggers, GA integration, promo codes, and AI product recommendations. Note: many features unlock on higher tiers.
Budget with constraints: The free tier covers <500 contacts and 2,500 sends. Removed and duplicate contacts still count toward your limit.
Automate at scale: Advanced workflows, scoring, tagging, and A/B testing outperform mid-market peers, but are reserved for higher plans.

How Brands Win on Substack: 20M MAUs, Creator-Led Commerce, and Realistic ROI

Fragmented distribution punishes passive brands. Substack’s audience skews educated, with discretionary income and shopping intent. Treat it as a high-intent network, not a megaphone.

Build or borrow an audience: Partner with existing creators first, or publish yourself if you have the editorial muscle.
Copy what works: Domino gets roughly one-third of its subscribers from Substack by offering free weekly sends and paid twice-weekly exclusives.
Commit to the craft: Be consistent, authentic, and participate in the community. Expect 6–12 months for traction.
Test spend, don’t spray: Avoid jumping into $10K+ takeovers before proving resonance across PR, affiliate, and social channels.

Creativity vs. AI Average, Faster Content in 6 Steps, LLM Bias Loops, MA Tools ROI

Lucas Pawlik @ ZestScout.com — Wed, 13 Aug 2025 07:26:01 GMT

In this edition:

AI in B2B: scale output, not sameness
AI-assisted speed without losing voice: a 6-step playbook
AI prefers AI: self-preference bias and its fallout
Marketing Automation 2025: ROI benchmarks and hidden costs

This week’s main theme: how to merge human creativity with AI support in content creation. The goal? Use AI to enhance, not erase, your unique perspective. Because while AI can speed research, draft faster, and help you structure ideas, overreliance risks producing generic, recycled work that readers instantly forget - or worse, actively avoid. Let’s dive into the third issue of our newsletter:

B2B AI will scale content - buyers won’t notice

The author wrote "AI is a creative tool, not a replacement for creativity." He’s right. In many B2B marketing teams, AI doesn’t just write - it decides what will be written, executing strategies born from prompts. Once, Don Draper in Mad Men drowned in whisky hunting the one idea that would make a campaign unique; today, many marketers hand to AI the job of producing something safely averaged from what others have already done.

US marketing content output is climbing—up 12% YoY—but attention isn’t keeping pace. People scroll past 100+ ads daily and remember only about 10%. According to System1, 71% of B2B ads are instantly forgettable. Add AI into the mix without a clear strategy, and you risk accelerating invisibility instead of growth.

Prioritise creativity to capture attention, not just increase volume.
Ungate standout content to build brand salience well before consideration.
Use ABM selectively, while scaling reach to grow overall demand.
Vet AI like a new hire—track for effectiveness as well as efficiency, and challenge defaults.

Read more in Advertising Council Australia

And if we are talking about using AI to support creativity, below is a simple recipe...

AI for faster content: 6 steps, 4 reasons it still matters

Andy Chadwick shares a speed playbook that preserves voice by mixing AI agents with dictated insights and tight edits.

Automate research with agents. Use AI agents (like Manus) to gather stats and pain points in minutes, not hours.
Speak, then structure. Dictate your take, transcribe, feed notes plus research into a model trained on your tone.
Multiply clarity. Add 1 example, ask for 3 more, then layer tight metaphors to anchor complex ideas.
Polish with intent. Shorten, fix transitions, restructure, and add a specific CTA.

"Original thought still wins."

AI prefers AI – self-preference bias and what it breaks

A new study shows LLMs systematically prefer AI-generated text, even when humans rate quality equal. That bias, plus human disclosure effects, sets up a feedback loop that reshapes hiring, education, and news distribution.

Bold insight you’ll gain: Spot the loop – AI trains on AI, then prefers AI, shifting hiring, grading, and distribution.

Evidence: LLM evaluators upscore their own outputs across tasks; GPT-4 self-preference correlates with lower perplexity, meaning familiarity.
Impact: AI-optimized résumés and AI copy gain algorithmic boosts, authentic human work is penalized or flagged.
Human twist: People often prefer AI text until origin is disclosed, then trust drops, altering decisions in high-stakes contexts.
Do now: Run self-preference audits, diversify training data, blend human review, use multiple detectors, and build double literacy to counter human and algorithmic bias.

Read more in Forbes

I often hear founders and CMOs debating “HubSpot or not” and how to choose the right marketing automation platform. This sharp, methodical piece lays out a clear and simple framework for making that decision - and reveals what it will really cost.

Marketing Automation 2025: ROI Benchmarks, Top Picks, Hidden Costs

Data from 312 companies and $23.7M spend shows average 215% ROI while top performers hit 400%+. Use this to de‑risk platform selection, budget, and implementation.

Hidden costs can 2–3x software. Three‑year TCO: Startup 47K, SMB 189K, Mid‑market 456K, Enterprise 987K.
Why teams fail: 61% miss year‑one ROI. Winners allocate 2.4 FTE, implement in 3.2 months, improve lead quality 89%.
Payback: e‑commerce 2.1 months (Klaviyo), SMB 2.8 (ActiveCampaign), mid‑market 4.2 (HubSpot), enterprise 6.1 (Pardot).

SEO Recycled, AI Deep Dives, SMB Efficiency Gaps, Expert-Led Content

Lucas Pawlik @ ZestScout.com — Wed, 30 Jul 2025 07:25:35 GMT

Dear Readers,

In today's edition:

AI Search Disrupts SEO: The New Playbook
10 Survival Tactics for SEO in the Age of AI
Debunking the “SEO Is Dead” Myth with Data
AI Deep Research: The Marketer’s Secret Weapon
Authenticity Over Polish: The Power of Expert-Led B2B Content
AI in SMB Marketing: Efficiency Gains and Adoption Gaps
…and more. Enjoy the read!

In today's edition, we're taking another look at yet another 'end of SEO,' along with several other topics. Let's kick off with an insightful report on SEO in the age of AI.

AI Search Disrupts SEO: Brainlabs Data, 200 Countries, and the New Playbook

AI search isn’t nibbling at SEO’s edges, it’s rewriting the rules. Brainlabs’ July 2025 report shows Google’s AI Overviews now run in 200 countries and 40 languages. The kicker? 96% of AI Overview links still come from the top 10 organic results, but click-throughs are plummeting.

Impressions up, clicks down: Marketers see more visibility but fewer site visits as AI answers user queries directly.
Bot traffic overtakes humans: 2024 marked the first year bots outnumbered people on websites.
AI search visitors are 4.4x more valuable than traditional organic, but attribution is a nightmare.
Winning requires “Search Everywhere Optimization”: Brands must build credibility and structure across all platforms, not just websites.

“Impressions are climbing, but clicks are steadily dropping.”

And here's the full report.

Subscribe now

So if you want to dig deeper...

SEO Isn’t Dead - But AI Is Changing the Game: 10 Survival Tactics

Google’s search share just dipped below 90% for the first time in a decade. Nearly 1 in 4 Americans have used ChatGPT at least once. The old SEO playbook? It’s obsolete. Here’s what actually works now.

Google now delivers half the referral traffic it did four years ago.
27% of U.S. users report using AI tools instead of search engines.
AI chatbots reached 987 million global users in 2025.

Here are our top tips for now to tie everything up – with the emphasis on ‘for now’:
Extend your reporting to make sure that you understand where you’re appearing. Google is now testing its AI reports in Search Console, for example, and those will be mighty handy.
Create top quality content that’s well structured and visual.
People search using AI Chatbots in a more rambly conversational way versus the abrupt phrases of classic SEO (‘sustainable marketing agency’ vs. ‘can you recommend a sustainable marketing agency that might be able to help me in Europe in English, please?’). So take exact keyword volumes with a pinch of salt when creating content. Instead, consider overall themes and audiences.
Avoid scientific ‘top-of-funnel’ content where people would rather get a quick AI summary that assimilates a load of sources instead of just, like, your opinion. Don’t write a post on ‘how to…’ or ‘what is…’ unless it’s a very special take.
Be creative and tell original personal stories that AI can’t easily replicate. Even better to be a little opinionated, like AI isn’t.
Adopt the Reddit spirit. People search for ‘x + reddit’ because they want a human perspective. Bring a bit of that personality into your brand’s content.
Philosophically, get back to thinking about how people found things before SEO. Consider AI to be like an erudite – if unreliable – friend making recommendations. - Embrace unpredictability. What works today might vanish tomorrow. The relative steadiness of SEO has been rocked.
On the other hand, don’t change too much! Some of the same ‘brand building’ things that work for modern SEO will also help you to be cited by AI.
Simply, make sure AI agents can crawl your site and there are no technical barriers.
Examine your server logs using tools like Screaming Frog. This can give you a deeper view of how AI chatbots are interacting with your content. Standard analytics like GA4 can’t tell you what’s happening when people engage with your content through ChatGPT or Custom GPTs.

SEO’s “Death by AI” Is Overhyped: Data Shows Old Playbooks Still Win

AI search isn’t killing SEO. It’s recycling it.

93.57%: Google’s search share in 2024, dwarfing ChatGPT’s sub-1% (SparkToro).
“Revolutionary” AI tactics? Mostly rebranded SEO - long-tail keywords, multi-modal content, and cross-platform visibility have been standard since 2015.
AI search visitors convert 4.4x better than organic, but traffic volume remains tiny (Semrush, June 2025).
Core SEO skills - content quality, technical optimization, and user intent - remain the foundation. AI just adds new layers: prompt engineering, NLP, and workflow automation.

“SEO professionals remain uniquely qualified to guide companies through the transition to AI-powered search environments.”

AI Deep Research: The Strategic Edge Marketers Ignore

Most marketers waste hours sifting through surface-level search results. DeepResearch AI flips the script, delivering 80%‑complete strategic briefs in under 90 minutes - work that used to take two days.

Go beyond page one: DeepResearch uncovers sources buried past the top 100 search results, including analyst reports and social sentiment from forums like Reddit.
Synthesize, don’t just search: AI aggregates competitor messaging, identifies content gaps, and surfaces emerging trends - no more manual slog.
Prompt like a pro: Structured, goal-driven prompts yield actionable insights. Vague questions get you summaries; specific tasks get you strategy.
Reality check: AI can hallucinate. Always verify sources and context before acting.

“It wasn’t about automating work. It was about surfacing research, case studies and trends past the first page of search results.”

Expert-Led B2B Content: Why Authenticity Outperforms Polish

B2B buyers are tuning out glossy, brand-safe content. They crave real insights from practitioners, not marketers.

Expert-led posts drive results: Informal videos and candid takes from founders or product leads spark thousands of views and direct sales conversations.
Marketers must shift roles: The best teams act as amplifiers, not gatekeepers, helping internal experts turn raw experience into public value.
Proof in numbers: Brands like Lavender and Gong built communities and pipeline by putting subject-matter experts front and center, not behind templates.
Risk pays off: Letting go of total brand control increases trust and engagement, even if it means going off-message.

AI in SMB Marketing: 13 Hours Saved, $4.7K Cut - But Only 23% Go All-In

Most small businesses dabble in AI, but few go deep. A new ActiveCampaign study of 1,000 marketers found:

AI saves SMB marketers 13 hours per week and $4,739 monthly per team.
Only 23% use AI across the full marketing cycle; 82% use it for at least one task.
Power users (15%) are 14x more likely to apply AI end-to-end and save nearly 15 hours weekly.
Transparency pays: 64% of businesses that openly share AI use see very positive customer reactions.

The real edge? Teams reinvesting time savings into strategy and creativity are outpacing larger rivals. Occasional AI use is table stakes - systematic adoption is the multiplier.

Read more in Forbes

A few more, if you're in the zone...

Why “AI Slop” Is Flooding Your Feed - and Why Human Content Matters More Than Ever – via LinkedIn

Why Hitting ‘Publish’ Is Just the Beginning: Ross Simmonds on Unlocking the Real Power of Content Distribution – on The Agents of Change

What LinkedIn’s Massive Study Reveals About B2B Video Success (and the 5 Creative Secrets You Need) – on PPC Land

B2B Marketing by the Numbers: Surprising Stats Shaping 2025’s Biggest Trends – on Sci-Tech Today

Why Most B2B Marketing Gets Forgotten - and How Mental Availability Can Unlock Explosive Growth – on CXL

How to Make Your Content Irresistible to AI Recommendations – by Search Engine Journal

Enjoyed the roundup? Share to support the author.

Content Perfectionism, AI Thought Leadership, Substack Playbooks, Schema Wins

Lucas Pawlik @ ZestScout.com — Tue, 15 Jul 2025 06:20:44 GMT

Alright, here we go. First edition.

I’m Lucas. I've spent years in B2B marketing—agency side, startup founder side, both sides of the table. Now I'm building ZestScout – a tool to help craft B2B newsletters that actually cut through.

Seems only right I use it myself. This is my signal-boosting operation: hand-picked articles, sharp takes on B2B content, AI's impact, thought leadership, and why newsletters are having a moment. I’ll use the product I’m building to bring you the B2B content I wish someone sent me.

Hope this selection – filtered through my lens – brings something useful to your own day-to-day.

It’s V1. It'll evolve based on what you tell me. Reply and let me know what lands.

Subscribe now

In today's edition:

Content Marketing Perfectionism: The Hidden Revenue Killer
B2B Thought Leadership: Data-Backed Keys to Buyer Momentum
AI & Thought Leadership: 4 Myths That Will Sink Your Credibility
Substack for Brands: Unlocking Authentic Engagement
Schema Markup for SaaS: Small Fixes, Big Visibility Gains
B2B Marketing & PR: 41 Stats That Entertain, Surprise, and Challenge

…and more. Enjoy the read!

Guilty as charged. This newsletter would already have about eight issues if I didn't have this exact problem myself. I should stick this article on a sticky note on my monitor—maybe you should, too.

Content Marketing Perfectionism: The Hidden Revenue Killer

Perfectionism isn’t a badge, it’s a bottleneck. While 82% of marketers invest in content, most are losing ground to their own hesitation. The stats are brutal: 71% of U.S. CEOs and 65% of execs admit to imposter syndrome, stalling their output. Meanwhile, buyers consume 3–5 pieces of content before talking to sales – so every delay is lost pipeline.

Delayed content = lost pipeline: 47% of buyers consume 3–5 pieces before engaging sales. Every unpublished post is a missed conversation.
Resource drain: 58% cite lack of resources, but perfectionism amplifies scarcity—most spend 80% on creation, 20% on promotion.
SaaS and B2B are most at risk: Endless reviews, legal checks, and “feature-perfect” content kill momentum and relevance.
The fix: Adopt the SPELL framework—Speak to pain, Publish over perfect, Empathy, Let it be human, Learn from feedback.

"Every piece of content you don’t publish is a conversation you’re not having with potential customers."

B2B Thought Leadership: Data-Backed Keys to Buyer Momentum

AI-generated content floods the market, but 74% of executives crave more provocative, challenging thought leadership. Nearly 60% see near-identical content from multiple providers, and 72% of marketers fear AI will homogenize everything.

68% of leaders now consume more thought leadership; 55% say its credibility and decision-making value have improved
63% want advice relevant within 3–12 months, not distant trends
99% consider thought leadership crucial for evaluating trusted advisors
Four essentials: originality, conversation stimulation, actionable ideas over format, and a clear problem-to-solution arc

AI & Thought Leadership: 4 Myths That Will Sink Your Credibility

AI’s content boom tempts experts to take shortcuts. But the bar for real thought leadership has never been higher.

Myth 1: AI makes thought leadership easier. Reality: Content inflation means standing out is harder than ever; depth, not volume, wins.
Myth 2: You can automate idea creation. AI remixes, but only you can originate. Originality still demands human discomfort and risk.
Myth 3: Editors are obsolete. Wrong. AI can’t challenge or clarify; human editors remain essential for rigor and resonance.
Myth 4: Writing skills are optional. Writing is thinking. Without mastering narrative craft, even AI-assisted work falls flat.

AI is not a magic wand. It’s a force multiplier.

That’s the bet behind ZestScout: use your exxpertise to cut through the noise, not add to it.

Read more in Forbes

The ZestScout prototype was first battle-tested on my wife’s ESG newsletter at wastebusters.pl. That’s when I saw firsthand: if you deliver real value, an audience will follow - also on Substack. I’m now exploring the platform’s potential for myself. Maybe you should, too.

Substack for Brands: 5M Paid Subs, Real B2B/B2C Playbook

Substack’s not just for indie writers anymore. With over 5 million paid subscriptions—a 67% jump in under a year—brands are moving in, chasing direct audience access and engagement.

American Eagle: Launched “Off the Cuff” and hit 2,000+ subscribers in six weeks. The focus? Gen Z, cultural relevance, and authentic, non-transactional content—think group chat, not sales pitch.
Hinge: Ran a five-part literary series, “No Ordinary Love,” partnering with Substack-native writers to deepen storytelling and build trust through narrative, not ads.
Rare Beauty: Publishes weekly behind-the-scenes content shaped by community questions. The newsletter spotlights company values and transparency, not just products.

Curious how these brands actually execute—and what pitfalls to avoid? The article breaks down each case and delivers actionable tips for leveraging Substack in your own strategy.

Read more in Content Marketing Institute

To wrap: something practical you can implement today and create compound impact on your business . We spend hours crafting content, then skip the simple tweaks that give it reach. This piece shows how a few technical fixes can quietly boost your visibility.

Schema Markup for Content: Small Fixes, Big Visibility Gains

Most marketing teams obsess over product pages and blog polish, but ignore the invisible layer that makes Google actually “get” your content. Schema markup is that layer. It’s not glamorous, but it’s the difference between being just another tool and owning the SERP spotlight.

Clarify your content’s true purpose. Schema turns vague pages into explicit signals – pricing, tutorials, reviews – so Google stops guessing.
Unlock rich SERP features. Sites using schema see higher click-through rates and more FAQ, review, and job listing visibility.
Reduce ambiguity, boost trust. Structured data helps Google distinguish your SaaS from generic products, surfacing ratings and outcomes.

A few targeted schema tweaks can compound into outsized search gains – without a full site overhaul.

Read more in DataDab and follow the instructions to implement today.

B2B Marketing & PR: 41 Stats That Entertain, Surprise, and Challenge

A quick glance at these stats might amuse you, but the real story is in the patterns they reveal. The numbers span CMO trends, budgets, sales alignment, content, PR, and the AI arms race.

Budgets edge up: Marketing budgets now average 9.4% of company revenue, with 23% of marketers seeing “significant” increases.
Email still rules, but beware overload: 19.3% of conversions come from email, yet buyers get 100 emails daily and 54% unsubscribe due to excess.
AI is everywhere: 82% of PR pros and over half of journalists use generative AI, but 72% worry about factual errors.

I haven’t verified every stat’s credibility - treat these as conversation starters, not gospel.