Category Design Is a Company Strategy, Not a Marketing Exercise

Why Scrunch reframed bot traffic as a first-class website visitor — and what that means for B2B site architecture | Kevin White

Scrunch is building the measurement and optimization layer for the AI search era — helping marketers understand how their brands show up inside ChatGPT, Perplexity, Gemini, and beyond. In this episode of The Marketing Front Lines, we sat down with Kevin White [https://www.linkedin.com/in/kevbosaurus/], Head of Marketing at Scrunch [https://scrunch.com/], to cut through the noise on what's real, what's myth, and what's actually worth doing in AI search optimization right now. Topics Discussed: * AEO vs. GEO: why the terminology debate is a distraction from what actually matters * Why no one — including the LLMs themselves — fully understands how citations work * The Reddit citation myth and what's actually driving high-intent AI results * How to measure AI search performance in a probabilistic, non-deterministic world * Whether SEO and AI search belong under the same roof — and who should own it GTM Lessons For B2B Founders: * Don't outsource your strategy to self-proclaimed AI search experts — run your own experiments. The foundational models are holding their mechanics close. No LLM has published how its citation algorithm works, which means anyone claiming a definitive playbook is speculating. Kevin's take: build controlled tests yourself. If you hear FAQs drive citations, run 10 pages with FAQs against 10 without, monitor results, and let your own data inform strategy. Borrowed conviction in a fast-moving probabilistic space is a liability. * Ditch daily rank-tracking logic entirely. AI search is probabilistic — the same prompt asked twice can return different citations, different brands, different answers. Applying traditional SEO rank-tracking to this environment will make results look random and uncontrollable, because by that framework, they are. The right measurement model: track brand mention and citation trends across a defined set of high-intent prompts over a longer time horizon. Directional momentum — are you showing up more or less across that prompt set over time — is the signal that matters. * Reddit dominates volume, not value. Reddit shows up heavily in top-of-funnel, high-volume AI queries. But when you isolate the prompts that matter — bottom-of-funnel, higher purchase intent — citations shift toward niche industry publications, many of which most marketers aren't tracking at all. The implication: chasing Reddit presence as an AI search strategy optimizes for the wrong part of the funnel. Find the authoritative niche sources that LLMs are pulling from for your category's high-intent prompts, and get your brand into those. * Your website's primary visitor is no longer human — build for that reality. If buyers are researching inside AI platforms and only occasionally clicking through, the entity actually crawling your pages most often is an AI agent. These bots don't engage with animations, JavaScript, or heavy HTML — they want fast, token-light, structured content. Kevin's framing: AI exchanges value in tokens, so a token-heavy page is a slow, inefficient crawl. The practical path forward is serving two distinct experiences — a full human-facing site and a stripped-down, facts-forward version that AI bots can consume accurately and quickly. Scrunch does this by identifying AI bot traffic at the CDN edge layer via integrations with tools like Cloudflare and Akamai, then serving clean HTML to the bot in real time. //  Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]

Category Design Is a Company Strategy, Not a Marketing Exercise

In this episode of The Marketing Front Lines, we sit down with Daniel Frohnen [https://www.linkedin.com/in/danielfrohnen/], Founder and Fractional CMO at FrohnenGTM [https://frohnengtm.com/], for a masterclass on category design. Dan has worked across the full startup spectrum — from $2M seed-stage companies to Series C organizations scaling past $180M ARR — and he's developed a proprietary framework called the Category Momentum Model that he uses to help B2B founders and GTM leaders build durable, differentiated market positions. The conversation covers how to assess whether a true category creation play is viable, how to get the entire company speaking the same language, and why most teams get the sequence completely wrong. Topics Discussed: * The biggest misconception about category design and who actually owns it * How to audit a company's digital and product footprint to determine the right category strategy * The Category Momentum Model: a four-stage flywheel for building compounding category authority * Why narrative without enablement is just a nice deck that gathers dust * How to train your AI tools on foundational messaging and why it needs to happen monthly * Advice for founders vs. marketers approaching category strategy Lessons For B2B Marketers: * Category Design Is a Company Strategy, Not a Marketing Campaign. The single biggest mistake Dan sees is teams treating category design as a marketing exercise. The CEO has to own it. Marketing runs shotgun. When it lives only in the marketing org, the initiative almost always dies before it gains traction — no matter how well-crafted the narrative is. * Audit Before You Claim. Before declaring a new category, Dan maps the company's digital footprint against its product footprint. Most products touch five, six, or seven subcategories simultaneously. That overlap is where the real signal lives — it tells you whether you can credibly make an umbrella claim the market has never seen, or whether your best move is to own and modernize an existing category. Skipping this step and just declaring a new category is, in his words, "a bit of a fool's errand." * The Sendoso Lesson: Buyer Language Beats Founder Ego. When Dan was at Sendoso, there was internal resistance to the term "direct mail automation" because it sounded old. His pushback: that's exactly what buyers search for and how they remember solutions. Category naming isn't about what sounds cool internally — it's about what buyers actually use to find, remember, and talk about what you do. * The Category Momentum Model: Sequence Matters. Dan's four-stage flywheel runs in a specific order — and most companies get it wrong by starting at stage three. The stages are: (1) category positioning and narrative, (2) product velocity and market signal, (3) demand and channel strategy, and (4) sales enablement and revenue alignment. Companies that jump straight to demand generation without laying the narrative and product foundation typically don't get the compounding effect they're looking for. * Enablement Is a Weekly Practice, Not a Launch Event. Getting the exec team aligned on category strategy is just the beginning. Dan treats messaging enablement the way you'd treat physical fitness — you don't get results by going to the gym once a month. He advocates for weekly enablement cycles, templated messaging that flows from the same core DNA, and making sure AI tools are trained on the foundational narrative and revisited monthly and quarterly as the market evolves. * Train Your AI on Your Category Narrative. With GTM increasingly powered by AI, Dan sees a major gap: teams that haven't fed their foundational messaging into their AI tooling. If your AI is generating content and outreach from a generic base rather than your specific category positioning, you're competing on commodity terms. The fix is treating your narrative as a living document that gets updated and re-ingested as the market shifts.

Why Category Creation Is a Trap (And What Actually Works)

In this episode of The Marketing Front Lines, we sit down with Andrea Bailiff-Gush [https://www.linkedin.com/in/andreabailiffgush/], Head of Marketing at Reco [https://www.reco.ai/], a SaaS security and AI governance company. While most guests on shows like this make the case for category creation, Andrea does the opposite — drawing on a failed category launch, years in cybersecurity marketing, and a front-row seat to the AI security space to explain why the strategy fails far more often than it succeeds, what the real warning signs are, and how sophisticated marketers can stand out without creating a category at all. Topics Discussed: * Why category creation is often a solution to a company problem, not a customer problem * The "Decision Augmentation" failure: what went wrong and why * The three hell-no signals that mean you should abandon category creation * Why you can't have a category of one — and why competitors won't save you * How Gong got it right (and what most companies get wrong when they try to copy that playbook) * How AI is going to upend analyst relations and category-based buying altogether * What to do instead: descriptive positioning, differentiation without category creation * Book recommendation: Play Bigger Lessons For B2B Tech Marketers: * Category Creation That Solves Your Problem, Not the Customer's, Will Always Fail The most common mistake Andrea has seen across high-growth startups is using category creation as a solution to a business growth problem rather than a buyer pain point. Her own experience launching the "Decision Augmentation" category — which was supposed to reframe a PR tool in the age of early AI — is the case study. The campaign had strong thought leadership, analyst investment, and even a conference "lightning strike" moment. It still fell completely flat because customers didn't recognize the pain it claimed to solve. The diagnosis: the company was trying to fix its own positioning problem, not a real gap in the market. Before any category conversation starts, the only question that matters is whether your buyer is actively feeling a pain that no existing solution addresses. * The Three Hell-No Signals for Category Creation Andrea's framework for when to kill the idea immediately: (1) There's no clear, unmet pain — if customers aren't frustrated with existing solutions, there's no whitespace. (2) Existing solutions are already meeting the pain adequately — you'd be creating confusion, not clarity. (3) Buyers aren't asking for a new way to think about the problem. If your customer interviews aren't surfacing language that points toward a gap in how the market is organized, you're ahead of the market in a way that will cost you enormously to bridge. * You Cannot Force a Category Into Existence — and You Can't Have a Category of One A category only becomes real when buyers recognize it and when multiple companies orient around it. One of the reasons "Decision Augmentation" failed is that no other company associated themselves with the term — it was a category of one. Practically, this means that if you're serious about creating a category, you need third parties (analysts, industry publications, research firms) to bucket multiple players together. Companies can't do this alone, and founders who think they'll get competitors to collaborate are usually in for a rude awakening. * The True Cost of Category Creation Is Wildly Underestimated The resource requirements aren't just financial. You're committing your marketing team and product team to sustained market education — the equivalent of a full rebrand in terms of internal lift. You'll need a serious PR investment, deep analyst relations work, and company-wide evangelism. Andrea points to the SaaS security category: five years in, with consistent market education investment, Gartner still doesn't recognize it as a standalone category. One founder Brett spoke with spent eight years and raised $400M before Gartner created the magic quadrant for his space. If you're a Series A or B company, this math almost never works.

How Redis trained a custom GPT on rebrand documentation to automate brand compliance | Adam Haskew

In this episode of The Marketing Front Lines, we sit down with Adam Haskew [https://www.linkedin.com/in/adamhaskew/], Associate Director of Brand Experience at Redis [https://redis.io/]. Adam leads the verbal identity of the Redis brand — everything from trade show copy to website language — as one of three people on the Brand Experience team. Faced with a small team, a growing content demand, and an organization already reaching for AI tools, Adam didn't wait for someone else to build the infrastructure. He built it himself: a custom ChatGPT trained on Redis's brand voice, style guide, and buyer personas, now being piloted with 12 people ahead of a full marketing-wide rollout. Topics Discussed: * Why a three-person brand team needs AI infrastructure more than most * What to actually feed a custom GPT to make it produce on-brand content * The three core functions Adam built into the Redis Brand GPT * How to think about AI "tell" auditing before content goes live * Why user testing is the most underrated step in GPT deployment * How to prompt-engineer for both the machine and the human on the other end Lessons For B2B Marketers: 1. Assume Your Team Is Already Using AI — Then Get Ahead of It Adam's trigger for building the Redis Brand GPT wasn't a top-down mandate. It was the recognition that people were already reaching for ChatGPT in their day-to-day work. Rather than fight it or ignore it, his team asked: how do we channel that behavior toward on-brand outputs? If you're a brand or content leader, this is your call to action. The question isn't whether your team is using AI — it's whether they're using it with any guardrails. 2. Your Brand Artifacts Are Already GPT Training Material The raw inputs for the Redis GPT weren't novel — they were documents the brand team had already produced: voice and tone guides, style sheets, buyer personas, and strong content examples that served as quality benchmarks. The insight here is that a recent rebrand or a well-documented brand system is essentially a GPT curriculum waiting to be uploaded. If you've done the brand work, the AI infrastructure work is closer than you think. 3. Build for Three Distinct Use Cases, Not a Catch-All Rather than positioning the Redis Brand GPT as a general-purpose writing tool, Adam scoped it around three specific functions: (1) guided content brief creation, (2) on-brand first draft generation, and (3) review and audit of existing content against voice, tone, and accuracy standards. This narrow scoping is what makes the tool reliable. Generic AI outputs fail because the inputs are vague — building with specific jobs-to-be-done in mind forces precision on both ends. 4. Build an AI "Tell" Audit Into Any Brand GPT One of the more tactical features Adam built was an automated check for AI giveaway patterns — overused em dashes, generic phrasing, the linguistic tics that signal machine-generated copy to a trained eye. If your brand is producing AI-assisted content at scale, this kind of audit layer isn't optional. It's the difference between content that reads as human and content that quietly erodes brand credibility. //  Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠ [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠ [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: ⁠https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]

What’s the ROI of Bringing a Horse to Wall Street? (Ft. Alex Mann)

In this episode of The Marketing Front Lines, we speak with Alex Mann [https://www.linkedin.com/in/alextmann/], Head of Growth at Lunos [https://www.lunos.ai/], an AI startup transforming accounts receivable. In a crowded market where every B2B AI company looks identical—same fonts, same color schemes, same website layouts—Alex took a radically different approach. Instead of pouring money into LinkedIn ads and traditional demand generation, he brought a horse and cowboy to Wall Street, sent cowboy hats to prospects, and built a content engine that generated more pipeline than any ad campaign could deliver. Through stunts that cost a fraction of typical CAC, Alex demonstrates how early-stage startups can break through the "sea of sameness" and create memorable brand moments that drive real business outcomes. Topics Discussed: * Breaking through B2B marketing sameness with provocative stunts * The economics of stunts vs. traditional paid acquisition * Securing permits and executing a Wall Street horse stunt for under $4K * Converting viral moments into sustained pipeline generation * Building content halos from single marketing events * Navigating founder buy-in for unconventional marketing tactics * Escaping the CAC addiction cycle in early-stage startups * Positioning AI agent products that don't compete with traditional software Lessons For B2B Tech Marketers: * Invest in Stunts as Content Opportunities, Not CAC Plays: Alex reframes stunts entirely—they're not direct response vehicles, they're content goldmines. The horse stunt cost $3,500 total ($3K donation to animal shelter, $500 in permits) but generated months of LinkedIn content, email campaigns, and pipeline conversations. Every prospect referenced seeing "the horse everywhere." Calculate ROI based on content volume and brand recall, not immediate conversions. * Use "One Quote Per Source MAXIMUM" Cold Email Strategy: After the horse stunt, Alex sent a cold email with the subject line "You must open this email right now" to accountants, achieving a 70% open rate. The email told the story of the stunt with a link to a LinkedIn post that had hundreds of likes. This created social proof for an entirely cold audience at near-zero cost, demonstrating how viral content can make cold outreach feel warm. * Apply the "Thanksgiving Turkey" Content Model: Borrowed from LinkedIn's Jason Miller, this approach treats major marketing moments like a Thanksgiving turkey—the initial event is valuable, but the real ROI comes from repurposing it into "soup, sandwiches, and leftovers." One podcast recording becomes audio clips, newsletter content, blog posts, LinkedIn quotes, and multiple content formats. Plan stunts with maximum repurposing potential built in from the start. * Recognize When You're Selling to People, Not Competitors: For AI agent products specifically, Alex identifies a critical positioning advantage—you're not competing with other software in an apples-to-apples feature comparison. You're competing with human labor and manual processes. This creates "green space" for brand creativity since there's no incumbent feature set to defend against. Use this freedom to build distinctive brand personalities that explain fundamentally new value propositions. * Send Physical Gifts That Demand Social Sharing: Inspired by Unify and Default's Series fundraising stunts, Alex sent cowboy hats to prospects with one simple ask: take a selfie and post it. The execution was expensive and complex (sourcing hats, designing multiple box layers for shipping damage, individual FedEx costs), but it generated significant pipeline from people who saw others posting about it. The key insight: the gift must be photogenic and aligned with your brand narrative. * Escape CAC Addiction Before It Starts: Alex warns that LinkedIn ads become "very hard to turn off" once you start—you get reliable pipeline, but at $150+ per contact and increasing CAC over time. For pre-seed through Series A companies spending $5-20K/month, there's limited optimization runway, and your marketing becomes "less about creativity and more about CAC." His alternative: invest that budget in 2-3 major stunts per year that create lasting content and brand differentiation. * Understand the Two B2B Buyer Personas: Alex simplifies B2B audiences into two groups: (1) Senior leadership asking "How do we save/make money faster?" and (2) End users saying "Please save me time, my job is killing me." Both groups are humans who watch Westworld, use Instagram, and appreciate personality. Stop treating B2B buyers like they're different people outside of work—they respond to the same creative, memorable content as consumers. * Execute "On The Line" Marketing: Position your brand between "boring as fuck" and "prison"—right on the line where things get interesting but not offensive. Be provocative without punching down. In AI/tech startups specifically, there's enormous room to "punch up" at the sameness of competitor positioning. The goal: create permission structures within your organization to take creative risks that make your 50-person startup look like a 500-person company. //  Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io [http://www.frontlines.io] The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co [http://www.globaltalent.co] // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM [https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM]