Phill Brougham

They call this a 'bulldozer problem': the most senior person ploughs through competing evidence and points of view.

• The cost emerges downstream.
• Sales reps develop edge use cases they can sell, demand generation promotes content that misses the official value story, product marketing starts writing informal new messaging, and buyers see one message on the website and another in conversation.
• Deals slow, pilots multiply, and competitors get a look in.
• Brougham distinguishes this from stubbornness: it is loyalty to a formula that once worked.
• The fix is 'updating the map, not changing the vehicle' — grounding conviction in what the market is telling you now.

The post opens with the line 'Your CEO says: "We shouldn't change our messaging, this is who we are"' and describes a first-time head of marketing who knew the target customer but also knew the current value proposition was not converting. The original value proposition had carried the company from seed to Series C, and that history made it comforting; the market signals they had gathered from account executives, customers, and demand generation felt useless in the room.

The same principle appears in the AI contact center post, applied to the gap between features and outcomes rather than an executive’s conviction.

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The underlying mistake is assuming features equal value.

• The team should have asked what value the product delivers that customers cannot get today: buyers can see themselves in an outcome, but not in someone else’s feature.
• Messaging built on outcomes and tied honestly to what the product actually does is what carries a company past its first fans.

Their first product marketing role was at an AI contact center automation company with strong logos and cutting-edge technology, including deep learning.

• The first year went well, but expanding beyond technology evangelists became 'a really painful battle for both sales and marketing', no matter how many AI and automation features were added.
• The closing formula is blunt: features excite early adopters; outcomes move the rest of your market.

The same priority appears in the VBF ordering Brougham recommends from Emma Stratton's book: value proposition first, then benefits, then features. It puts customer pain and challenge at the front.

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Workflows and tooling are still being productized, and much of what currently works is experimental.

• Leadership’s demands for regular proof of AI use push teams to read and test everything while learning little about what actually changed.
• Brougham proposes three measures instead: efficiency (did the work actually take less time), impact (did it free time for higher-value work such as deeper thinking, strategy, or preparing a hard conversation), and KPIs (did anything move a business outcome).
• The advice: curate sources, take regular breaks from AI learning, and ask whether using AI changed anything for the better.

The post describes marketers reading three Substacks, ten LinkedIn posts, and two 'ultimate guides' a week and still feeling behind, with leadership adding pressure through recurring updates on how teams are using AI. Brougham recommends Emily Kramer of MKT1, Maja Voje, and Product Marketing Alliance as sources.

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The idea is VBF: the value proposition is the transformation customers buy and the reason they purchase; benefits are what the product lets customers do, feel, or have; features are the things in the product that make the benefits and value proposition possible.

• The order matters because it starts with customer pain and connects it to the product.
• Brougham also argues that the book is not only for marketers, since what a company says shapes revenue, its reputation with investors, and its relationships with customers.

Brougham came close to hiring messaging specialist Emma Stratton two years earlier.

• They had a first call, then delayed until the budget was gone.
• The next-best option was buying and reading Stratton's book 'Make it Punchy'.
• The post states the missed chance and lost budget plainly while crediting the framework to the author.

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They apply that to a career reset, a missed chance to work with an expert, and a messaging mistake from an early role. It reads as a working preference as much as a style: the posts state what went wrong, what remains unknown, and what comes next.

The freelance announcement describes discomfort with posting on LinkedIn, a restructuring at the beginning of 2025, time spent travelling and reading about career pivots, and a career that had run 'on autopilot' from one job to another.

• The concrete decision is to go freelance as a product marketer, work with a small group of clients, and build a website, define offerings, and test services, while the direction takes months or years to settle.
• It closes by offering help to anyone considering a career change or wanting to learn about product marketing.

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Start here for the core argument, stated concisely and backed by a failure.

Brougham describes their first product marketing role at an AI contact center automation company.

• Strong logos and advanced technology carried the first year, but growth stalled when the company tried to sell beyond technology evangelists.
• The messaging was feature-led: it worked for early adopters, but not for more skeptical buyers, no matter how many AI and automation features the team added.
• In hindsight, the missing question was: “what is the value thing that our product does for our customers that they can't do today?”
• The durable idea in the post's closing line: features excite early adopters; outcomes move the rest of your market, because customers see themselves in outcomes but not in features.

For brands planning a campaign

Useful for a brief on repositioning a technical product for buyers beyond the early-adopter stage. Brougham's framing gives the campaign a starting question and a clear audience split—early adopters versus the broader market—rather than a general claim about good storytelling.

Brougham recounts being a first-time head of marketing, knowing the target customer, and knowing the current value proposition wasn't converting.

• The core product and its original value proposition had carried the company from seed to Series C; that past success served as evidence of its own, despite what the market was showing.
• Brougham traces the consequences of the gap: sales reps develop edge use cases they can sell, demand generation promotes content that misses the official value proposition, product marketing writes informal new messaging, and buyers hear one story on the website and another in conversation.
• Deals slow, more pilots and proof-of-concepts appear, and competitors enter.
• Brougham calls this value erosion and names the executive pattern a “bulldozer problem,” where the most senior person plows through competing evidence.
• The distinction matters: this is loyalty to a successful formula, not stubbornness.
• The fix is to update the map, not change the vehicle.

For brands planning a campaign

Relevant when a campaign needs internal agreement before it can run. The post offers language for describing the gap between brand messaging and sales reality, along with observable symptoms—slower deals, more pilots, more competitors—to make the case to a skeptical executive.

It's the most practical of the posts, with a short measurement list readers can act on.

Brougham reports talking to marketers who read several newsletters, posts, and long guides each week and still feel behind on AI, while leadership amplifies the anxiety with recurring updates on how teams are using AI.

• Their argument: AI for marketing is still in a formation phase, with workflows and tooling being productized and much current practice experimental.
• Demanding proof of expertise in tools still being built creates activity without clarity.
• Instead of proving familiarity, Brougham suggests measuring efficiency (was time actually saved?), impact (was time freed for higher-value work such as strategy or planning a hard conversation?), and KPIs (did anything move a business outcome?).
• The post closes with three pieces of advice: curate sources, take regular breaks from AI learning, and ask whether AI use actually changed anything for the better.

For brands planning a campaign

Offers a concrete evaluation frame for campaigns aimed at marketers under pressure to adopt AI, whether focused on AI tooling, enablement content, or thought leadership. The three measures—efficiency, impact, KPIs—can anchor a content series or webinar instead of another list of tools.

It's the clearest explanation of a working model in these posts.

Brougham describes almost hiring messaging specialist Emma Stratton two years earlier, losing the budget, and later reading Stratton's book 'Make it Punchy' instead.

• They summarize one concept from it: VBF, meaning value proposition, benefits, features.
• The value proposition is the big transformation or achievement for customers and the reason they buy; benefits are what the product lets customers do, feel, or have; features are the things in the product that make the benefits and value proposition possible.
• Brougham notes that the order puts customer pain and challenges first, then connects them to the product.
• They say the book is useful beyond marketing—for founders, leadership, product, and sales teams—because messaging affects revenue, reputation with investors, and customer relationships.

For brands planning a campaign

A ready-made structure for a messaging workshop, positioning document, or campaign narrative review. The order is the recommendation: value proposition, then benefits, then features, with customer problems at the front.

It's the right starting point for anyone weighing whether to engage Brougham for project work.

Brougham writes about being uncomfortable posting on LinkedIn, then describes a restructuring at the start of 2025, taking time to travel and think about a career, speaking with people in their network, and reading books on career pivots.

• They describe much of their career before that as running on autopilot, going from one job to another without asking difficult questions, and say figuring out what comes next will take months or years.
• The concrete decision is to go freelance as a product marketer, working with a small group of clients while building a website, defining offerings, testing services, and having more conversations.
• Brougham thanks named former colleagues and managers for guidance and invites anyone considering a career change or wanting to learn about product marketing to reach out.

For brands planning a campaign

Sets expectations for working with Brougham: independent, project-based, currently building out service offerings, and open to new conversations. Useful context for brands considering an agency team or a large ongoing engagement.

They trace the downstream costs: sales reps develop edge use cases they can sell, demand gen promotes content that is not the official value story, and product marketing starts writing informal messaging.

• Buyers then encounter something different from the brand's top-line promise, and deals slow.
• The post calls the pattern "value erosion" and its cause a "bulldozer problem" — the most senior person ploughing through evidence and competing views.
• The proposed fix is accountability to what the market is saying now, rather than loyalty to a formula that once worked.

Uses a first-person decision story, names a dynamic and traces a before-and-after sequence, helping readers recognise the same pattern in their own company.

For brands planning a campaign

Strong fit for narrative and messaging work when a marketing or product marketing leader needs an outside voice to make the case to a sceptical executive team. The value lies in aligning leadership, not just rewriting copy.

Examples: Source 1

That worked with early adopters but could not win more cautious buyers, however many AI and automation features were added.

• The team assumed features equalled value and never asked what outcome the product delivered that customers could not achieve today.
• The post argues that messaging built on outcomes, tied honestly to what the product does, carries a company beyond early adopters: customers can see themselves in an outcome, but not in someone else's feature.

A retrospective first-person case that presents the failure, the wrong assumption and the corrected principle in that order.

For brands planning a campaign

Useful for AI-first and technically complex products that have proven the early adopter market and now need messaging for mainstream buyers. Brands can ask for a review of where their current messaging remains feature-led.

Examples: Source 1

The post credits the author, says the book is worth reading without spoiling it, and explains how the resource supports their freelance work, particularly current messaging projects. It also returns to a habit of being honest about what changed and what did not: missing the chance to work with a named expert, losing the budget and finding the next-best option.

A short recommendation post that teaches one framework, names its source and applies it to the writer's own client work.

For brands planning a campaign

Signals an opening for co-marketing or educational collaborations with authors, tooling vendors and training providers, as well as brands that want a practitioner to explain a framework rather than invent one.

Examples: Source 1

The argument: AI for marketing is still in a formation phase, with workflows and tooling emerging and much of what works remaining experimental.

• Pressure to appear expert leads to plenty of reading and updates but little clarity about what moved the needle.
• The post proposes three measures: whether time was actually saved; whether time was freed for higher-value work such as deeper thinking or planning; and whether anything moved a KPI.
• It recommends curating sources, naming Emily Kramer of MKT1, Maja Voje and Product Marketing Alliance, and taking regular breaks from AI learning.

Lists the felt problem, reframes it, then poses three measurement questions and offers practical recommendations.

For brands planning a campaign

Relevant for AI marketing vendors: expect a sceptical, measurement-first reception and lead with concrete time saved or business outcomes rather than novelty. A commentary or webinar that tests AI use against results is a natural fit.

Examples: Source 1

They are candid that posting on LinkedIn feels as uncomfortable as early Facebook statuses and that their career direction is not fully worked out.

• The plan is to keep learning, work with a small group of clients, build a website, define the offerings, and keep testing and having conversations.
• They close by offering help to others considering a career change or wanting to learn more about product marketing.

For brands planning a campaign

Sets a practitioner-to-practitioner, reflective tone rather than a vendor-promotional one. Relevant to brands whose audience includes product marketers and career changers.

Examples: Source 1

They plan to keep using it on current messaging projects. The post says a former employer came close to hiring Stratton as a consultant but never signed her; it does not say they worked together.

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Like Brougham, uses practitioner observation to argue that messaging should address the customer's actual situation.

Sifers often frames the argument around emotional transitions and buyer empathy, and one post turns to sales enablement and pipeline concerns. Brougham focuses more on messaging fundamentals, value erosion when leadership resists change, and feature-led versus outcome-led positioning.

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They write short, practical LinkedIn posts for marketing leaders.

Lodge's posts target founders and small marketing teams, emphasizing ownership, accountability, and operating cadence. Brougham focuses more on product-marketing messaging, AI pressure, and lessons from early-career mistakes.

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Both push product marketers to tie launches and messaging to evidence about what buyers actually want.

MacKinnon's posts use survey numbers and include a clear vendor call to action for Wynter. Brougham's posts use personal narrative and argument without promoting a product, focusing more on messaging change, value proposition, and AI-related measurement.

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Sifers writes directly to that, framing product marketing as a pipeline function rather than a support function and listing the five concerns sales leaders raise most often, each paired with a product marketing response: validated messaging mapped to buyer pain and trained repeatedly, competitive battlecards rebuilt from win/loss analysis, sharper ICP targeting for outbound, mid-funnel content that speaks to every stakeholder including the CFO who now signs off on most B2B technology purchases, and onboarding that covers positioning, personas, competitive landscape, and objection handling.

• The post also names the operating conditions that make this work: bi-weekly sales and product marketing syncs instead of chat messages, product marketers riding along on discovery calls, honest feedback from sales leaders on what is landing, and shared pipeline metrics rather than separate activity metrics.
• For a company that needs reps and demand generation to carry a new narrative into conversations, that is a more concrete enablement plan than Brougham's posts provide.
• Sifers also writes about the human side of a purchase — the looming deadline, the anxiety of recommending the wrong tool, the exhaustion of juggling systems that do not talk to each other — and argues that the best product marketing acknowledges the human experience of the problem.
• That is useful when buyer research is thin or a technically accurate message is landing as cold.

The tradeoff is diagnosis versus delivery.

• Sifers's posts assume someone has already produced a defensible positioning and messaging decision; they focus on enabling sales to use it, not rebuilding it when a company's old value proposition no longer fits the market.
• Brougham's material covers that earlier moment: a first-time head of marketing at an AI contact center company where feature-led messaging won early adopters and then stopped working, and the internal pattern they call value erosion, where reps invent edge use cases, demand generation publishes off-message content, and product marketing writes informal messaging until the buyer's experience no longer matches the website.
• They also supply a compact structure for the rewrite — value proposition, benefits, features, ordered with the customer problem first, credited to Emma Stratton's book Make it Punchy — and a three-question test for whether messaging work was worth doing: did it save time, did it free time for higher-value work, did it move a key metric.
• Sifers's sales-enablement program is a heavier commitment than a messaging project, and it needs a sales leader willing to share pipeline metrics and give product marketing honest feedback; without that partner, the cadence advice has nowhere to land.
• Read the two Sifers posts in full before deciding.

Examples: Source 1 · Source 2

Lodge's account of positioning is unusually direct about the organisational cause of weak messaging: at a company past roughly fifteen million in revenue, the homepage headline has typically been rewritten several times in a year by several different people, because positioning was never settled by the people who have to live with it.

• Lodge's prescription is that positioning is a collective decision — chief executive, sales, product, and customer success leave one room with the same answer about who the company is for and why buyers should choose it over the alternative — while messaging is how you say it, and that part belongs to marketing.
• Everyone should contribute feedback, because sales, product, and customer success each see customer conversations marketing does not, but messaging research and customer interviews in the customer's own words should outrank preferences and opinions.
• Lodge also frames small-team management sharply: handing a marketer a task list makes them responsible for activity, while giving them an accountability makes them responsible for an outcome, and a single clearly owned outcome this quarter is enough to start.
• Use Lodge when a founder or chief executive keeps rewriting the message, when nobody can say who owns it, or when a one-person marketing function is being judged on activity instead of results.

The tradeoff is that governance advice does not write the new narrative.

• Lodge explains who should decide and how to keep opinions from muddying a researched messaging project, but the posts do not show how to move a company whose product story has aged out — the situation in Brougham's posts, where a value proposition that carried a company from seed to Series C is no longer converting and the market has shifted underneath it.
• Their account of that moment names the internal dynamics a governance change has to overcome: an executive loyal to a formula that once worked, quiet peers at the table, and the erosion that follows when each team quietly works around the official story.
• Lodge's examples lean toward smaller companies and a specific buyer context — one post asks whether the content says anything a health system buyer would care about — so a larger software organisation with an established marketing department may find the accountability lesson less relevant than the positioning-ownership one.
• If leadership disagreement is the blocker, Lodge is the stronger starting point; if the message itself has to be rebuilt and tested against outcomes, Brougham's diagnosis-and-structure approach pairs well with Lodge's ownership rule — and the two can be combined rather than treated as substitutes.

Examples: Source 1 · Source 2

MacKinnon's work is survey-based.

• In one post, after asking 100 B2B software product marketers to describe a real feature launch that underperformed, roughly 55% of coded answers pointed back to the same missing step: stronger problem, demand, ICP, or market validation before anything was built.
• The post lays out the foundational questions those marketers wished had been answered before engineering committed — is this a real problem, is it painful enough that anyone changes behaviour, how many target customers have it, which segment cares most, do they want the proposed solution, will it improve adoption, retention, or revenue, is it worth building now — and traces the sequence that skips them: an internal idea, a competitor with something similar, one large customer who asked once, leadership excitement, a mock-up, a roadmap slot, and political investment in shipping before product marketing's questions arrive.
• In the second post, MacKinnon isolates the 66 respondents at companies of 50 to 999 employees and compares high-release-volume teams against moderate and low-volume teams: 85% against 38% said they are overloaded by launches, 88% against 50% said launch-support work has increased, and 50% against 12% said release volume is diluting the company's core positioning.
• MacKinnon's conclusion is not to stop shipping but to raise the burden of proof on what gets built and what earns serious go-to-market support, and to accept that some releases belong in the release notes and nothing more.
• That is the right material when the internal argument is about volume, sequencing, and where product marketing effort should go.

The tradeoff is that this is market research with a product attached, not a hands-on messaging engagement.

• Both posts end by directing readers to Wynter, the buyer-research platform, and offer a demonstration, so the content is built to demonstrate a research tool's value; the figures are what respondents reported in those surveys, and the posts do not describe delivering a messaging or positioning project for a client.
• If the need is a rewritten narrative, a workshop that reconciles sales, demand generation, and product marketing, or a public teaching series, MacKinnon's posts do not show that work — Brougham's do, including the VBF structure and the three-question test for whether AI-assisted marketing work actually saved time, freed time for higher-value work, or moved a metric.
• MacKinnon's material is also heavier to act on: it implies a recurring research budget and a willingness to gate the roadmap on buyer research, a bigger organisational change than a one-off messaging project.
• A practical option is to use MacKinnon's survey framing to win the internal argument about launch volume, then bring in a practitioner such as Brougham to do the messaging work itself.

Examples: Source 1 · Source 2