Sr. Growth Manager @ ActiveCampaign | Institutional Consultant | Founder

Casey is a growth veteran, with over a decade of experience in helping software companies scale fast. 

Whether it's garnering 28,000,000+ views across Linkedin, Reddit and Quora, or pioneering new growth levers (like booking his team on hundreds of podcasts), Casey is always looking for creative and value-led ways to grab attention and break from the mold. In his current role leading marketing at DoWhatWorks, he is looking to reshape how brands split test and experiment online. 

On the consulting side, Casey has worked with some of the world's biggest firms including places like McKinsey, Blackrock, Colemans, GLG, Guidepoint, etc., where he provides institutional guidance to PE/VC teams around topics such as: SMB marketing vendor selection, SaaS pricing, SaaS marketing/CRM tool differentiation, market analysis, inbound marketing, conversion rate optimization and marketing automation.

Casey also teaches classes at UCSD and Stanford extension around demand creation, email marketing and content marketing.

I run a Substack that does analysis on the world's top websites based on our proprietary database of A/B test results: https://dowhatworks.substack.com/

Current areas of extensive experience...

-> B2B SaaS / B2B Enterprise SaaS / SMB SaaS

-> CRO (Conversion Rate Optimization) / Website optimization

-> Email marketing

-> Content marketing (especially LinkedIn and Reddit)

-> B2B Influencer marketing

-> Pricing optimization

Casey Hill

I looked at over 50 competitor comparison pages. PostHog had the best ⬇️

Let me start by saying that most competitor comparison pages are dreadful.

They are dishonest (like factually inaccurate about the competitors).

They are misleading. They don’t build trust. They treat the prospect like they are dumb.

And here is the kicker… they don’t convert. 

I have worked with a handful of marketing teams (startups to at-scale orgs) who have shifted retargeting budget away from competitor comparison pages because the CPA was just too high (one spent $800k/m for a quarter and had just 7 sales at a 5-figure ACV)

It makes sense to educate prospects about your strengths (and even mention competitor weaknesses), but the framing is what is killing all these pages.

With Posthog, they do several things that build trust and buck the trend:

1) When describing a competitor, they quote how the competitor describes themselves. No misrepresenting or trying to paint them into a certain box. Just be straightforward.

2) They include a “what people like about [competitor]” and “What people don’t like about [competitor] and then include quotes from reviews (I think they pull from G2). And the real part that builds trust is that they include honest positives. Not weird, fake compliments, “this is a perfect software if you are an enterprise org with 5,000+ employees and a $12 million a month budget for all the consultants you will need”. Just actual strengths. It then makes the weaknesses that they bring up next feel way more realistic. 

Ultimately, the most effective competitor comparisons start with honesty.

That in and of itself is so rare, it’s disarming, and builds trust and confidence in whatever you say next. 

Have you read a competitor comparison that really resonated (or created one that converted really well)?

Chief Marketing Officer @ DoWhatWorks | Institutional Consultant | Founder

I lined up a call with a top executive to talk through their A/B testing learnings. 

Then it went completely off course…

Them: “Yeah I ran a bunch of tests this quarter. Nothing works. Headline tests, section tests, button tests. None of it moved the needle. Not a focus area any more”.

I listened and took it all in. I had all these notes. 

All this data to compare against their test results. These follow up questions lined up to get into the “why it won”. 

But none of it worked for them. It wasn't even that the variants "lost", they just were the same. They didn't matter.

We still had a nice chat, but after I got to analyzing his situation.

I realized the experience of this exec is actually exceptionally common. 

Optimizely published data saying that 90% of A/B tests "lose" (as in the variant doesn’t show any statistical difference so they stay with the control).

A big part of the problem stems from how we approach testing. 

1. Do we really understand where our traffic comes from and how that impacts positioning? If your traffic comes from paid retargeting ads or if it comes from dark social, what resonates will be very different.

2. Do we design A/B tests with a specific, unified problem we are trying to solve for? Many brands just do a dozen homepage hero headline variants and try and see what wins. But the question always has to be what problem are you solving for? Everything should ladder up to that.

3. Are you testing things that are meaningful? A big gap I found from my chat with that executive was a lack of “meaningful testing”. This means you try 10 copy variants but none of them a) introduce new information or b) provide new direct value. 

I am teaming up with the incredible team from GrowthX AI this Thursday (9AM PST) to do a workshop, where we will get deep into how to better convert your web traffic in 2026. 

Not only will we look at specific A/B tests from dozens of the top brands in the world, but we will address what to test, and how to think about your website in an age of AI discovery.

There is a major problem across AI companies selling agentic products ⬇️

They are unbelievably vague in their messaging. 

I curated a list of 30 top companies selling agents. 

Here are the headlines…

Company A: “We are a frontier research and deployment company providing enterprises with a powerful, cost-efficient, and easy-to-adopt technology to integrate agentic AI directly into their core workflows and processes.”

Company B: “Deploy, orchestrate, and govern fleets of specialized AI agents that work alongside your team”

Company C: “Ops teams can build and manage an entire AI workforce in one powerful visual platform.”

Company D: “[company] is the simplest way for businesses to create, manage, and share agents.”

It took me until company eight on the list that I got one that actually gave me any real information about what it did.

Company H: “Docket's AI agent handles qualification, discovery, and booking while you sleep. Teams see 30%+ more qualified pipeline from the same traffic.”

I understand these brands want the optics of addressing a large TAM, but when you can go to ten sites, and the headlines are almost identical, this isn’t providing any clarity or insight that is helping prospects decide on your product.

What does the data say 💡: I looked at DoWhatWorks database of hundreds of A/B tests around AI messaging. Tests from brands like OpenAI, IBM, Hootsuite, GoDaddy, Notion, and beyond. The takeaway is clear → AI messaging that is clear and explanatory to the capability it solves for (i.e. our support agents provide 24/7 ticket coverage in 42 languages) dramatically outperforms vague or sweeping messaging.

Juan Bello

Co-founder at Porter (No-code marketing reporting for teams and agencies) 📊

I'm co-founder at Porter Metrics, a startup that automates cross-channel marketing reporting for teams and agencies.

We've +1,500+ customers in 60 countries including Oracle, Johns Hopkins University, Visual Capitalist, Globant, and Havas. 

We're building agents on top of this data—that we've built for years—to automate marketing operations tasks. Think of an n8n for marketing. 

I'm always looking to talk to great marketers who are both technical and creative.

Co-Founder

At Porter, we connect apps to reporting tools. Think of Zapier for data reporting.

We started by automating marketing agencies reporting on Google Data Studio and Google Sheets.

Las ideas de startups no vienen de epifanías.

Netflix, supuestamente, nació porque Reed Hastings pagó $40 en multas de Blockbuster por no devolver Apolo 13.

Pero en "Esto no Funcionará" la historia es más aburrida: al principio pensaron en enviar VHS y DVD, no en innovar con streaming.

Y a Marc Randolph, el autor, seguro no le apasionaban los medios audiovisuales; literal buscaba "qué vender por internet". 

No tengo muchos ejemplos de hackatones o incubadoras que realmente hagan más allá que "jugar a emprender". Solo Zapier, se me ocurre de ejemplo. 

En Porter Metrics pasamos más de un año haciendo cámaras para contar personas en tiendas físicas (y medir tráfico y tasa de conversión). 

Conseguimos nuestro primer cliente grande y llegó la pandemia. Se cerraron todas las tiendas. 

Por diversión había hecho un curso de Data Studio en Platzi. La gente me preguntaba cómo conectar sus datos "barato".

De ahí salió Porter.

Con AI el camino es más incierto porque no puedes solo copiar algo y hacerlo más barato (el costo marginal del software es 0, esa estrategia no funciona).

Y cuando crees que algo no es posible, hay una startup —con o sin millones— que demuestra que sí lo es.

Es muy divertido, y hasta romántico, escribir una visión de producto. Pero la realidad es más simple: es salir a vender. 

La gente de ventas (y marketing) es tan importante como los que crean producto. 

La resiliencia (o terquedad) le gana a la genialidad.

Co-Founder @ Porter Metrics | Marketing Operations Agents

La explicación más simple suele ser verdadera. 

Hay un blog de marketing analytics llamado Occam's Razor de Avinash Kaushik que sigo hace años. 

No tenía ni idea que "Occam's Razor" significara algo. 

Se refiere al principio de que la explicación más simple suele ser correcta. 

En marketing muchas variables pueden explicar por qué el rendimiento es bueno o malo. Es culpa de:

✅ El creativo
✅ El copy
✅ la landing page
✅ el formulario
✅ El canal
✅ La campaña
✅ El equipo
✅ El mercado
✅ La temporada

Y si uno se esfuerza lo suficiente, va a encontrar 100 razones por las que algo no funciona. 

Si uno se esfuerza un poco más—y se enfrenta a la verdad—la razón es: 

✅ el producto no resuelve un problema
✅ el mercado no le importa lo que haces
✅ Tu oferta no es relevante para una audiencia

Todo lo demás tiende a ser marginal. 

La explicación más simple suele ser verdadera. Simple no es igual a fácil.

Así es como escribo mi "plan de marketing" en 2026. 

❌ No escribo un plan anual (ni mensual). 
❌ No lo escribo para "compartirlo" con el equipo.
❌ Rara vez vuelvo a leerlo.

Lo hago solo para tener claridad mental. 

No pienso el marketing a nivel de "campañas" o "proyectos" sino como productos.  

En una página escribo:
✅ Misión (qué hace Porter)
✅ Usuario (Para quién)
✅ Objetivo (Para qué)
✅ Posicionamiento (Cómo ser diferente)
✅ Casos de uso (Qué problemas resuelve)
✅ Lista de tareas (En qué orden) - Intención comercial y distribución


Cosas no oficiales que también miro:
❓Si me parece emocionante/ambicioso
❓Si soy la persona/equipo ideal para hacerlo
❓Si lo puedo hacer aún más corto (que ojalá no sobre ni una palabra, un gusto culposo) 

Podría hacerlo más extenso y complicado, pero eso sería más fácil.

Así es como usamos AI en marketing en Porter Metrics.

Con Daniela Estefania Gómez De Almada de The Growth System. 


Internal tools:

✨ Estamos creando nuestras landing pages para WordPress con un page builder interno.

✨ Workflows a los que les damos nuestros datos de marketing y documentación para que analicen los datos tal como yo lo haría. 

✨ Estoy creando slides con Google AI Studio (no con Canva o Gamma). Me pareció súper útil para un tutorial que estoy montando de "BigQuery para marketers" porque crea tablas y visualizaciones que me tomarían mucho tiempo en Canva. 

✨ Ahora, estamos usando Airtable para crear páginas y contenido a escala, de forma programática. Ya estamos creando una herramienta interna para reemplazar Airtable. 

Disclaimer: 
💀 Tuve el "hype" de que "cualquiera" podría ser frontend developer, pero eso no va a pasar. Yo con Claude no hice frontend, solo wireframes de alta fidelidad. Es más complejo de lo que pensé. 

💀 Llevar vibe coding a producción para apps internas igual requiere conocimiento técnico. En Porter estamos creando un producto para que los marketers creen sus internal tools con las APIs de herramientas que usan—y que realmente puedan llevar a producción. 

Casi todo, o todo, el código de Porter Metrics ahora es con AI, pero requiere de desarrolladores. Sí somos "más rápidos" pero al costo de más bugs inesperados en cosas que no se habían "tocado".

En comentarios dejo el episodio completo

¿Cuál es tu opinión del futuro de diseño de páginas web con AI? 

Pienso en page builders como Elementor, Leadpages, Unbounce, etc. 

Me parece mucho más fácil hacer una página con herramientas como Anthropic Claude Code, incluso Vercel V0 o Lovable. 

La limitación con las herramientas de vibe coding es que no están integradas por defecto al CMS como Webflow o WordPress pero seguro lo harán y con Claude Code ya se puede hacer. 

Una ventaja muy fuerte de Claude es que al conectarse con la API puedes controlar no solo una página sino todas tus páginas, carpetas, imágenes, enalces internos, etc. 

O sea, ya no tienes que pensar en crear página por página, sino crear y manejar varias en un solo chat. 

Ahora, cuando uno conecte eso al Figma con el sistema de diseño de la empresa, se podría eliminar la necesidad de que un diseñador web maquetee las páginas individualmente. 

El diseñador seguirá siendo necesario, pero para alimentar el sistema de diseño, no diseñar las páginas. 

Si uno es optimista, "siempre hay mercado".  

Pero creo que hay una disrupción clara para los page builders (y diseñadores web). 

En Porter Metrics justo creamos una herramienta interna para hacer "vibe coding" de nuestro sitio de WordPress, justo como yo la necesito. 

Si usas WordPress y quieres acceso, me escribes.

What is your current take on AI? 

Are you bearish or bullish?

Every week in my head, AI goes from underrated to overrated to underrated again. 

✨ ChatGPT started all in 2022—then hallucinations hit. 
✨ Satya Nadella announced the death of SaaS. 
✨ n8n gave us the illusion to build anything with workflows—but they remain technical. 
✨Maybe part of the future is deterministic workflows as Wade Foster at Zapier suggested. We built an MVP with that thesis. 
✨Then vibe coding tools like Lovable, Vercel V0 made us believe anyone could build apps—but they're not production-ready.
✨ Claude Code by Anthropic made me believe that frontend dev is dead—until my dev team made me realize I was building high-fidelity wireframes, not actual frontend. 
✨ AI bros sharing the ultimate workflow to replace your marketing team—in exchange of a comment on LinkedIn.
✨ My fiancee just told me their AI-generated ads have lots of hate comments—but they're converting. 

Even if there's hype (and anxiety), there's proof that magic exists. 

Even if new advancements stopped today, what we have today is enough for disruption. 

Time will tell, but here's my current take: 

➡️ Don't bet against builders. 
➡️ Don't bet against the contrarian. 
➡️ Don't bet against passion and obsession.

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