In this episode, we dive into the realities of CRO (Conversion Rate Optimization) today — from AI anxiety to experimentation culture and how teams should actually be structured.

We start with a surprisingly philosophical take on photography and overthinking, then quickly shift into what’s really happening in the CRO and AI space right now.

We discuss:

* Why AI might be making everything look the same

* The growing fear (and noise) around AI in CRO

* How to structure CRO teams: centralized vs hybrid vs embedded

* Why experimentation still struggles with a “nice-to-have” perception

* What actually builds a strong experimentation culture

* How individual contributors can influence culture without authority

* And how to position CRO as a true growth engine, not just testing

If you work in growth, product, or experimentation, this is a candid look at what’s changing and what actually matters.

Chapters

0:00 – Photography, overthinking, and creative process1:26 – Back to CRO: what’s happening in the industry2:07 – AI concerns and job market anxiety2:45 – The “everything looks the same” AI problem4:00 – Too many AI tools, no real differentiation5:38 – What people are really asking about AI6:23 – AI fear vs reality (and layoffs)7:08 – Fear-mongering vs signal8:00 – Fear and decision-making9:00 – CRO team structures: centralized, hybrid, embedded9:31 – Why centralized works early10:08 – When to move to hybrid10:29 – Why embedded is hard11:04 – The role of leadership buy-in12:13 – Why experimentation gets cut first13:00 – CRO’s “nice-to-have” branding problem14:00 – Why CRO is easy to underestimate15:45 – Future-proofing: combine CRO with other skills16:54 – Building experimentation culture (the “laundry” analogy)18:19 – How to destroy experimentation culture19:23 – Why authority and buy-in matter20:25 – How ICs can influence culture21:34 – Reframing experimentation as empowerment23:09 – Becoming a catalyst across teams24:46 – Confidence and presence in CRO roles25:59 – CRO vs Growth: what’s the difference?27:24 – Where CRO fits inside growth teams28:02 – Moving CRO upstream into systems thinking29:00 – Closing thoughts

In this episode, we answer real, unfiltered questions from the CRO and experimentation community. We dig into how far AI can realistically help with experimentation, why revenue metrics like ARPU are a nightmare for MDE calculations, how to handle sketchy interview “audits,” and why ROI conversations never seem to end.No hype. No magic bullets. Just honest perspectives from people actually doing the work.Topics include:

* Where AI helps (and quietly breaks) CRO workflows

* How to think about MDEs for continuous metrics like ARPU

* Making time for research when you’re already drowning

* When “auditing a site” crosses into spec work

* Volume hiring for CRO roles

* Escaping (or not) the endless ROI loop

* Why some CRO agencies don’t have designers

Drop your own questions in the comments or check the links below to submit anonymously.- Ask us a question here: https://docs.google.com/forms/d/e/1FAIpQLSd8P5yCsO5NB6WPe204k1WExhH1Bs8w6nZxPRRn-BiAGozpaQ/viewform- Visit Koalatative here: https://www.youtube.com/@koalatative⏱️ Chapters00:00 – Intro & warm-up04:34 – How far can AI actually help in delivering CRO?11:19 – How do experimentation experts estimate MDE for continuous metrics like ARPU?15:28 – How do you make the most of research time when there’s no time to do anything?19:29 – How do you handle being asked to audit a site as part of a CRO interview?24:20 – How do you approach CRO in volume recruitment?28:21 – How do you get out of the endless ROI loop with stakeholders (and stop saying “CRO”)?31:46 – Why do some CRO agencies not have designers on the team?33:47 – Outro & announcements#cro #experimentation #abtesting #aiincro #growth #productmanagement #conversionrateoptimization #experimentationculture #careerintech #experimentationnation

A real conversation about why A/B testing doesn’t magically fix broken businesses.We break down the biggest CRO myths, why copying case studies fails, how experimentation tools really get chosen, and what actually causes friction between CRO, UX, and research teams.For CROs, experimenters, product, growth, UX, and analytics leaders.1:38 The biggest myth in A/B testing3:00 The one-person CRO team fallacy4:34 Why copying tests never works10:44 Choosing an experimentation platform14:39 Working with “difficult” clients

In this episode, we go off-script and cover everything from CRO strategy to existential questions.We talk through:How to recover after being shaken at workWhy long-form content still matters in experimentationCRO differences between B2B, SaaS, and ecommerceWhy website redesigns without A/B testing backfireHow beginners can gain real CRO experienceWhat it actually takes to get people to listen to dataAnd yes… the meaning of life (besides 42)This episode is less about “perfect answers” and more about how CRO, experimentation, and work actually play out in the real world.If you work in experimentation, product, growth, or analytics, this one will feel uncomfortably familiar.Chapters00:00 – How to recover after being shaken at workReflection, time, and physical reset after tough moments02:10 – End-of-year reflection and career resetsBurnout, misfit roles, and rediscovering intrinsic motivation04:25 – Why short-form content fails complex industriesAttention, doomscrolling, and why long-form still matters07:18 – Listener Q&A begins: CRO across business modelsB2B vs SaaS vs ecommerce testing realities12:02 – The hidden buyer problem in B2B CROResearchers vs decision-makers and misaligned incentives13:44 – Website redesigns without A/B testingPolitics, risk, and how to introduce testing anyway18:16 – How beginners can get real CRO experienceSide projects, free tools, and hands-on learning23:46 – The meaning of life (other than 42)Creating your own meaning rather than finding one26:58 – Getting people to listen to data at workInfluence, likability, and organizational dynamics31:24 – Culture fit, authority, and when to move onWhy sometimes it’s not you, it’s the environment32:23 – Wrap-up and next episode teaser

Koalatative's Gerda Thomas and Experiment Nation's Rommil Santiago answer questions from the CRO community.Chapters3:35 – Is there room in CRO for AI skeptics anymore?4:58 – How can I feel like I'm using my CRO skills for good?11:29 – AI is boring and speeding up the decline of civilization. Agree or disagree?15:22 – How do I tell my micromanaging manager to shut up?18:43 – Why are you the way that you are?23:48 – How do you share a complete story with clients so they actually hear both sides of the research?26:39 – How do you calculate ROI for my CRO program for a client?29:17 – When you have no ideas on what test to run where do you get ideas?

Koalatative's Gerda Thomas and Experiment Nation's Rommil Santiago answer CRO questions from the community.Chapters:1:51 – What's the one thing people on internet still refuse to automate or use AI for that you think they should?”5:07 – How do you measure the impact of your CRO program over time?10:37 – What to do when leadership has a win at all cost mentality, choosing short-term wins over long-term ones. How can a proper experimentation program thrive?15:27 – How should checks and balances happen in an organization on data integrity? Who should own those roles?20:10 – Should a testing tool have a warning that says, 'Your win rate is too high. Check your data type warning.'?22:49 – It seems like every day it gets harder to land a quality job in CRO with some of my colleagues taking up to a year to bounce back from a layoff. Is it worth joining the field anymore?

Koalatative's Gerda Thomas and Experiment Nation's Rommil Santiago answer your CRO questionsPart 1 of 3Chapters:8:05 – What is the right balance between big tests versus small and medium tests?12:47 – How many iterations per test will you run knowing the first test was negative but still see some relevant data toward the hypothesis?14:32 – In small traffic sites, is it best to run one A/B test or launch a test under pre-post test assumption?17:40 – What’s the one thing most people in experimentation still refuse to automate or use AI for that you think they should do it?-----Catch Gerda on Koalatative's channel here:

In this episode of Experiment Nation, host Jason Gossit sits down with Ameliano Blanca, a senior growth and product leader with 10+ years of experience driving revenue through data-driven experimentation.They dive deep into:How to build experimentation programs from the ground upThe balance between qualitative and quantitative insightsExperimentation in startups vs. mature organizationsCRO frameworks and the power of iterationHow to avoid "random testing mode" and adopt structured frameworksIf you’re a growth, product, or CRO professional, this episode is packed with actionable insights to help you scale experimentation programs, improve conversion rates, and create sustainable growth strategies.👉 Get our new book: Prove It or Lose It – The (Mostly) No-Nonsense Guide to Surviving Experimentation Program Drama at experimentnation.com and all major bookstores.📌 Chapters:0:00 – Why tests should be rerun after 12 months0:19 – Welcome & introduction with Jason Gossit0:35 – Meet Ameliano Blanca: growth & product leader1:32 – First steps in building experimentation programs2:42 – Measuring conversion funnels & revenue impact3:46 – Tools for gathering quantitative & qualitative insights5:05 – Heatmaps, surveys, and finding hidden gems6:00 – Drafting test ideas & prioritization7:19 – Using and adjusting the ICE framework9:50 – The “three strikes” rule for failed experiments11:16 – Experimentation in startups vs. mature companies13:00 – Why rerunning startup tests is critical14:57 – When to pause or rerun losing experiments15:29 – Complementing quantitative data with customer interviews17:16 – Running experiments at scale in larger organizations18:18 – Balancing speed vs. rigor in CRO testing20:04 – Defaulting experiments & tracking long-term results20:11 – CRO frameworks and the power of iteration22:26 – Why iteration is underrated in experimentation23:44 – Adapting frameworks to your company & industry25:18 – Advice for teams stuck in random testing mode27:39 – How CRO perspectives have evolved over 10 years28:39 – Growth, insights, and the rise of experimentation in strategy30:38 – Real-world example: financing simulator boosts conversions