’Hello Me’ - AI has flipped Personalisation

In Chapter 19 of Hello $Firstname, Michel Stevens reads ‘People and Skills for Personalisation’.
Michel Stevens is course director at CXM Academy and has spent his professional life on exactly what this chapter is about: the people and skills behind customer experience. In this chapter, he reads the first of three deep dives into the back end of the Pyramid of Personalisation.
The chapter opens with Pernille at the Royal Danish Theatre. Her team has spent years building a website, an app, and a marketing automation platform. Now it is time to stop building more cars and start driving the ones they have. As the chapter puts it, owning a Formula One car is worth nothing if no one has the skills or the time to drive it.
To map the skills a team needs, the chapter builds on Scott Brinker’s Five M model of marketing technologists: marketers, maestros, modellers, and makers, plus the manager who brings them together. For each role, it explores how generative AI changes the work, from brand LLM guardrails for maestros to vibe coding for makers.
A key insight is that maestros and makers build, while modellers and marketers execute. Early on, you need maestros and makers to put platforms and data processes in place. Later, you rotate in modellers and marketers, whose skills mirror the two sides of the Bowtie of Personalisation: insights and content.
The chapter also argues that generative AI makes human craft more important, not less. If you do not know what good looks like, how can you prompt for it or recognise it when it comes back? It then looks at AI agents as part of the team, with examples from Royal Unibrew and Landfolk, and at how the operating model shifts from trial and error at the Hack level, through separate campaign and automation teams at the Pack level, to agile, journey-centric teams at the Stack level.
In his reflection at the end, Michel takes the chapter’s argument one step further. If the surviving skill is knowing what good looks like, the next question is: good for whom? Underneath all five roles sits one skill that belongs to none of them alone, a real working knowledge of the customer. When anyone can generate five hundred versions before launch, the scarce and valuable person is the one who knows the customer well enough to pick the right one. Michel calls that customer fluency.
More resources from the Hello $Firstname universe
You can buy the physical book here: https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalisation, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here: https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalisation Cards and Canvas, which help teams turn the Bowtie of Personalisation into practical use cases, here: https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 18 of Hello $Firstname, Fiona Ngaruro reads ‘Models of Organisational Maturity in Personalisation’.
Fiona Ngaruro is a digital growth and marketing technology strategist based in Nairobi, Kenya, and the creator and host of the Martech Unraveled podcast, which explores how marketing and technology are shaping business growth across Africa. In this chapter, she opens Part Four of the book, where the focus moves from what to build to how an organisation matures so it can keep building personalisation profitably.
The chapter introduces the back end of the Pyramid of Personalisation. Where the front end describes the scope of personalised experiences customers receive, the back end describes the organisational capabilities that make those experiences possible: people and skills, technology, and governance, each across three maturity levels.
To build the model, the chapter draws on three sources of inspiration. The first is the Omnichannel Hexagon from Make It All About Me, which showed that organisations do not abandon earlier practices as they mature. The second is a 2022 Forrester Consulting study on omnichannel marketing automation, which found that people challenges can be just as hard to solve as technology challenges. The third, and most important, is Frans Riemersma’s model of marketing productisation from MartechTribe.
That model gives the back end its three levels: Hack, Pack, and Stack. At the Hack level, you rapidly prototype combinations of insights, content, and features with real customers to see what is viable. At the Pack level, you strip away everything redundant and keep a lean version of what works. At the Stack level, that version is integrated into your platform ecosystem with the goal of zero maintenance. Between each level sits a glass ceiling you will need to break through.
The central idea is that personalisation should eventually be treated almost as a product in its own right, complete with product owners, standards, and automation. Defining a standard means ruling out the exceptions, and whatever is standardised can be automated.
In her reflection at the end, Fiona highlights exactly this shift from campaigns and projects to productised capability. Teams often celebrate a successful campaign without asking how to turn it into something repeatable. Productisation frees teams from the day-to-day slog of execution so they can spend more time on strategic and creative work.
The chapter sets the stage for the rest of Part Four, which explores each dimension of the back end in turn.
More resources from the Hello $Firstname universe
You can buy the physical book here: https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalisation, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here: https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalisation Cards and Canvas, which help teams turn the Bowtie of Personalisation into practical use cases, here: https://www.omnichannelinstitute.com/en/personalizationcards

For two decades, personalisation has been something brands did to consumers. AI just flipped that.
In this opening episode, Rasmus Houlind (Agillic, Hello $Firstname) and Frans Riemersma (MartechTribe, MartechMap.com) introduce Hello Me — an open, exploratory podcast about what happens to marketing once consumers start using AI to figure out who they want to be, instead of waiting for brands to tell them.
We get into: why humans may have already solved for safety and survival without quite noticing; the three types of AI agents reshaping martech; whether wearables are making us healthier or just better monitored; and who should really own the data behind your own AI agent.
This is the first episode of an open-ended series — we honestly don't know when the next one drops, or who's in it. That's the format. If you've got a sharp, unusual take on personalisation, AI, or the new rules of marketing — especially if you're not already in our usual orbit — we want to hear from you.
Chapters
0:00 – Cold open: why "Hello Me"1:00 – Who we are, and the show's format7:00 – The three types of agents: of marketers, for customers, of customers10:00 – The preference agent: an LLM that asks "what do you want?"12:00 – From cookies to context: "sound on silent movies"14:00 – Expressed vs. unexpressed intent: "AI slop is human slop"15:00 – Humans won the game: scarcity, abundance, and why we haven't noticed20:00 – A Maslow-based framework for why the same product lands differently22:00 – How fast are consumers actually adopting this?27:00 – Borrowing context: a new, revocable way to let brands "see" you28:00 – Wearables & health tech: fear-driven vs. love-driven data36:00 – What do marketers do now? Value engineering and guest picks43:00 – The "conceivability gap," and agents acting in your best interest46:00 – Data sovereignty: who owns your agent's context48:00 – The customer has always owned the customer journey51:00 – Wildcards: voice, robotics, and the impact on society54:00 – Recap, and how to get involved
Links & resources
Watch the full video playlist on YouTube: https://www.youtube.com/playlist?list=PLJGgw-cJasRwHello Me — the concept for the show, and every question we're chasing this season: https://omnichannelinstitute.com/hello-me.htmlHello $Firstname — a free written abstract of the book this whole show builds on: https://agillic.com/free-ebook-hello-firstname/Hello $Firstname — the audiobook edition, with a full cast of narrators, on Spotify: https://open.spotify.com/playlist/2zIvs5pSRNTO3YAeFUWZBL?si=zpeTEW_1RnWNHSwZZEAnWAPersonalisation Cards — workshop decks for Commerce, Subscription, Banking, and Charity/NGO teams: https://omnichannelinstitute.com/cards.htmlMartechTribe — Frans Riemersma's research and consultancy on marketing technology: https://www.martechtribe.comMartechMap.com — Frans Riemersma and Scott Brinker's joint map of the global martech landscape: https://martechmap.comOmnichannel Institute — Rasmus's home for frameworks, books, and courses on personalisation: https://www.omnichannelinstitute.com

In Chapter 17 of Hello $Firstname, Steen Rasmussen reads ‘Conversion Rate Optimisation and Personalisation’.
Steen Rasmussen is co-founder of Brand Leadership Community and IIH Nordic, as well as an international keynote speaker and consultant specialising in the commercial use of web data, optimisation, and personalisation. In this chapter, he reads the final chapter of Part Three, where the book explores the relationship between CRO and personalisation.
The chapter begins with a fundamental question: before you personalise every touchpoint, is the general customer experience already working well enough for most of your customers?
Conversion rate optimisation helps answer that question. It focuses on improving the baseline experience by removing friction, clarifying communication, and making websites, apps, and campaign pages convert more efficiently. Personalisation, by contrast, focuses on adapting the experience to known customers, specific customer segments, or particular moments of truth.
The chapter explains when to prioritise CRO and when to shift towards personalisation. For anonymous website visitors, optimising the general experience often matters most. For owned media campaigns, personalisation can start earlier because even simple self-segmentation, subject-line variants, highlighted offers, or product-feed selection can make a difference. For marketing automation, the boundary between CRO and personalisation becomes especially interesting because a triggered message that removes friction can be both.
The chapter also concludes Part Three by returning to the broader question of who personalisation is not for. If your value proposition is weak, your brand is unknown, your first-party data scale is too limited, your content layer is underdeveloped, or your general customer experience is not yet sound, then personalisation may not be the right tactic to double down on yet.
In his reflection at the end, Steen adds a timely perspective on agentic commerce, agentic personalisation, and agentic workflows. His point is not that personalisation has suddenly become hyper-individual overnight. Rather, the cost and effort of executing personalisation have dropped quickly. And when execution becomes cheaper for everyone, the competitive bar moves. That is the Red Queen effect: you may need to run simply to stay where you are.
The chapter is a useful reminder that personalisation runs deeper than chasing conversions, but that optimisation and personalisation are still closely connected disciplines.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalisation, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalisation Cards and Canvas, which help teams turn the Bowtie of Personalisation into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 16 of Hello $Firstname, Keanu Taylor reads ‘The CX Layers: How Data and Content Fuel Personalisation’.
Keanu Taylor is Global Head of Research at The MarTech Weekly, a global analyst firm helping enterprise brands turn the complexity of marketing technology into clarity. In this chapter, he reads about the CX Layers framework and how data and content work in parallel to fuel personalisation.
The chapter explains why many personalisation projects have historically been too data-centric. Data is essential, but data alone does not create a personalised customer experience. It needs to be matched with content that is structured, governed, scalable, and ready to be activated.
The CX Layers framework separates the work into three layers: the data layer, the content layer, and the personalisation layer. The data layer collects, cleans, models, and activates customer insight. The content layer collects, creates, models, and activates the content required for personalised experiences. The personalisation layer is where these two sides come together through experience optimisation, experience decisioning, and experience delivery.
The chapter also explores how generative AI changes both sides of the equation. AI can help scale qualitative insight from conversations, reviews, support dialogues, and other unstructured sources. It can also help marketers create, model, repurpose, translate, tag, and activate content in ways that make personalisation more operationally realistic.
In his reflection at the end, Keanu connects the CX Layers model to the emerging discipline of context engineering. His point is that enterprises do not only need content. They also need to manage the context around that content: when it is relevant, which use cases it belongs to, when it should no longer be used, and how it should be made available to AI and personalisation systems.
The chapter gives marketers and martech teams a clearer way to think about the prerequisites for personalisation: not as a single data project, not as a content production problem, but as a layered system where data, content, and decisioning have to work together.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalisation, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalisation Cards and Canvas, which help teams turn the Bowtie of Personalisation into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 15 of Hello $Firstname, Ida Söderbäck reads ‘The Basic Foundations for Personalisation’.
Ida Söderbäck is a customer loyalty and CRM marketing expert currently at the Swedish Red Cross. In this chapter, she reads the opening chapter of Part Three, where the book turns from what personalisation is and how it creates value to when personalisation is actually the right tactic to use.
The chapter asks three important questions: Do you have the prerequisites to do personalisation? Is it the right thing for your organisation to do? And is it the right thing to do now?
It argues that personalisation is a distinct communication tactic, not the answer to every marketing or business challenge. Before investing heavily in personalisation, organisations need a solid core offering, brand trust and demand, access to customer data and insights, and enough content to match those insights with something useful to say.
The chapter also makes a pragmatic point that is sometimes overlooked in personalisation projects: if the value proposition is weak, if the customer experience is fundamentally broken, or if no one knows or trusts your brand yet, personalisation is unlikely to fix the problem.
In her reflection at the end, Ida connects the chapter to loyalty and CRM. For her, personalisation is central to creating relevant communication, building relationships, and increasing loyalty and revenue. But she also underlines the chapter’s core message: personalisation becomes powerful only when the organisation has the right prerequisites, including individual-level data, the right competencies, and the martech systems to put it all into action.
The chapter serves as a useful reality check for any marketing leader facing pressure to personalise before the basics are in place.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalisation, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalisation Cards and Canvas, which help teams turn the Bowtie of Personalisation into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 14 of Hello $Firstname, Rasmus Houlind reads ‘Tying It All Up in the Bowtie of Personalization’.
Rasmus Houlind is the author of Hello $Firstname and narrates this chapter himself because it brings Part Two together. The chapter revisits all four corners of the Bowtie of Personalization and shows how they come together across campaigns, marketing automation, and inbound platforms.
The chapter explains what good looks like from the customer’s point of view. A realistic personalized customer experience is not hyper-personalized at every touchpoint. It is a mix of highly personalized communication, semi-personalized communication, and generic communication, shaped by how much data the brand has and how engaged the customer is.
The chapter also goes deep into measurement. It discusses control groups, proxy metrics, statistical significance, customer lifetime value, net promoter score, and the importance of doing the math all the way to the money. It then gathers the maturity levels for campaigns, marketing automation, and inbound platforms into the front end of the Pyramid of Personalization.
In his reflection at the end, Rasmus adds a 2026 perspective. AI has made it easier to turn structured and unstructured data into insight, create message variants, localize content, generate images, tag content, and prepare content feeds for activation. But he also warns that more AI-generated content is not automatically better content. Marketers still need judgment, taste, governance, and a clear model for what they are trying to do.
The chapter closes Part Two with a clear conclusion: AI does not make the Bowtie obsolete. It makes the Bowtie more useful. The more powerful the technology becomes, the more important it is to understand the customer, the moment, the message, the content, and the value being created.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalization, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalization Cards and Canvas, which help teams turn the Bowtie of Personalization into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 13 of Hello $Firstname, Mark Robertson reads ‘Personalization on Inbound Platforms’.
Mark Robertson is Partnerships Director at Mastercard Dynamic Yield and has spent around 25 years working across marketing, technology, sales, partnerships, and tools for both outbound and inbound marketing. In this chapter, he reads about personalization on websites, apps, and other inbound platforms.
The chapter explains that visitors arrive on inbound platforms with some kind of intention. If campaigns and marketing automation have done their job, the brand may even have helped spark that intention. The question then becomes how websites and apps can respond with the right content, functionality, messages, and feeds.
The chapter argues that the core customer experience must come before personalization. A website or app must first work well as a self-service experience. Only then should marketers add dynamic personalization, starting with ‘My’ pages, then content feeds, then personalized messages based on intent, and eventually the hiding of irrelevant content that creates unnecessary friction.
In his reflection at the end, Mark draws a clear distinction between testing, conversion rate optimization, and true personalization. He also points to the importance of operability across CDPs, loyalty systems, CMSs, digital asset management systems, ecommerce platforms, and analytics tools. His view is that AI will push inbound personalization beyond single-page testing towards more journey-based optimization.
The chapter reminds marketers that inbound personalization is not just about changing the homepage banner. It is about understanding customer intent in near real time and designing the whole platform experience around what the customer is trying to do.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalization, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalization Cards and Canvas, which help teams turn the Bowtie of Personalization into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 12 of Hello $Firstname, Maria Moreau reads ‘Content, Part 2: Content Feeds’.
Maria Moreau is CRM Director at Boozt.com, where she works with CRM for millions of users. In this chapter, she reads about the second content corner of the Bowtie of Personalization: content feeds.
The chapter opens with HBO Max and the challenge of personalizing which movies, series, and episodes are shown to each user. It explains how content feeds differ from messages: they are often fed from existing sources such as product information systems, article databases, application databases, or ecommerce platforms rather than being written from scratch by marketers.
The chapter covers how content feeds can be grouped, sorted, ranked, filtered, and marked. It explains why the right feed can matter more than the ranking within it, how feeds can support both relevance and inspiration, and why marketers must be careful not to create narrow echo chambers when recommendation logic becomes too rigid.
Maria’s framing at the beginning makes the practical stakes clear: for teams managing CRM at scale, content feeds are vital to making personalization operational. They are what allow brands to activate large bodies of products, articles, offers, shows, events, or recommendations in ways that feel useful to each customer.
The chapter shows why personalization on inbound platforms is often less about writing a perfect message and more about choosing the right shelf, the right feed, and the right context.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalization, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalization Cards and Canvas, which help teams turn the Bowtie of Personalization into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards

In Chapter 11 of Hello $Firstname, Jordie van Rijn reads ‘Personalization in Marketing Automation’.
Jordie van Rijn is an email marketing and martech specialist who guides businesses in selecting marketing software through emailvendorselection.com. In this chapter, he reads about personalization in marketing automation and customer lifecycle communication.
The chapter explains why marketing automation is different from campaigns. Instead of deciding that it is Thursday and sending a newsletter, automation waits for customers to reach specific moments of truth and then responds with a relevant message. This makes timing one of the strongest drivers of perceived relevance.
The chapter explores value creation in marketing automation across increased top-line sales, churn reduction, and cost savings. It discusses abandoned baskets, onboarding flows, welcome programs, subscription upgrades, win-back tactics, next best action, next best experience, and the importance of measuring automation over a longer time horizon than campaigns.
In his reflection at the end, Jordi brings the chapter back to practical marketing work. He describes marketing automation as data set in motion and encourages listeners to find one additional valuable data point or trigger that could make an automation more relevant. His point is that creativity and data belong together.
The chapter reminds marketers not to let perfect become the enemy of good. A triggered message that exists and reaches the customer in the right moment will often create more value than a beautifully segmented message that never gets built.
More resources from the Hello $Firstname universe
You can buy the physical book here:https://amzn.eu/d/6jV4QZT
If the Amazon EU link does not work in your country, please search for Hello $Firstname: Profiting from Personalization, AI Edition on your local Amazon store.
You can download the illustrations and models from the book here:https://www.omnichannelinstitute.com/en/resources
You can also learn more about the Personalization Cards and Canvas, which help teams turn the Bowtie of Personalization into practical use cases, here:https://www.omnichannelinstitute.com/en/personalizationcards