NeoMarketing’s Mantra: Double the Best, Halve the Waste (Part 1)

The Idea

Marketing stands at a crossroads, facing unprecedented challenges and opportunities in the AI era. As Google’s AI Overviews and AI answer engines like ChatGPT and Perplexity disrupt organic search traffic, and competitive pressures demand ever-accelerating growth, brands find themselves trapped in an increasingly expensive cycle. This perfect storm is forcing marketers to pour more resources into reacquisition—repeatedly paying premium prices to reach customers they already know—while traditional engagement channels continue to deteriorate.

I’ve written extensively about the profound inefficiencies plaguing modern marketing—what I call the “$500 billion AdWaste crisis.” This staggering figure represents the 70% of digital marketing budgets that brands squander on repeatedly reacquiring customers they already know through expensive adtech platforms.

The AdWaste crisis stems from two fundamental marketing failures: the “Not for Me” problem (generic messaging that fails to resonate with individual preferences) and the “No Hotline” problem (the absence of reliable engagement channels). These failures lead to attention recession, where customers mentally unsubscribe long before formally opting out, forcing brands into expensive reacquisition cycles.

During a recent meeting with an eCommerce client, this reality came into sharp focus. Despite building a successful business with $6 million in annual revenue, he struggled with balancing growth and profitability. His monthly acquisition spending through adtech platforms was $50,000—a stark contrast to the mere $2,000 he spent on martech solutions for retention.

When I pointed out this imbalance, his response captured the fundamental challenge facing marketers today: “Acquisition is easy—I just call up an agency, give them a budget, and they deliver the clicks. ABC. Agency, Budget, Clicks. Retention is tough. Martech platforms are complex. I know my team doesn’t make full use of your platform. I know we need better segmentation, sharper content, more targeted campaigns. But all that is hard work. Can you make martech as easy as adtech? And also provide agency support so you price on outcomes rather than inputs. Become a partner, not a vendor.”

This conversation crystallised the core ideas I’ve been exploring: NeoMarketing, the BRTN (Best-Rest-Test-Next) framework, AI Marketing Agents and Twins, Progency, NeoN, and NeoMails. These concepts represent a fundamental reimagining of marketing for the AI era—one that addresses the AdWaste problem while maximising Customer Lifetime Value (LTV) and minimising Customer Acquisition Cost (CAC) to deliver “Rule of 40” profitable growth.

As I reflected on this and other conversations during my flight back to Mumbai, I realised I needed a simple slogan to capture the essence of NeoMarketing: “Double the Best, Halve the Waste.” This encapsulates the dual mission of NeoMarketing—doubling the Best customer base (those top 20% who deliver 60-80% of revenue and 200% of profits) while cutting AdWaste (primarily spent on reacquisition) by 50%.

In this series, I’ll explore how breakthroughs like Progency (combining Platform, Experts, AI Agents, and Kaizen-driven continuous improvement) and NeoN (an alternate ad network based on authenticated identity) can transform marketing from a cost centre into a profit engine. I’ll demonstrate how these innovations enable brands to establish reliable hotlines with customers, deliver true N=1 personalisation at scale, and eliminate the wasteful reacquisition cycle that drains marketing budgets and stunts profitability.

Together, we’ll discover how to make NeoMarketing’s “Double the Best, Halve the Waste” vision a reality for businesses.

Thinks 1601

SaaStr: “Startups that are scaling are spending about: 15% of Revenue on Sales — and 18% for higher growth start-ups, 10% of Revenue on Marketing (and trending up), 7% on Customer Success (trending down).”

Elizabeth Reid: “Human curiosity is boundless. People have a lot of questions. A three-year-old will go: “Why, why, why, why, why?” But, as an adult, you don’t assume the person you ask the question knows the answer. You don’t know if you have enough time. You don’t know if it’s worth the effort. And so you don’t ask those questions. But if you lower the [barrier] to asking the question, then people just come. They have a lot more questions and they ask anything these days.”

FT: “In [Andy] Grove’s view, government plays a vital role in developing a robust national infrastructure, funding basic research and making the US a beacon for immigrants. He also believed it was vital for the country to maintain a thriving manufacturing base.

Sendhil Mullainathan: “People imagine that AI is going to automate things, but they don’t appreciate that automation is just one path. There’s nothing intrinsic about machine learning or AI that puts us on that path. The other path is really the path of augmentation. For me, bicycles for the mind describe that. Whether we end up building things that replace us, or things that enhance our capacities, that is something that we can influence. But I am feeling as much urgency as everyone else: If we keep going down the automation path, it’s going to be very hard to walk back and start changing things…One of the most useful things augmentation can do is it can help us with the things that we’re not as good at, to leave room for the things we are excellent at. Behavioral economics has helped identify those blind spots.”

Vlad Tenev: “I think news, entertainment, financial services, sports to some degree… these are all merging over time, and they’re part of our collective consciousness. I think retail investing is a big part of that. A big, enduring trend is power and capabilities that were formerly reserved for institutions going to the individual level.”

Ending AdWaste: Progency for LTV, NeoN for CAC

Published May 20, 2025

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Past, Present, Future

The $500 billion annual AdWaste crisis—where 70% of marketing budgets evaporate reacquiring customers brands already know—has become marketing’s accepted tragedy. This systemic inefficiency persists unchallenged: Big Adtech platforms remain silent to protect their profits, CMOs avoid the topic in boardrooms fearing budget cuts, and CEOs remain largely unaware of this massive profit leak. With each passing quarter, this insidious drain tightens the vice between skyrocketing Customer Acquisition Costs (CAC) and declining Customer Lifetime Value (LTV), slowly strangling business profitability and hurting shareholder value. Two breakthrough innovations now offer a path to liberation from this costly cycle.

The Root of AdWaste: Marketing’s Twin Failures

AdWaste isn’t merely inefficient spending—it’s the symptom of two fundamental marketing failures. First, the “Not For Me” problem: generic messaging that fails to resonate with individual needs and preferences. Second, the “No Hotline” problem: the absence of reliable engagement channels between brands and customers. When these failures combine, attention recession follows—customers mentally unsubscribe long before formally opting out, forcing brands into expensive reacquisition through Google and Meta’s auction-based platforms.

This vicious cycle creates a mathematical impossibility: sustainable profitable growth cannot coexist with perpetual reacquisition. For decades, this systemic inefficiency persisted unchallenged—until now. Progency and NeoN dismantle AdWaste, offering brands new hope: slashing reacquisition costs by 30-50% while unlocking trapped profit potential.

Progency: Transforming Martech’s Promise

What if martech platforms evolved beyond selling software to guaranteeing outcomes? Today’s powerful martech platforms sit largely underutilised—victims of the execution gap between technological capability and operational reality. Most brands leverage just 30-40% of their martech features despite significant investments.

Progency—a fusion of product, expertise, AI agents, and continuous improvement—represents the missing link. Through the PEAK framework (Platform, Experts, AI agents, Kaizen), Progency delivers true N=1 personalization at scale, transforming martech economics from cost-centre software to performance-based profit engines. This isn’t outsourcing—it’s a revolutionary approach where compensation ties directly to measurable business impact.

NeoN: The Authenticated Attention Exchange

Simultaneously, NeoN introduces a paradigm shift in reacquisition through PII-based (Personally Identifiable Information) targeting. This authenticated identity network enables brand-to-brand collaboration without expensive intermediaries. Through NeoN, one brand’s inactive “Test” customers can be precisely targeted through another brand’s engaged “Best” customer channels.

This creates a powerful dual advantage: publishers “print money” by monetising their engaged audience while advertisers “save money” through dramatically more efficient reacquisition—cutting costs by 30-50% compared to traditional platforms.

The NeoMarketing Revolution

Together, Progency and NeoN form the twin pillars of NeoMarketing—marketing’s third great era following Traditional Marketing (1950s-1990s) and Modern Marketing (2000s-2020s). This transformation fundamentally inverts established priorities: retention before acquisition, relationships before transactions, and precision before volume.

For CMOs, this represents an unprecedented opportunity to evolve from money guzzling managers into C-Suite MVPs—the executives who transform marketing from necessary expense into the primary profit engine driving sustainable business growth.

In this series, I’ll build upon my previous writings to outline a practical pathway toward this new future—one where AdWaste becomes a relic of the past, and marketing finally fulfils its promise as the catalyst for profitable, sustainable growth.

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Best and Rest Customers

I have written multiple essays recently about Progency:

Progency’s transformative power lies in its singular focus: driving revenue upside to maximise Customer Lifetime Value (LTV). Unlike traditional agencies or martech implementations, Progency operates exclusively on performance-based economics—taking ownership of interactions with specific customer segments whilst being compensated solely on incremental revenue generated above established baselines. This distinctive approach aligns incentives perfectly: Progency succeeds only when brands succeed.

What enables Progency to outperform brands’ internal marketing departments? The answer lies in its comprehensive PEAK framework:

  • Platform Mastery: As an extension of the martech vendor, Progency possesses unparalleled platform expertise. This intimate knowledge unlocks the full potential of martech systems that typically sit 60-65% unutilised within brand environments. Whilst internal teams struggle with limited bandwidth to leverage advanced features, Progency operates with complete command of every capability, from sophisticated segmentation algorithms to complex journey orchestration.
  • Expert Specialisation: Progency deploys vertical industry specialists with deep domain knowledge—professionals who understand not just the technology but the specific business contexts in which it operates. These experts bring contextual intelligence that general marketers cannot match, identifying revenue opportunities and optimisation levers that internal teams often miss due to operational constraints or knowledge gaps.
  • AI Agent Orchestration: Whilst marketing departments wrestle with incorporating rudimentary AI into their workflows, Progency deploys sophisticated AI agent ecosystems operating at unprecedented scale. These include specialised agents for segmentation, content creation, journey orchestration, and performance analysis—all coordinated by an AI Co-Marketer that ensures alignment with brand guidelines and business objectives. This “Department of One” enables true N=1 personalisation without proportional staffing increases.
  • Kaizen Methodology: Progency implements continuous improvement systems that transcend traditional campaign-based thinking. Through rigorous A/B testing, real-time performance monitoring, and systematic optimisation across all customer touchpoints, Progency creates a virtuous cycle where every interaction generates insights that improve future engagements. This systematic approach ensures compounding performance improvements that outpace episodic campaign optimisations.

By mastering the platform, leveraging expert specialisation, employing AI agents, and implementing continuous improvement, Progency directly addresses the “Not For Me” and “No Hotline’ problems” that fuel AdWaste.

Progency delivers its greatest impact across two critical customer segments:

  • Best Customers (top 20% who deliver 60-80% of revenue and 200% of profits) benefit from hyper-personalised experiences that maximise individual LTV potential. By understanding specific preferences and behaviours at granular levels, Progency identifies cross-sell and upsell opportunities that generic segmentation approaches invariably miss.
  • Rest Customers (the middle 40-50% showing declining engagement) receive precisely timed interventions that prevent the slide into dormancy. Through AI-orchestrated personalisation and daily hotlines crafted via NeoMails, Progency systematically converts these wavering relationships into Best customer status—unlocking substantial revenue currently left unrealised by resource-constrained marketing departments.

Additionally, Progency harnesses these engaged segments to drive referral programmes that simultaneously reduce CAC and increase Earned Growth—transforming existing customers into acquisition engines that bypass expensive adtech platforms entirely.

The cumulative advantage becomes clear: whether performing complex segmentation, creating personalised content, orchestrating sophisticated journeys, or executing multichannel campaigns, AI-powered Progency consistently outperforms human-centric marketing departments. The result isn’t merely improved efficiency but a fundamental transformation in how brands monetise customer relationships—shifting marketing from cost centre to profit engine through measurable, sustainable revenue growth.

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Test and Next

I have written multiple essays recently about NeoN:

AdWaste represents the single greatest destroyer of brand profitability today—a staggering $500 billion globally squandered on reacquiring customers who already exist in brands’ databases. This inefficiency stems primarily from dormant, inactive, or churned “Test” customers who become unreachable through owned channels, forcing brands into expensive retargeting through Google and Meta’s auction-based platforms.

While Progency’s mission is building reliable hotlines to prevent customers falling into attention recession, NeoN addresses the inevitable reality: some customers will still disengage. For these Test customers—and for genuinely new Next customers—NeoN provides a revolutionary alternative to traditional adtech platforms, fundamentally transforming both reacquisition and new acquisition economics.

The PACE framework powers NeoN’s disruptive approach:

  • PII Matching Engine: Unlike cookie-based targeting that relies on probabilistic matching, NeoN’s core innovation is its authenticated identity engine. This precise system enables brands to reach their dormant Test customers through the active email engagement channels of non-competing brands. When Brand A wants to reconnect with inactive customers, NeoN identifies where those individuals appear as engaged Best customers for Brand B—creating a direct, privacy-compliant pathway for reacquisition without platform intermediaries.
  • ActionAds: Traditional digital advertising suffers from a devastating “click-through penalty” where 80-90% of potential conversions are lost when customers must leave their current environment. NeoN eliminates this friction through AMP-powered ActionAds embedded within partner emails. These interactive mini-applications enable customers to browse products, complete forms, and make purchases without ever leaving their inbox—dramatically increasing conversion rates whilst reducing acquisition costs.
  • Cooperative Structure: NeoN creates a brand-to-brand marketplace where companies simultaneously play dual roles—as publishers monetising their Best customers’ attention and as advertisers efficiently reacquiring their Test customers. This cooperative approach bypasses expensive platform intermediaries whilst creating powerful network effects: each new brand joining the ecosystem adds both valuable inventory and targetable audiences.
  • Ecosystem Services: Beyond its core matching capabilities, NeoN builds complementary utilities that expand email inventory opportunities whilst enhancing data capabilities. These include inbox intelligence utilities, AI-powered daily newsletters and games, an Atomic Rewards system for micro-actions, and sophisticated data management platform (DMP) functionality for identifying high-potential audiences for new acquisition.

Through PII matching, ActionAds, a cooperative structure, and its ecosystem services, NeoN provides a powerful alternative to traditional adtech, directly addressing the inefficiencies of customer reacquisition.

NeoN delivers transformative value across the other two customer segments:

  • For Test customers (dormant 90+ days), NeoN enables precision reacquisition at 30-50% lower cost than traditional platforms. By reaching these individuals through channels where they’re actively engaged, brands can reconnect relationships at a fraction of typical adtech costs—immediately improving marketing ROI whilst reducing platform dependency.
  • For Next customers (genuinely new acquisitions), NeoN leverages its accumulated cross-brand intelligence to identify high-potential prospects with unprecedented precision. Unlike traditional lookalike modelling that relies on superficial behavioural signals, NeoN’s authenticated approach enables acquisition targeting based on genuine affinity and proven engagement patterns, with a specific focus on in-market segments (akin to what Google and Meta do).

The revolutionary impact lies in NeoN’s ability to create a virtuous cycle where brands simultaneously “print money” by monetising their engaged audience and “save money” through dramatically more efficient customer acquisition to reduce CAC. This dual advantage fundamentally rewires marketing economics—liberating brands from platform dependency whilst transforming customer attention from cost centre to profit engine.

By creating a viable alternative to Big Adtech for both reacquisition and new customer acquisition, NeoN delivers the missing piece in the AdWaste solution puzzle: a pathway to sustainable, profitable growth that isn’t built on platform dependency and endless acquisition cycles.

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Email Utilities

NeoN’s true power lies not just in its PII-based matching engine, but in the complementary suite of email-focused utilities that extend its reach and sharpen its targeting precision. These utilities create new inventory channels while simultaneously collecting zero-party data—fuelling high-accuracy targeting for both reacquisition and new customer acquisition, and dramatically accelerating the fight against AdWaste.

The development of proprietary utilities follows a proven strategic playbook employed by digital giants—one that has redefined the digital landscape. Google built its empire atop Search, Gmail, Maps and YouTube, whilst Meta constructed its walled garden through Facebook, Instagram and WhatsApp. These owned properties serve a dual purpose that transcends their consumer-facing utility: they generate both first-party inventory and invaluable user data. By establishing its own ecosystem of email utilities, NeoN creates a virtuous cycle where consumer value drives adoption, adoption creates inventory, inventory enables monetisation, and interaction data enhances targeting precision. This strategic approach allows NeoN to gradually reduce dependency on third-party inventory sources whilst simultaneously building targeting capabilities that rival or exceed traditional platforms—all whilst maintaining complete ownership of the value chain. Unlike traditional ad networks that merely broker others’ attention, NeoN’s owned properties establish direct consumer relationships that create sustainable competitive advantages in both inventory quality and targeting precision.

Mindmap: Intelligent Inbox Assistant

Mindmap serves as NeoN’s intelligent inbox layer, applying sophisticated AI to transform email from an overwhelming stream of messages into actionable intelligence. Unlike conventional email clients that simply organise messages chronologically or by sender, Mindmap analyses content to extract meaningful patterns, commitments, and opportunities.

Key features include:

  • Receipt Analysis: Automatically identifying and categorising purchases to create valuable in-market segments based on actual spending behaviour rather than mere browsing signals
  • Commitment Detection: Surfacing promises made or received within emails (“I’ll send you that report by Friday”) to create contextual task lists without manual entry
  • Intelligent Summarisation: Distilling lengthy messages into actionable bullet points, enabling users to process information more efficiently
  • Predictive Organisation: Clustering related communications across time to provide conversation threads that transcend traditional folder structures
  • “Just One Thing”: Curating a single high-value insight or action item every few hours, creating a habit-forming engagement pattern

Mindmap addresses a fundamental consumer pain point—email overwhelm—whilst simultaneously providing NeoN with invaluable insights into purchase patterns, brand relationships, and consumer preferences. This zero-party data, gathered with explicit consent, powers targeting capabilities that match or exceed what Google and Meta offer through tracking and inference.

MyToday: Personalised Micron Delivery

MyToday reimagines newsletters through AI-powered personalisation and interactive AMP experiences. Unlike traditional email newsletters that deliver identical content to all subscribers, MyToday creates truly individualised daily experiences:

  • AI-Generated Content: Tailored news, information, and entertainment based on demonstrated interests and engagement patterns
  • Interactive Microns: 15-60 second “brain gain” experiences including games, puzzles, quizzes, and micro-learning modules
  • Personalised Timing: Delivery optimised for each recipient’s engagement patterns rather than arbitrary scheduling

MyToday serves two crucial functions within the NeoN ecosystem: creating valuable daily inventory for ActionAds whilst simultaneously deepening user profiles through engagement data. Each interaction reveals preferences, interests, and receptivity to different content types—information that enhances targeting precision across the entire network.

Muniverse: The Atomic Rewards Platform

Muniverse introduces a revolutionary approach to attention economics through its Atomic Rewards (Mu) system. This micro-incentive framework transforms mundane digital interactions into rewarding experiences:

  • Micro-Earning Opportunities: Points awarded for small actions like opening emails, completing surveys, providing preferences, or engaging with content
  • RaffleCash System: A gamified redemption approach where accumulated points enter users into daily, weekly, and monthly prize draws
  • Attention Marketplace: A self-sustaining economy where brands fund rewards in exchange for verified attention
  • Cross-Brand Portability: Rewards earned across participating NeoN partners, creating powerful network effects

Muniverse addresses a fundamental market failure in digital marketing: the asymmetrical value exchange between consumers and advertisers. By creating a transparent system where attention is properly valued and compensated, Muniverse transforms the traditional adversarial relationship into a mutually beneficial partnership.

From NeoN’s perspective, Muniverse serves as both an engagement driver and a precision targeting enhancer. The granular preference data gathered through reward-incentivised actions enables targeting capabilities that far exceed traditional lookalike modelling, particularly for in-market segments with demonstrated purchase intent.

Micronbox: The Future-Proof Messaging Platform

Micronbox represents NeoN’s strategic hedge against platform dependency. This lightweight messaging system linked to both mobile numbers and email addresses provides:

  • Universal Inbox: Messages accessible regardless of device or primary messaging platform
  • Platform Independence: Control over delivery mechanisms without dependence on potentially restrictive platforms
  • Rich Interactive Experiences: Native support for AMP elements, allowing sophisticated in-message applications
  • Identity Verification: Multi-factor authentication enhancing the reliability of PII matching

While initially positioned as a complementary channel, Micronbox provides crucial insurance against potential restrictions from email providers like Gmail. Should platform policies change, Micronbox offers a direct, owned channel to verified audiences—maintaining NeoN’s ability to deliver authenticated targeting at scale.

The Integrated Ecosystem Advantage

Individually, each utility delivers significant consumer value whilst enhancing NeoN’s core capabilities. Together, they create a self-reinforcing ecosystem with powerful network effects:

  1. Complementary Data Signals: Behavioural patterns across utilities provide multi-dimensional understanding of consumer preferences
  2. Cross-Utility Engagement: Users of one service naturally discover and adopt others, creating efficient customer acquisition
  3. Enhanced Targeting Precision: Combined intelligence enables targeting capabilities that rival or exceed traditional platforms
  4. Sustainable Value Exchange: Genuine utility ensures ongoing consumer engagement, creating persistent rather than transactional relationships

This ecosystem approach transcends traditional adtech strategies that focus solely on targeting efficiency without addressing the fundamental attention recession crisis. By creating services people actively value, NeoN establishes reliable “hotlines” to consumers—solving the very problem that creates AdWaste in the first place.

For brands seeking alternatives to Google and Meta’s increasingly expensive walled gardens, NeoN’s email utilities create not merely another advertising channel but a fundamentally different approach to consumer relationships: one built on authenticated identity, genuine value exchange, and sustainable attention economics.

Additional Readings:

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The NeoMarketing Era

For far too long, marketing has been trapped in a cycle of profitless prosperity—growing revenues that never translate into sustainable profits due to spiralling acquisition costs and stagnant customer lifetime value. This dysfunctional system redirects approximately $500 billion annually into “AdWaste”—money spent reacquiring customers brands already know, creating perhaps the greatest untapped profit opportunity in modern business.

Marketing’s mission must fundamentally change. Beyond building brands and driving performance campaigns, marketing must become the primary engine for profitable growth by systematically eliminating AdWaste and driving Earned Growth. This transformation heralds NeoMarketing—marketing’s third great era following Traditional Marketing (1950s-1990s) and Modern Marketing (2000s-2020s).

NeoMarketing is built on a revolutionary segment-based framework. Unlike demographic or psychographic segmentation, the BRTN approach categorises customers based on their actual engagement patterns and value contribution:

Best customers (top 20%) receive hyper-personalised experiences that maximise individual LTV and transform them into referral engines through Progency’s AI-orchestrated journeys.

Rest customers (middle 50%) benefit from NeoMails (and Progency) that establish reliable daily hotlines, preventing the attention recession that leads to dormancy and costly reacquisition.

Test customers (dormant 30%) are precisely targeted through NeoN’s authenticated identity network at a fraction of traditional platform costs, dramatically reducing reacquisition waste.

Next customers (new acquisitions) are efficiently targeted through NeoN’s sophisticated DMP capabilities, leveraging cross-brand intelligence to identify genuinely high-potential prospects.

Two breakthrough innovations make this vision achievable:

  • Progency transforms martech from “software without service” into “software with success”—combining proprietary platform capabilities with specialist expertise and AI agent orchestration in a performance-based model. By eliminating platform costs in favour of revenue-sharing tied directly to measurable outcomes, Progency creates perfect alignment between technology providers and business results.
  • NeoN reimagines advertising through authenticated identity, enabling brand-to-brand collaboration without expensive intermediaries. This cooperative approach simultaneously allows brands to “print money” by monetising their engaged audience and “save money” through dramatically more efficient customer acquisition.

These innovations are enhanced through proprietary email utilities that generate both invaluable first-party data and additional inventory channels—creating a self-reinforcing ecosystem that gradually reduces dependency on third-party platforms whilst building targeting capabilities that rival or exceed traditional adtech giants.

The cumulative impact of these innovations isn’t merely improved efficiency but a fundamental transformation in marketing economics. By maximising LTV through deeper, more valuable customer relationships whilst simultaneously minimising CAC through precision targeting and referral programmes, NeoMarketing creates a sustainable growth engine that eliminates the wasteful acquisition cycles plaguing modern businesses.

For CMOs, this is an unprecedented opportunity to evolve from managing a cost centre to becoming C-Suite MVPs—executives who transform marketing from a necessary expense into the central profit engine driving sustainable business growth. By abandoning the sinking ship of acquisition addiction and embracing the lifeline of NeoMarketing’s retention-first approach, CMOs can finally deliver the profitability metrics that cement their strategic importance in the boardroom.

The future belongs to organisations that recognise this shift—those who redirect resources from wasteful acquisition to value-creating retention strategies focused on genuine customer needs rather than platform metrics. Brands that continue the acquisition addiction will find themselves trapped in an increasingly expensive race to the bottom, whilst those who embrace NeoMarketing will discover the ultimate competitive advantage: profitable growth through authentic, valuable customer relationships.

Thinks 1600

Adam Grant: “Givers add more value than takers. Studies show that tech companies are more profitable when servant leaders are at the helm. The competitive advantage comes from treating people better than they expect and earning their trust, which makes it easier to attract, motivate and retain talent. That doesn’t mean being soft on people. Servant leaders aren’t shy about dishing out tough love. But they put their mission above their ego, and they care about people as much as performance.”

Stanley McChrystal: “Fear defines us. Not by its presence, but by how we respond to it. There are two kinds of fear. The first is primal. It grips us when lightning strikes too close or when the crack of a bullet signals imminent danger. In those moments, our bodies freeze, and our focus narrows. But with time, experience and discipline, we recover. We learn to navigate perilous situations, even to function in the face of fear. The second kind of fear is more insidious. It seeps into our daily lives, lingers in the background and dictates our choices without us realizing it. America has always known fear — war, economic pain, uncertainty…There is no magic cure for fear. But there is an antidote: rules.”

WSJ: “As China produced more and more stuff, America became even more adept at producing services. Many of these can’t be traded globally: Somebody in London can’t easily go to a dentist in San Diego. But some, like software and other intellectual property items, can. In 2023, the U.S. exported $24 billion in advertising services, for example. The U.S. now exports in excess of $1 trillion-worth of services—far more than any other country. Moreover, America’s services exports are undercounted as a result of companies moving overseas the rights to intellectual property developed in the U.S.—like patents and trademarks—for tax purposes…In new research, Hanson and Enrico Moretti find that in 1980 manufacturing accounted for 39% of the U.S. jobs where workers earned high wages (after adjusting for factors such as education). By 2021 that had dropped to 20%. Over the same period, the share of high-paying jobs in the finance, professional and legal industries jumped from 8% to 26%.”

Marc Benioff: “I would say that it is the beginning of digital labour and that it has been fun being in the software industry. Enterprise software is maybe a multi $100 billion or total addressable market right now. It is a $3-12 trillion opportunity in digital labour, and agents and robots – and yes, apps and data are still going to be a critical part of it, though.”

FT: “Factories across China at the low-end of manufacturing are facing the same dilemma — either they invest in automation that shrinks the number of jobs, or they slowly wither away. The result, in the view of researchers and economists, is a painful shift away from low-cost, labour-intensive production that could leave millions of older, lower skilled workers in the lurch. Analysis of 12 labour-intensive manufacturing industries between 2011 and 2019 by academics at Changzhou University, Yancheng Teachers University and Henan University found that average employment shrank by roughly 14 per cent, or nearly 4mn roles, between 2011 and 2019. Roles in the textile industry shrank 40 per cent over the period.”

From SaaS to Success: The Progency Proposition

Published May 19, 2025

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The recent SaaSBoomi Annual 2025 was a watershed moment that crystallised a fundamental truth: the traditional SaaS model is reaching its evolutionary endpoint. While conversations buzzed about “SaaS AI” and the opportunity to capture “salary TAM” through Agentic AI (alongside India’s domestic software market), these discussions merely scratched the surface of a more profound shift required in how software delivers value in the AI era

I asked Perplexity to summarise the key themes discussed:

  1. Transition from SaaS to AI: The event emphasised the pivotal shift from traditional SaaS to AI-powered solutions. Sessions explored how companies can integrate AI into their products and processes, reinvent business models, and address challenges posed by this transition.
  2. AI Product and Technology: A significant focus was placed on moving beyond AI hype to delve into practical engineering and product design efforts. This included frameworks for scalable architectures, data mastery, compliance, security, and personalized user experiences.
  3. Vertical AI Opportunities: The event highlighted sector-specific opportunities in industries such as manufacturing, energy, and life sciences. Founders were encouraged to collaborate with industry leaders to solve real-world problems using AI solutions/
  4. India’s SaaS Advantage: The event spotlighted India’s potential to become a global hub for SaaS and AI innovation, leveraging its talent pool and market opportunities. Discussions also covered India’s software market outlook for 2035.
  5. New World Order: A recurring theme was the emergence of a “New World Order,” where mastering AI integration with industry expertise would define successful companies of the future. This theme underscored India’s role in leading this transformation.

A post-event Rothschild report added more colour to the impact of AI on SaaS:

  • AI is fundamentally changing SaaS, making conventional subscription-based models irrelevant as AI-driven automation takes over
  • Future software will not just offer tools but will act as autonomous agents executing business processes without human intervention
  • Companies relying on feature-based SaaS offerings will struggle as AI-driven automation reshapes the landscape
  • AI-powered business applications will move from static workflows to self-learning systems capable of real-time decision-making
  • The age of static, subscription-based SaaS pricing is coming to an end as
  • AI disrupts how software is sold and monetized
  • Future AI-first solutions will shift towards usage-based, outcome-driven pricing where businesses pay for automation, intelligence, and efficiency, not just access to software

Yet these observations, while insightful, don’t address the most critical evolutionary leap SaaS must make: transforming from software vendors to success partners. This is the essence of Progency—the fusion of product, agents, and agency that reimagines how software creates value. The harsh reality is that SaaS has largely been software without service, leaving customers with powerful tools but inadequate expertise to leverage them effectively.

This fundamental disconnect has created an execution gap where brands typically utilise only 30-40% of their platform capabilities despite significant investments. SaaS companies must now add a thin service layer—initially human-led but increasingly powered by AI agents—that ensures customer outcomes rather than merely providing access to features.

By embracing performance-based pricing tied directly to business results, SaaS companies create perfect alignment with their customers: they win only when their customers win. This shift from selling inputs (features, seats, API calls) to guaranteeing outputs (revenue growth, cost savings, measurable business improvements) transforms the SaaS business model from a capped subscription revenue stream to an unlimited upside opportunity with truly “infinite” TAM.

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Previous Writings

NeoSaaS: From India First to Global Leader in Big Martech (Dec 2024): “As the world’s foremost hub of software engineering talent still awaits its first homegrown software products multinational, this series explores how a powerful convergence of Indian innovation, US market access, AI capabilities, and strategic acquisitions could finally produce that elusive global colossus – one that dominates at home while becoming a formidable player in the US and beyond. Let’s call this company “NeoSaaS”. The name signifies more than just another software venture – it represents a transformational business model built on the foundation of four interconnected pillars: strategy, software, services, and profit sharing (the 4S framework). This unique approach transcends traditional SaaS boundaries, creating a blueprint for a world-class software entity emerging from India.” I focused on the AdWaste opportunity in marketing. “While most SaaS companies focus heavily on their software offerings, merely providing great software is insufficient for creating a game-changing solution. NeoSaaS must transcend traditional SaaS limitations by embracing a comprehensive 4S framework that combines product and agency (Progency) and transforms it from a vendor into a true partner in customer success: Strategy, Software (Stack), Service (Kaizen Progency), Sharing (Profit)… This 4S framework ensures that NeoSaaS delivers comprehensive solutions rather than just tools. By combining strategic guidance, powerful software, continuous service improvement, and aligned incentives, NeoSaaS creates an ecosystem that truly enables customer success. The result is not just a product deployment but a transformative partnership that drives measurable business impact.”

SaaS Futures: Exploring New Revenues Streams (Aug 2024): In this series, I focused on new products, new markets, new geos, services, and M&A. On services, I wrote: “SaaS and Services have traditionally been viewed as fundamentally different business models, akin to chalk and cheese for most companies. The mindsets driving these two approaches are indeed quite distinct. SaaS companies typically focus on scalability, product development, and recurring revenue, while service-oriented businesses emphasise customisation, client relationships, and project-based work. The economic metrics for these models also diverge significantly. SaaS companies are often valued based on their high gross margins and the predictability of their recurring revenue, resulting in higher valuation multiples. In contrast, services businesses generally have lower gross margins due to the labour-intensive nature of their work and are typically valued at lower multiples. However, in today’s challenging business landscape, where competition is fierce and customer expectations are ever-increasing, software companies must be open to exploring new avenues for growth and customer satisfaction. This is where a thin layer of services as an add-on capability can prove invaluable.”

New SaaS: Services, AI Agents, Sharing (May 2024): I wrote about the new SaaS: Services, AI Agents, Sharing. “Services…bring in people into the product proposition to ensure continuous monitoring and improvement. This component integrates human expertise and intervention into the digital offering, enhancing the adaptability and personalisation of the software…AI Agents help automate conversations, tasks, and ‘next best action’ predictions. These autonomous, intelligent systems empower the platform by automating interactions, streamlining tasks, and providing predictive insights…Sharing (a “progency” business model) combines product and agency, to price based on performance and outcomes. It redefines the economic relationship between service providers and their customers. By adopting a performance-based pricing strategy, the focus shifts towards shared success and outcomes…The “New SaaS” can be defined as an integrated, outcome-driven ecosystem that leverages the synergistic potential of services, AI agents, and performance-based collaboration.”

Additional writings:

3

3D Evolution

As I see it, SaaS needs to evolve along three axes: a thin layer of services, AI Agents, and success-based pricing. This three-dimensional transformation will fundamentally redefine the relationship between software providers and their customers.

  1. Thin Layer of Services: From Tool Provider to Success Partner

Traditional SaaS deploys powerful platforms but leaves implementation largely to customers, creating an execution gap where capabilities exceed utilisation. A thin layer of specialised services—strategically added without transforming into a full-service consultancy—bridges this critical divide.

This services layer includes:

  • Implementation specialists who understand industry-specific workflows
  • Vertical experts who translate software capabilities into business outcomes
  • Ongoing optimisation consultants focused on continuous improvement

The goal isn’t providing extensive professional services but ensuring customers extract maximum value from their software investment. This approach transforms the vendor-client relationship from “here’s your license, good luck” to “we’re invested in your operational success.”

  1. AI Agents: From Passive Tools to Active Participants

The second evolutionary axis introduces AI agents that transform software from tools that await human instructions into systems that proactively execute business processes. These agents fundamentally alter how organisations interact with software:

  • Autonomous Operations: Agents handle routine tasks without human intervention, from data analysis to workflow orchestration
  • Predictive Intelligence: Systems that anticipate needs before users articulate them
  • Continuous Learning: Capabilities that improve automatically through usage patterns
  • Cross-Functional Coordination: Multiple specialised agents working in concert to accomplish complex business objectives

This shift goes beyond automating existing processes—it fundamentally reimagines how work gets done. AI agents don’t just augment human capabilities; they create entirely new operational paradigms where systems take initiative rather than merely responding to commands.

  1. Success-Based Pricing: From Access to Outcomes

Perhaps the most revolutionary axis is the shift from subscription-based pricing (paying for access) to success-based models (paying for outcomes):

  • Performance Metrics: Compensation tied to specific KPIs relevant to the customer’s business
  • Risk-Sharing: Vendors assume partial responsibility for implementation success
  • Unlimited Upside: Both parties benefit proportionally from exceptional results
  • Value Quantification: Rigorous measurement of software’s business impact

This approach requires vendors to develop sophisticated measurement frameworks and prediction capabilities. More importantly, it demands the courage to stand behind one’s product with financial commitments.

**

The combination of these three axes—services, AI agents, and success-based pricing—creates a new entity that transcends traditional SaaS – Progency. This isn’t incremental improvement but fundamental reinvention. Companies making this transition aren’t merely selling better software; they’re guaranteeing better business outcomes through an integrated approach that combines human expertise, autonomous intelligence, and aligned economic incentives.

For enterprise buyers, this evolution eliminates the frustration of underutilised software investments. For vendors, it transforms the addressable market from software budgets to business outcomes—exponentially increasing potential revenue while creating deeper, more strategic client relationships.

4

What’s Changed

For several years, I’ve been exploring the Progency concept within martech—the powerful fusion of product and agency capabilities. Initially, my conversations with marketers revealed a fundamental misunderstanding: many interpreted the “agency” component as merely outsourced labour performing the same tasks as their internal teams. This approach would simply shift costs without addressing the core inefficiencies that prevent outcome-based pricing models.

My perspective transformed fundamentally a few months ago during a demonstration of Netcore’s Agentic AI system. Unlike isolated agents performing discrete tasks, I witnessed a sophisticated multi-agent ecosystem working collaboratively toward complex business objectives. This revelation crystallised a crucial insight: the “gen” in Progency shouldn’t represent generic services but rather AI agents—autonomous systems that could transform execution capabilities while dramatically reducing operational costs.

Yet this insight revealed another challenge. While organisations could theoretically deploy these AI agents themselves, the reality of effective AI utilisation remains stubbornly difficult. Even after two and a half years of widespread ChatGPT adoption, most professionals still struggle with effective prompting. As I frequently remind colleagues, crafting the right instructions to generate optimal AI outputs remains an underappreciated skill—one that prevents organisations from fully leveraging even the most sophisticated AI systems.

The integration of AI agents into the Progency model transcends the original vision of a thin services layer with performance-based pricing. While that approach would have offered incremental improvements and modest upside potential, it wouldn’t have created the scale necessary to make Progency economically transformative across diverse client portfolios. AI agents fundamentally alter this equation by enabling a previously unimaginable economic model: zero upfront platform costs coupled with compensation tied exclusively to measurable business outcomes.

This revolutionary approach draws inspiration from adtech’s remarkable trajectory over the past two decades. The advertising technology sector has grown into a $700 billion industry boasting some of the highest gross margins and profitability in the technology sector. This extraordinary success didn’t occur through traditional software licensing or agency service models—it emerged when the industry decisively shifted from input-based metrics (cost per thousand impressions, or CPM) to outcome-based models (cost per click, or CPC).

By directly tying costs to measurable business results, adtech created perfect alignment between platform capabilities and client objectives. The platforms that delivered superior outcomes thrived; those that couldn’t deliver results quickly perished. This ruthlessly efficient model drove unprecedented innovation and value creation for both providers and their clients.

For established SaaS companies, the Progency model represents both an extraordinary opportunity and an existential imperative: disrupt your own business model before newcomers inevitably do. As AI capabilities accelerate, the window for this transformation is rapidly narrowing. The first-movers who successfully implement the Progency approach—integrating specialised services, AI agent orchestration, and outcome-based economics—will establish competitive advantages that laggards simply cannot overcome.

This is more than just a pricing shift or a service enhancement; it’s a fundamental reimagining of the relationship between software providers and their customers. In the Progency future, vendors don’t sell access to capabilities—they guarantee business results, creating a virtuous cycle of continuous improvement where both parties’ interests align perfectly around measurable outcomes.

5

Startup!

What should SaaS companies do to embrace this revolutionary model? This question has occupied my thoughts particularly in relation to Netcore’s Martech SaaS platform, though the principles apply broadly across the enterprise software landscape. My recommendation: create an internal startup dedicated to building a Progency offering, focusing initially on prospects where it is a struggle to gain traction. In essence, carve out a blue ocean opportunity within the increasingly commoditised red ocean of SaaS.

Incumbent SaaS companies possess three critical advantages: established clients, recurring contracts, and predictable cashflows. These should continue undisturbed while a separate, dedicated team launches a “Progency Startup” within the organisation. This new venture leverages the full capabilities of the existing platform alongside the thin managed services layer that the SaaS business has already developed. Over time, the human elements within these services will be systematically augmented and eventually replaced by AI agents, creating unprecedented economies of scale.

The fundamental differentiators for this internal startup lie in its go-to-market strategy and pricing model.

Every business exhibits a power law distribution across its customer base: approximately 20% of customers (the “Best” segment) typically generate 60-80% of revenue. The Progency Startup should strategically target the next 40%—the “Rest” customers who account for the remainder of revenue but often receive disproportionately less attention. (The final category, “Test,” encompasses dormant and churned customers requiring separate reactivation/reacquisition strategies.)

The Progency Startup’s revolutionary proposition to prospective clients is straightforward yet compelling: “Let us take ownership of your ‘Rest’ customer segment with zero platform fees. This allows your team to focus exclusively on your highest-value customers while we apply our PEAK framework—Platform, Experts, AI Agents, and Kaizen methodology—to maximise value from your underserved middle segment.”

This approach creates a win-win scenario. Clients eliminate costs associated with servicing these customers while maintaining revenue streams. Meanwhile, the Progency demonstrates its superior capabilities through a genuine skin-in-the-game approach—earning money only when it delivers revenues exceeding established baselines. The underlying thesis is powerful: Progency’s orchestrated AI agents will consistently outperform the client’s human teams in addressing the personalised needs of this long-tail customer segment.

While the “Best” customers ultimately represent the more lucrative prize, successfully demonstrating measurable results with the “Rest” segment accomplishes something far more valuable than gaining initial market entry—it earns the Progency a strategic seat at the decision-making table. Success creates an irrefutable case for expanding the model to encompass the client’s entire customer base.

**

The path forward for SaaS companies is clear: reinvent themselves through the Progency model before market forces make this transition inevitable. Begin at the periphery where resistance is lowest, demonstrate compelling results through outcome-based economics, and methodically expand toward the core business. The performance-based paradigm of Progency it the destined evolution for enterprise software that will separate tomorrow’s winners from legacy providers clinging to yesterday’s business models.

The question isn’t whether this transformation will occur, but rather: which visionary companies will lead this revolution, and which will follow belatedly—if they survive at all?

6

Other Industries

I asked the AIs to provide examples of success-based models from other industries.

While the evolution from SaaS to Progency draws significant inspiration from adtech’s transformation, numerous other industries have successfully implemented outcome-based economic models. These precedents not only validate the viability of success-based approaches but offer valuable blueprints for implementation within the enterprise software sector.

Healthcare’s Value-Based Revolution

Perhaps the most ambitious shift toward outcome-based economics is occurring in healthcare, where fee-for-service models are gradually giving way to value-based care arrangements. Under these frameworks, providers receive compensation based on patient outcomes rather than the volume of procedures performed.

Accountable Care Organisations (ACOs) in the US exemplify this approach—receiving financial rewards when they improve patient health metrics while simultaneously reducing overall treatment costs. This transformation fundamentally realigns healthcare provider incentives from maximising billable procedures to optimising patient health outcomes—a perfect parallel to Progency’s shift from selling software access to delivering measurable business results.

Energy Sector’s Performance Contracting

Energy Service Companies (ESCOs) have pioneered performance-based models through Energy Savings Performance Contracts. These innovative arrangements allow organisations to implement energy efficiency upgrades with zero upfront capital investment. The ESCO finances and implements the improvements, then receives compensation exclusively from the documented energy savings achieved over time.

This model has transformed energy efficiency from a capital expenditure decision to an operational improvement with guaranteed positive ROI. The parallel for SaaS is compelling: rather than requiring customers to invest in software licenses hoping for eventual returns, Progency enables organisations to implement solutions with compensation tied directly to measurable efficiency gains or revenue improvements.

Legal Services’ Contingency Approach

The legal industry has long employed outcome-based economics through contingency fee arrangements, where law firms receive payment only upon successful case outcomes. This approach fundamentally transforms the attorney-client relationship by creating perfect alignment around a common objective—winning the case.

What makes this model particularly relevant to Progency is its risk-shifting mechanism. The service provider (law firm) assumes significant upfront investment with compensation contingent on delivering specific results. This arrangement has democratised access to legal representation while ensuring lawyers are incentivised to maximise client outcomes rather than billable hours.

Manufacturing’s “Power-by-the-Hour”

Traditional industrial manufacturers have revolutionised their business models through outcome-based approaches like Rolls-Royce’s pioneering “Power-by-the-Hour” concept. Rather than selling jet engines outright, Rolls-Royce charges airlines based on engine uptime and performance. This transforms the relationship from a transactional hardware purchase to an ongoing partnership focused on operational reliability.

This approach mirrors Progency’s potential in enterprise software—shifting from selling products to guaranteeing operational performance. The customer no longer bears all the risk of implementation success; instead, the provider is directly incentivised to ensure continuous optimal performance.

Education’s Income Share Agreements

Perhaps the most innovative recent application of outcome-based economics appears in education, where coding bootcamps and alternative educational providers implement Income Share Agreements (ISAs). Students pay no upfront tuition, instead committing to share a percentage of their post-graduation income for a defined period.

This model creates extraordinary alignment between educational providers and students—schools succeed financially only when their graduates secure well-paying positions, driving relentless focus on employable skills and job placement. Similarly, Progency succeeds only when its clients achieve measurable business improvements, creating an educational incentive to continuously enhance capabilities and outcomes.

**

The Common Thread: Risk Shift and Incentive Alignment

What unites these diverse examples is a fundamental reallocation of risk and realignment of incentives. In each case, service providers assume greater upfront risk in exchange for participation in the value they create. This arrangement naturally drives continuous improvement, as providers constantly seek to enhance outcomes that directly impact their compensation.

For SaaS companies considering the Progency model, these precedents demonstrate that success-based approaches can create thriving economic ecosystems across widely varying industries. More importantly, they illustrate how such models can transform client relationships from transactional vendor interactions to true strategic partnerships—precisely the evolution enterprise software needs in the age of AI and growing customer expectations.

7

Critique

I then asked the AIs for a critical assessment of the Progency ideas.

Implementation Hurdles

Measurement Complexity
The success-based model hinges on accurately measuring outcomes attributable to the software. In complex business environments, establishing clear causality between software usage and business results can be exceptionally difficult. Factors beyond the software’s control—market conditions, competitor actions, internal execution—significantly impact outcomes, creating potential attribution disputes that could undermine the entire model.

Scope Definition and Baseline Establishment
Defining what constitutes “success” and establishing appropriate performance baselines presents considerable challenges. Without rigorous, mutually agreed frameworks, companies risk either setting targets too low (creating windfall profits for Progency providers) or too high (making success impossible). The initial negotiation period could become protracted and contentious.

Economic Viability Concerns

Cash Flow Challenges
The zero-upfront cost model, while attractive to clients, creates significant cash flow challenges for providers. Traditional SaaS businesses rely on predictable subscription revenue to fund ongoing operations, development, and growth. Progency providers must secure substantial capital to sustain operations during the potentially lengthy period before success metrics generate revenue—particularly problematic for smaller SaaS companies or startups.

Risk Allocation Imbalance
While sharing risk theoretically creates alignment, the Progency provider potentially assumes disproportionate risk. Factors outside their control (executive decisions, organisational changes, market shifts) can undermine performance, creating financial exposure without corresponding control. This imbalance may necessitate complex contract provisions that reintroduce the very complexity Progency aims to eliminate.

Practical Business Constraints

Scalability Limitations
The thin services layer, even augmented by AI agents, may face scalability challenges across diverse client requirements. Each client implementation requires customisation and contextual understanding that may resist full automation. As the client base grows, maintaining quality while expanding AI agent capabilities across different industries and use cases presents substantial technical and operational challenges.

Vertical Expertise Requirements
Effective implementation demands deep industry-specific knowledge that most horizontal SaaS providers lack. Building this expertise across multiple verticals requires significant investment and time, potentially limiting Progency’s applicability to specific industries or use cases in the near term.

Strategic Risks

Competitive Positioning Challenges
Progency represents a hybrid model between pure SaaS and consulting services. This creates potential competitive disadvantages against both specialised SaaS providers (with lower operational costs) and established consultancies (with deeper domain expertise). Finding the optimal positioning in this landscape may prove challenging.

Client Dependency Concerns
The success-based model could inadvertently create unhealthy dependencies on specific clients. If a disproportionate share of revenue comes from a few high-performing implementations, the Progency provider becomes vulnerable to client leverage or loss.

Organisational Resistance
Established SaaS companies with traditional subscription-based models may face significant internal resistance to adopting such a radical shift. The transition requires not just technological changes but fundamental cultural and mindset shifts across the organisation.

Technological Limitations

AI Capability Reality Check
Your model heavily relies on AI agents reaching a sophistication level that may be further away than anticipated. While AI capabilities are advancing rapidly, fully autonomous agent systems capable of replacing human expertise across complex business functions remain largely theoretical. Over-promising and under-delivering on AI capabilities could undermine client trust in the entire model.

Integration Complexity
The seamless operation of AI agents requires robust integration with client systems. Legacy infrastructure, data quality issues, and API limitations could significantly constrain effectiveness, particularly in enterprises with complex technology landscapes.

Ethical and Regulatory Considerations

AI Governance and Oversight
As autonomous AI agents take on more critical workflows, questions of accountability and liability become increasingly important. Who bears responsibility for AI errors? A comprehensive governance framework would be essential to maintain trust and transparency.

Compliance Challenges
Industry-specific regulations (GDPR, HIPAA, financial services requirements) add layers of complexity to AI agent deployment. Each vertical may require specialised compliance approaches, further complicating scalability.

**

Conclusion: Promising but Nuanced

The Progency model presents a genuinely innovative vision for SaaS evolution, addressing fundamental limitations in the current subscription paradigm. However, its successful implementation will require careful navigation of the challenges outlined above.

A more measured approach might involve:

  1. Hybrid Models: Combining baseline subscription fees with performance-based upside to balance cash flow needs while maintaining outcome alignment
  2. Controlled Scaling: Starting with specific vertical markets where outcomes are more easily measured and attributed
  3. Phased AI Integration: Gradually introducing AI agents alongside human expertise rather than assuming immediate wholesale replacement
  4. Selective Client Partnerships: Initially targeting clients with modern tech stacks and collaborative mindsets to establish proof points

Thinks 1599

Shane Parrish: “Great ideas often look wrong at first; that’s why the independent-minded discover them.”

Rudy de Waele: “Have you ever stopped to think about the role models who shaped your life? Who were the people—real or imagined—who influenced your path, inspired your passions, gave you courage, or made you feel seen? Whether we’re aware of it or not, we are continuously shaped by the people we look up to. They appear in many forms: a superhero from comics or screens, a parent, an artist, a writer, an entrepreneur, a coach, a teacher, a spiritual guide, a visionary leader… sometimes even someone we’ve never met. As we grow, our role models evolve with us, helping us navigate life’s many thresholds. In turn, we all become role models ourselves—to our children, to the youth around us, to our peers, and even to our elders—through the integrity we embody and the lives we choose to lead. Reflecting on who inspired us at different stages can offer deep insight into our journey—how we made decisions, why we changed course, and what we valued at a given time.”

FT: “Household debt has grown to about 43 per cent of GDP in June, from just over 35 per cent in March 2020, according to the latest RBI data. A crackdown in 2023 by the Reserve Bank of India, which warned retail lending was getting out of hand, has hit financial sector earnings just as many Indians are struggling to repay their loans. More broadly, the unsecured credit crisis threatens to puncture India’s narrative that it is a rising power driven by an expanding moneyed cohort. Prime Minister Narendra Modi wants the country to escape the middle-income trap, a period of stagnation that follows high growth, and reach developed status by 2047 — a century after independence from Britain. That stress is “fuelling the kind of inequality that we are seeing”, says Kunal Kundu, India economist at Société Générale. “While India still remains the fastest growing large economy, what people do not realise is there is only a small part that’s driving growth.””

SaaStr: “So that 30 person, $100m ARR AI B2B start-up?  It’s possible.  For sure.  We have examples now.  It’s even cool.   But … But … can the Small and Mighty Startup compete that way in the coming years?  And can it sell and scale sales? I’m not so sure.  At least, I think the answer, is not always. Efficiency is a wonderful thing.  But AI is also making the world incredibly competitive.  Even in spaces that didn’t used to be all that competitive. Most of us are having to step up much more just to keep up.”

WSJ: “Focusing on what is both essential and foundational has powered Nvidia’s growth. It’s able to do so many things because it knows what it can’t or won’t do.”

From CMO to C-Suite MVP: How Progency Transforms the Marketing Leader’s Game

Published May 18, 2025

1

Shifting Sands

“How do I earn a seat at the high table? What I mean is: how do I gain true influence in the C-suite? Marketing is seen as peripheral – just branding and delivering clicks. None of my peers have risen to the corner office. Most hop laterally every 2-3 years because success can’t be measured, and marketing is viewed as a cost centre. I don’t want that fate. What can I do? How do I turn marketing into a boardroom priority?

This candid question from a CMO at a recent meeting resonated deeply with me. My response was direct: “Transform yourself from a traditional CMO into a Chief AI and Profits Officer. Become the undisputed champion of profitable growth.” I added, “Develop a broader business acumen beyond marketing—master P&L, strategy, and cross-functional leadership to position yourself for the CEO leap.”

As I reflected on our conversation afterward, I realised this challenge echoes across countless interactions with marketing leaders. I’ve explored this disconnect before in my essays Why CMOs Don’t Become CEOs – and How They Can and Profitless to Profipoly: A CEO-CMO Dialogue on Marketing’s New Direction. The path forward for marketers has always been clear to me: own retention, not just acquisition, and drive measurable profitability.

While many factors lie beyond a marketer’s control—product mix, supply chain, logistics, physical retail—ambitious CMOs can revolutionise their function (and future) by leveraging the convergence of omnichannel commerce and Agentic AI. This transformation enables them to make profitable growth their North Star, measured through Earned Growth within their department and contributing to the company’s Rule of 40 performance.

This evolution won’t be easy. Most marketers have built careers on branding initiatives and performance marketing campaigns, relegating customer retention and loyalty to secondary concerns in the relentless pursuit of acquisition. Customer Acquisition Cost (CAC) has dominated the conversation, while Customer Lifetime Value (LTV) has languished in the background. But in today’s reality of spiralling acquisition costs, rapidly shifting customer expectations, and compressed margins, the marketing playbook demands a complete rewrite.

Generative AI has begun improving content creation efficiency and campaign performance—a promising start, but insufficient. What marketers truly need is a solution to the punishing CAC-LTV squeeze. This requires addressing two fundamental failures: the “not for me” problem that crudely segments unique individuals, and the “no hotline” problem that leads to attention recession and customer disengagement.

Fortunately, breakthrough innovations now make this possible. AI Marketing Agents, AI Twins, and Channels 2.0 offer unprecedented opportunities to enhance LTV, reduce CAC, and eliminate the staggering 70% AdWaste (spent on reacquiring customers) currently haemorrhaging marketing budgets. For the first time, CMOs can take ownership of profitability by building deep, enduring customer relationships through truly personalised experiences—the essence of the NeoMarketing revolution.

Progency takes this transformation even further by making martech (retention and referrals) as frictionless as adtech (acquisition and reacquisition). It brings unprecedented efficacy to marketing by enabling the once-utopian dream of a “Department of One” serving a “Segment of One.” For forward-thinking CMOs, Progency represents the fast track to becoming the Most Valuable Player in the C-Suite—the executive who transforms marketing from a cost centre into the organisation’s primary profit engine.

2

The Boardroom Reckoning

The quarterly board meeting looms. As CMO, you’ve prepared slides showcasing impressive campaign metrics: growing impressions, declining cost-per-click, expanding social reach, and rising email engagement. Yet beneath the polished presentation lies a gnawing anxiety—the inevitable questions that expose marketing’s vulnerability in the C-suite conversation.

These aren’t hypothetical scenarios. In boardrooms across industries, marketing leaders face a trio of questions that strip away marketing jargon and demand business-focused accountability:

“Why are acquisition costs still rising despite increased spending?”

This question strikes at marketing’s efficiency paradox. Despite growing sophistication in targeting and attribution, CAC continues its relentless climb, typically increasing 15-25% annually through auction-based platforms. Traditional agencies and adtech vendors offer short-term tactical optimisations, but these merely slow the bleeding rather than addressing the systemic issue: 70% of digital marketing budgets fund the expensive and wasteful reacquisition of customers who already know the brand.

When the CFO juxtaposes rising marketing budgets against diminishing marginal returns, the CMO is left defending a model fundamentally misaligned with financial discipline. The uncomfortable truth? Marketing now acts as a collection agent for Google and Meta, managing ever-larger budgets that primarily enrich platforms rather than building sustainable customer relationships.

“What’s our actual return on marketing investment beyond impressions and clicks?”

Here, boardroom patience with proxy metrics evaporates. While marketers have grown comfortable with engagement statistics, executives demand direct connections to revenue and profitability. Traditional attribution models—last-click, first-touch, multi-touch—all suffer from fundamental flaws that obscure true causality.

Even more damaging is marketing’s disconnect from the customer lifecycle. By focusing predominantly on acquisition rather than retention, traditional marketing frameworks prioritise top-line growth while neglecting the more profitable strategy of maximising LTV. This leaves CMOs struggling to articulate marketing’s contribution to sustainable business growth, appearing tactically proficient but strategically limited.

“How does your retention strategy compare to our acquisition strategy in terms of ROI?”

This question exposes perhaps the most significant blind spot in contemporary marketing. While most CMOs can recite their CAC across channels with precision, far fewer can articulate their retention economics with equal confidence. The reality? Increasing customer retention by just 5% can boost profits by 25-95% according to Bain & Company research, yet marketing departments typically allocate only 10-15% of their budgets to retention initiatives.

The traditional agency model compounds this problem by focusing predominantly on campaigns and creative rather than relationship-building. Similarly, martech vendors sell sophisticated platforms but leave execution to overstretched internal teams, creating an implementation gap where capabilities exceed actual utilisation.

When pressed on retention ROI, most CMOs lack the measurement framework, technological infrastructure, and operational model required to deliver a compelling answer—leaving them exposed precisely where the greatest opportunity for profitable growth exists.

**

These questions reveal why marketing often fails to earn its rightful place in strategic leadership discussions. Traditional approaches—whether through creative agencies or technology platforms—leave CMOs equipped with impressive tactical capabilities but lacking the strategic framework to connect marketing investments directly to business outcomes that matter to the board.

The path to C-suite credibility demands a fundamental reimagining of the marketing function—one that transforms marketing from a cost centre into the primary profit engine for sustainable growth. This is where Progency enters the conversation.

3

Primer

Modern Marketing is about two strands: adtech and martech. Adtech acquires, martech monetises. But this is easier said than done. Adtech is easy – agencies do the heavy lifting to deliver the customers through the virtual door. But adtech is also expensive – auction platforms maximise revenue for platforms at the cost of brands. The adtech black boxes have taken away much of the marketing control and limited the fine-tuning that marketers or agencies can do.

Martech platforms are just the opposite. Myriad complex point solutions offer zillions of tuning parameters and data points. From segment creation to journey orchestration to campaign execution to insights generation to fine-tuning of the next day’s activities, there is deep involvement from the CRM/retention team. Data needs to be stitched together at various points in the customer journey. Even though every customer is unique, marketers have to bunch tens of thousands of them into segments because it is humanly impossible to craft individual pathways for each of them. The daily drudgery saps energy and reduces efficiency and efficacy, which in turn feeds the adtech machine.

If adtech is a leaky faucet and martech is the bucket catching drips, then what’s needed is to replace both with a sealed pipeline. This is where Progency steps in – making martech as easy as adtech. Progency is not just a transfer of labour costs from the brand to an outsourced entity. Progency combines the power of the martech platform with experts who understand verticals along with AI agents which take care of the mechanical work, continuously monitor trends, and are built for continuous improvement. This is the PEAK framework: Platform, Experts, AI agents, and Kaizen.

From Execution Gap to Revenue Engine: The PEAK Framework

At the heart of marketing’s profitability crisis lies what can be called the “execution gap”—the vast difference between martech’s theoretical capabilities and its practical implementation. While brands invest millions in sophisticated platforms, they typically utilise only 30-40% of available features. This isn’t due to lack of ambition but to fundamental operational constraints: limited resources, fragmented data, and the sheer complexity of modern marketing operations.

Progency’s PEAK framework directly addresses this gap through four integrated components:

Platform: Unlike traditional agencies that rely on third-party tools, Progency builds upon proprietary martech infrastructure with deep integration capabilities. This technological foundation provides complete control over execution while eliminating dependency on external systems. For example, Progency’s proprietary CDP (Customer Data Platform) unifies fragmented customer data across touchpoints, enabling real-time decisioning that most brands can only theorise about.

Experts: Specialist talent focused on specific industry verticals brings contextual understanding that generic agencies cannot match. These professionals collaborate with AI systems rather than competing with them, applying human judgment where it adds the most value. When a fashion retailer needs to understand seasonal buying patterns or a financial services firm requires compliance-sensitive communications, these experts provide the domain knowledge that purely technological solutions lack.

AI Agents: A sophisticated “AI Marketing Department” handles complex marketing operations at scale—from audience segmentation and content creation to journey orchestration and performance analysis. This multi-agent system—coordinated by an AI Co-Marketer—includes specialised agents for content, journey orchestration, segmentation, analytics, and testing, enabling seamless execution across the customer lifecycle.” All agents are coordinated by an AI Co-Marketer that ensures alignment with brand guidelines and business objectives. This agent ecosystem enables true N=1 (one-to-one) personalisation—treating each customer as a unique individual rather than a segment member—without proportionally scaling human resources.

Kaizen: The Japanese philosophy of continuous improvement ensures relentless optimisation across all facets of marketing performance. Unlike the campaign-based thinking that dominates traditional marketing, Kaizen implements systematic processes for testing, learning, and enhancing every customer interaction. This creates a constant upward trajectory of performance rather than the peaks and valleys typical of campaign-driven approaches. This continuous improvement loop compounds ROI over time, turning marketing from a cost centre into a self-tuning growth engine.

Together, these components transform marketing from a series of disconnected campaigns into a continuous value-creation system. By addressing the execution gap that plagues traditional approaches, PEAK enables brands to fully leverage their martech investments while freeing internal teams to focus on strategic initiatives rather than operational drudgery.

4

Process – 1

The traditional marketing funnel represents perhaps the most wasteful business model in modern commerce. Brands continuously pour resources into acquiring customers, only to lose a significant percentage to disengagement and dormancy, then pay a premium to reacquire those same customers through expensive ad platforms. This creates what I’ve termed “AdWaste”—the estimated 70% of digital marketing budgets (approximately $500 billion globally) spent on reacquiring existing customers rather than finding genuinely new ones.

Progency fundamentally rewires this broken economic model through the “Only Once” philosophy: acquire each customer exactly once, then invest systematically in keeping them engaged, active, and increasingly valuable over time. This approach acknowledges a fundamental truth that acquisition-obsessed marketing has long ignored: even a small increase in retention can dramatically boost revenues and profits.

This philosophy manifests through Progency’s complementary solutions targeting different customer segments:

Best Customers (20% of database): These high-value, highly engaged customers typically generate 60-80% of revenue and 200% of profits. While they warrant the brand’s dedicated internal attention, Progency enhances these relationships through predictive analytics that identify cross-sell and upsell opportunities, timely intervention when engagement signals waver, and incentivised referral programmes that transform best customers into acquisition engines.

Rest Customers (50% of database): This critical middle segment—showing declining engagement within the past 30-90 days—represents both the greatest risk and opportunity. Progency’s Neo360 delivers comprehensive lifecycle optimisation through AI-orchestrated personalisation across all channels, seamless cross-channel journeys, and continuous optimisation. Meanwhile, NeoMails establishes reliable daily “hotlines” through interactive email experiences, preventing the attention recession that leads to dormancy.

Test Customers (30% of database): For dormant customers (inactive 90+ days), Progency’s NeoN provides a PII-based advertising network that transforms reacquisition economics. Instead of paying premium prices on Google and Meta to reach customers already in the database, brands precisely target these individuals through the active email engagement channels of non-competing brands. This cuts reacquisition costs by 30-50% while simultaneously creating new revenue streams from existing email programmes.

Next Customers: When new acquisition is necessary, Progency ensures efficiency through authenticated identity targeting rather than cookie-based approximation, lookalike modelling based on actual customer value rather than surface behaviours, and seamless onboarding journeys that rapidly convert first-time buyers into loyal customers.

This comprehensive approach systematically eliminates the leaks in the traditional marketing funnel. By preventing customer dormancy before it begins, Progency reduces the need for expensive reacquisition while simultaneously increasing customer lifetime value through deeper, more relevant engagement.

The economic impact is transformative: brands typically see big reduction in overall marketing costs coupled with large improvement in customer lifetime value—a combined impact that can double marketing’s contribution to profitability.

5

Process – 2

Perhaps the most revolutionary aspect of Progency’s approach is its ability to deliver true N=1 personalisation at scale—treating each customer as a unique individual rather than a segment member. Traditional segmentation approaches, even when sophisticated, fundamentally fail to capture the nuanced preferences and behaviours that make each customer unique. This creates what I’ve termed the “Not For Me” problem—the persistent customer feeling that brand communications, however well-intentioned, don’t truly reflect their individual needs and preferences.

Agentic AI transforms this dynamic by enabling a degree of personalisation previously impossible at scale:

AI Twins: Digital replicas of individual customers continuously learn from every interaction, creating increasingly accurate models of preferences, behaviours, and likely future needs. Unlike traditional personas or segments that rely on statistical averaging, these twins capture the specific nuances that make each customer unique—from product preferences and price sensitivity to channel affinity and optimal engagement timing.

Contextual Understanding: Beyond static preferences, Progency’s AI system analyses situational context—time of day, device used, recent interactions, seasonal factors, and even external events—to deliver perfectly timed, relevant communications. For example, a customer browsing winter coats on a mobile device at 9 PM might receive very different messaging than the same customer viewing the same products on a desktop at lunch.

Journey Orchestration: Rather than forcing customers through predefined journey paths, Progency creates what I call “Generative Journeys”—dynamically adapting pathways that evolve in real-time based on individual actions and signals. Like Google Maps recalculating routes based on traffic conditions, these journeys continuously optimise to provide the most effective path to conversion for each unique customer.

Content Generation: AI content agents create thousands of content variations tailored to specific customer attributes and contexts. Unlike traditional approaches that might test a handful of subject lines or creative elements, this system can generate and test countless permutations to identify the perfect message for each individual.

Real-Time Learning: Every interaction—whether a click, purchase, browse, or ignore—feeds back into the AI system, continuously refining its understanding and improving future interactions. This creates a virtuous cycle where engagement improves over time as the system learns more about each customer’s preferences.

The impact of true N=1 personalisation extends far beyond incremental improvements in campaign metrics. When customers consistently receive relevant, contextually appropriate communications, fundamental relationship dynamics transform: open rates increase, click-through rates improve, conversion rates grow, purchase frequency rises, and average order value jumps.

More importantly, these metrics compound over time as the system learns and customer relationships deepen. A brand that might have lost a customer after 2-3 purchases can now extend that relationship to dozens of interactions over years rather than months.

This approach is particularly powerful for addressing the “Rest” customer segment, where timely, relevant interventions can prevent the slide into dormancy that typically leads to costly reacquisition. By solving the “Not For Me” problem through genuine personalisation, Progency transforms marketing from an interruption to be tolerated into a service that customers actively value—fundamentally changing the economics of customer relationships.

6

Pillars

Progency’s revolutionary approach manifests through three complementary solutions, each targeting specific challenges in the customer lifecycle. Brands can begin with NeoN, expand to NeoMails, and leverage the full power with Neo360.

  1. NeoN: Revolutionary Reacquisition

NeoN represents a fundamental reimagining of how brands reconnect with dormant customers. Traditional approaches rely on expensive retargeting through Google and Meta, creating the “AdWaste” phenomenon where brands pay premium prices to reach customers already in their database. Unlike cookie-based retargeting, NeoN uses first-party data partnerships to bypass platform fees.

NeoN creates an authenticated identity network that enables brand-to-brand collaboration without expensive intermediaries. Through NeoN, brands can precisely target their dormant “Test” customers through the active email engagement channels of non-competing brands. This creates a powerful dual advantage:

  • Publishers “print money” by monetising their engaged audience through interactive ActionAds embedded in their emails
  • Advertisers “save money” by reaching dormant customers at 30-50% lower cost than traditional platforms

The core innovation lies in authenticated identity—using email addresses or mobile numbers (with appropriate permissions) rather than anonymous cookies—ensuring precision targeting without the waste inherent in traditional approaches.

Interactive ActionAds within partner emails enable complete transactions without leaving the inbox, eliminating the “click-through penalty” that typically loses 80-90% of potential conversions.

For CMOs, NeoN delivers the holy grail of marketing efficiency: reduced acquisition costs, increased conversion rates, and new revenue streams from existing assets—all without compromising brand safety or customer experience.

  1. NeoMails: Redefining Engagement

Email remains marketing’s highest ROI channel, yet traditional approaches yield disappointingly low engagement rates. NeoMails transforms static communications into interactive experiences that command attention and drive action.

Through AMP technology, NeoMails incorporates three revolutionary elements:

  • Atomic Rewards (Mu): Micro-incentives embedded in subject lines create habit-forming engagement patterns, increasing open rates from single digits to 30-40% through gamification
  • Microns: 15-60 second “brain gain” experiences deliver genuine value in every interaction, combating “brain rot” from endless social scrolling
  • SmartBlocks: Interactive elements enable frictionless zero-party data collection, creating a value exchange where customers willingly share preferences in return for better experiences

NeoMails addresses the “No Hotline” problem—the inability of brands to reliably reach customers through owned channels—by creating daily engagement habits that prevent attention recession. By establishing consistent touchpoints with Rest customers, NeoMails prevents the slide into dormancy that typically necessitates expensive reacquisition.

The economic impact is substantial: reducing dormancy rates by even 10% can save millions in reacquisition costs while simultaneously increasing revenue through deeper engagement with existing customers.

  1. Neo360: LTV Engine

For brands seeking comprehensive optimisation of customer relationships, Neo360 provides end-to-end lifecycle management powered by AI orchestration. This “Department of One” handles complex marketing operations at scale—from segmentation and content creation to journey orchestration and performance optimisation.

Neo360 delivers three transformative capabilities:

  • True N=1 Personalisation: Treating each customer as a unique individual rather than a segment member, delivering precisely tailored experiences based on specific preferences and behaviours
  • Cross-Channel Orchestration: Creating seamless experiences across all touchpoints (email, website, app, messaging) with consistent, contextually relevant messaging
  • Continuous Optimisation: Implementing Kaizen methodology for systematic improvement over time, ensuring every interaction becomes more effective than the last

Neo360 operates as a parallel marketing department focused specifically on maximising customer lifetime value. While the brand’s internal team concentrates on strategic initiatives and Best customer relationships, Neo360 ensures no opportunity for engagement or monetisation is missed across the broader customer base.

The economic model aligns perfectly with brand objectives: compensation is tied directly to measurable uplift in customer lifetime value, creating a true partnership rather than a vendor relationship.

**

Together, these three pillars create a comprehensive system for transforming marketing economics. By systematically eliminating waste while maximising customer value, Progency enables CMOs to finally deliver the profitability that earns them a respected seat at the executive table.

7

Future

The CMO’s Transformation: From Cost Centre to C-Suite MVP

The modern CMO stands at a crossroads. On one path lies the familiar territory of rising acquisition costs, opaque ROI debates, and diminishing boardroom influence. On the other, a transformative opportunity: to become the C-suite’s undisputed Most Valuable Player by wielding Progency’s AI-powered arsenal to turn marketing from a cost centre into the company’s profit engine. The choice is stark—continue managing campaigns or lead a revolution in business growth.

The Economics of Transformation

For decades, CMOs have been trapped in a tactical straitjacket—optimising CPMs, juggling campaigns, chasing ROAS, and defending the ever-rising CAC before increasingly sceptical finance teams. Despite the rhetoric about customer-centricity, the reality has been clear: marketing was about acquisition, and acquisition was about spend. Retention? That was someone else’s job—or worse, an afterthought.

Progency fundamentally rewrites this narrative by addressing the boardroom’s three existential questions with surgical precision:

  • “Why are acquisition costs rising?” — NeoN slashes reacquisition costs by 30-50%, redirecting AdWaste into authenticated, brand-safe partnerships that transform how brands reconnect with dormant customers.
  • “Where’s the real ROI?” — Neo360 unlocks 20%+ revenue lifts via AI-orchestrated N=1 personalisation, transforming LTV from theoretical concept to boardroom-proof metric with clear attribution to marketing initiatives.
  • “How does retention compare?” — NeoMails rescues “Rest” customers from dormancy, boosting engagement 4-10X through AMP-powered hotlines that establish daily touchpoints and prevent the slide into disengagement.

This trifecta doesn’t just optimise marketing—it rewires its economics. By solving the “Not For Me” and “No Hotline” problems, Progency shifts the CMO’s role from budget guardian to profit architect, where every pound spent compounds into measurable business value rather than evaporating in platform fees.

From Execution Gap to Leadership Advantage

Progency’s PEAK framework (Platform, Experts, AI Agents, Kaizen) erases the execution gap that has long neutered martech’s promise. While traditional CMOs juggle fragmented platforms and overstretched teams, Progency-equipped leaders deploy a “Department of One” that scales infinitely:

  • AI Twins predict individual customer needs with eerie accuracy, turning satisfaction into anticipation by modelling preferences at the individual level
  • AI Agents craft Generative Journeys that adapt in real-time, like a concierge refining experiences based on micro-signals and behavioural patterns
  • Kaizen Methodology ensures relentless improvement, turning marginal gains into a profits flywheel that compounds over time

This isn’t just about efficiency—it’s about strategic leverage. When AI handles segmentation and journey orchestration, CMOs reclaim bandwidth to master P&L, forge cross-functional alliances, and align marketing with CFO-grade financial rigour. The result? A leader who speaks the language of EBITDA, not CTRs.

The Four Pillars of C-Suite Dominance

The transition from traditional marketing leader to C-Suite MVP requires mastering four essential capabilities that Progency uniquely enables:

  1. Profit Ownership: Progency ties compensation to LTV uplifts, forcing marketing to “eat its own cooking.” No more hiding behind vanity metrics—success is measured in margin points and customer equity. When marketing takes direct accountability for profit contribution, its strategic value becomes undeniable.
  2. Boardroom Storytelling: Armed with Neo360 and NeoMails, CMOs can map customer journeys to revenue waterfalls, replacing vague “brand lift” claims with board-ready profit attribution models. This transforms the marketing narrative from creative justification to strategic business leadership.
  3. AI Fluency: Progency transforms CMOs into AI-native leaders who command algorithms, not just creatives. This duality—art meets AI—future-proofs their role in an era where 70% of marketing tasks will be automated. The leaders who master this convergence will be irreplaceable.
  4. Ecosystem Orchestration: Through NeoN’s brand-to-brand collaboration, the CMO becomes a growth diplomat, building external alliances that amplify reach without inflating budgets. This network approach creates competitive moats that pure acquisition strategies cannot match.

These capabilities collectively transform how the CMO is perceived within the executive team—from a functional specialist to a comprehensive business leader capable of driving sustainable profitable growth.

From Marketing Leader to Business Catalyst

With Progency as a strategic partner, the CMO’s boardroom narrative changes dramatically. Rather than defending rising acquisition costs or explaining vague attribution models, they confidently present a new story: “We’ve reduced our dependence on Google and Meta by 40% while increasing customer lifetime value by 30%. Our retention rate has grown from 27% to 42%, driving an incremental $4.2 million in annual recurring revenue. This isn’t just better marketing—it’s a fundamental improvement in our business economics.”

This transformation in language—from campaign metrics to business outcomes—elevates the marketing function from creative service to strategic business driver. When marketing discussions focus on profit contribution rather than creative awards, the CMO naturally transitions from a tactical operator to a strategic business leader.

The Progency-powered CMO builds precisely the cross-functional perspective and financial acumen that boards seek in CEO candidates:

  • P&L ownership through measurable marketing contributions to profitability
  • Strategic vision through deep customer understanding and market foresight
  • Operational excellence through AI-orchestrated execution at scale
  • Growth expertise through balanced acquisition and retention strategies

These capabilities transform the perception of marketing leadership from creative direction to comprehensive business leadership—precisely the evolution needed for CMOs to be considered serious CEO candidates.

The Call to Action

The path to C-suite MVP status isn’t theoretical—it’s immediate and actionable through three concrete steps:

  1. Audit Your AdWaste: Calculate the percentage of your budget bleeding into reacquisition—then redirect it to Progency’s profit-generating solutions. This isn’t cost-cutting; it’s strategic reallocation from waste to growth.
  2. Pilot the “Department of One”: Deploy Neo360 on your “Rest” segment—those showing declining engagement in the past 30-90 days. Within 90 days, you’ll have a boardroom story of increased lifetime value that silences ROI sceptics.
  3. Rewrite Your Narrative: Transition from “We acquired X leads” to “We increased customer equity by Y%”—adopting the language CEOs and CFOs recognise and reward with greater influence and career advancement.

Progency isn’t merely a tool—it’s a leadership accelerant. In an era where CMOs last just 42 months on average, it offers the ultimate insurance: irreplaceable value through measurable profit contribution. The question isn’t whether you can afford Progency, but whether you can afford to let your competitors wield it first.

The Future is Now

The transformation from cost centre CMO to C-Suite MVP isn’t a distant possibility—it’s an immediate opportunity. The convergence of Agentic AI capabilities, emerging channels like AMP in email, and systematic approaches to eliminating AdWaste creates a perfect moment for marketing leaders to redefine their role and contribution.

The C-suite MVP isn’t born—they’re built. With Progency, CMOs gain the metrics, the mandate, and the AI muscle to claim their rightful seat at the strategy table. The age of marketing as a cost centre is over. The age of the profit-driving CMO has begun.

In the emerging world of NeoMarketing, the winning CMOs will be those who reject the old playbook of endless acquisition and embrace a retention-first, profit-focused future. They will lead with AI, measure what matters, and act like business owners—not just brand stewards.

The question is no longer whether marketing can drive profits. The question is—will you be the CMO who leads this revolution, or will you watch from the sidelines as others claim the C-Suite MVP mantle?

Thinks 1598

Tanay Jaipuria: “Alongside the surge in AI apps, there’s an exciting trend toward agentic technology. While agents are still early, and you’d be hard pressed to get three people to agree on a definition of them, its clear that founders across the infra and application layers are pushing beyond simple chatbots and copilots to ones that can complete entire workflows leveraging planning, memory, reasoning and tool use. Looking at the list, we see that enablers of agents such as Browserbase, CrewAI, LlamaIndex make up three of the five early-stage spots. Similarly, early poster examples of agentic applications such as Decagon also were high up on the list. I expect to continue to see more agentic companies in future lists, as we see the continued rise of the agentic workforce.”

Evan Armstrong: “When writing falls short, it’s often because the writer concentrated on the wrong level of craft for their desired audience. For example, carefully editing at the individual word or sentence level can create a smooth, waterslide-like flow where readers glide effortlessly from sentence to sentence, unable to stop themselves. Many writers mistakenly think achieving this effect means using elaborate language, complicated grammar, or ornate sentences. In reality, especially in online publishing, it typically means simplifying—shorter sentences, direct language. People behave differently on the internet than when they sit down to read a book. You need to work harder to hold their attention.”

Andrew Chen: “Your product actually has to be very good. I wish I lived in a world where you could have amazing marketing and growth strategies, have a shitty product, and you would win. Then marketers would run tech, and they do not. It’s the people visionaries that create the products that run tech, and that’s a good thing! The reason is that even if you do a ton of work to acquire a bunch of users, it won’t matter if they leak out of the DAU number. I’ve come to think of great marketing strategy as a multiplier effect on your inherent product quality. If you have a great product, you will multiply that into greatness. If you have a shitty product, you will multiply that into… well, you get it.”

Sangeet Paul Choudary: “When answers get cheap, good questions are the new scarcity.”

WSJ: “AI agent adoption is limited so far, according to Tom Coshow, a senior director analyst at researcher Gartner. Just 6% of 3,400 people in a recent Gartner webinar on the subject said their companies had deployed AI agents, according to Coshow. The survey isn’t a formal market analysis, Coshow cautioned. While the group potentially was predisposed to have an interest in AI agents, its responses may have actually been tempered by Gartner’s guidance that many so-called AI agents are mere assistants. During the webinar, Gartner shared its definition of agents as AI that makes a decision and takes an action.”

Progency’s Problem-Solving Prowess (Part 7)

Pitches – 3

DeepSeek

Pitch Conversation: Andy (Progency) and Maya (B2C CMO)

Andy: Maya, thanks for taking the time. I know your team is juggling a dozen priorities, so I’ll cut to the chase. Progency exists to solve one problem: the $5 million AdWaste crisis draining your marketing budget. We’ve helped brands like yours turn marketing from a cost center into a profit engine by focusing on retention, not just acquisition. Can I share how?

Maya: Retention’s important, Andy, but we already invest in loyalty programs and email marketing. How is this different?

Andy: Fair question. Traditional loyalty programs and email campaigns still leak value because they treat customers as segments, not individuals. Let me ask: Are you paying Google and Meta to retarget customers who already know your brand?

Maya: Of course—it’s unavoidable. If customers go dormant, we have to reacquire them.

Andy: That’s the $5 million problem. Brands waste 70% of budgets reaching people they already own. Progency stops that cycle. Our NeoN solution replaces platform retargeting with authenticated email networks. Instead of paying Meta’s auction tax, you reach dormant customers through non-competing brands’ engaged audiences. We’ve cut reacquisition costs by 30-50% for clients.

Maya: Interesting, but we’ve built a martech stack over years. Adding another tool sounds messy.

Andy: Progency isn’t another tool—it’s a performance partner. We plug into your stack with our PEAK framework: Platform tech, Experts, AI agents, and Kaizen optimization. For example, NeoMails transforms your emails into interactive hotlines. AMP-powered experiences drive 4-10X higher engagement by embedding rewards, micro-experiences, and zero-party data collection in the inbox. No more “click-through penalty.”

Maya: AI’s a buzzword. How does this actually work without requiring my team to become data scientists?

Andy: Totally valid. Our Department of One model uses AI agents to handle personalization, segmentation, and journey orchestration. Your team stays in control of strategy, while our AI executes N=1 campaigns at scale. For your “Rest” customers—those slipping into disengagement—Neo360 predicts their next best action and delivers hyper-personalized experiences across all channels. No hiring spree required.

Maya: Sounds idealistic. How do you prove ROI?

Andy: We’re 100% performance-aligned. Our fees are tied to revenue uplift from increased CLTV, not hours or CPMs. For example, a beauty brand using Neo360 saw a 22% lift in repeat purchase rates within 90 days by personalizing cross-channel journeys. Another client reduced reacquisition spend by 45% with NeoN. We commit to beating your current benchmarks—or you walk away.

Maya: What about new customer acquisition? We can’t ignore growth.

Andy: Absolutely. Our BRTN framework includes “Next” customers. NeoN uses authenticated identity targeting for new prospects, cutting acquisition costs by 30% versus cookie-based ads. But the bigger win? Turning your “Best” customers into advocates. With Velvet Rope Marketing, we help you monetize their loyalty through referral programs and even revenue-sharing via NeoN’s publisher network.

Maya: I’m intrigued, but my CFO will ask about upfront costs.

Andy: Zero upfront investment. We scale with you—our revenue-sharing model means we only win if you do. Imagine redirecting even 20% of your AdWaste budget into owned-channel retention. That’s $1 million back on a $5 million ad spend, plus the upside of deeper customer relationships.

Maya: Let’s pilot this. Where do we start?

Andy: We’ll run a 90-day sprint on your “Rest” segment—activate NeoMails and Neo360. You’ll see engagement spikes and CLTV lifts within 30 days. If we don’t beat your current metrics, you owe nothing. Deal?

Maya: Deal. Let’s save that $5 million.

Closing Note: Progency isn’t about chasing shiny objects—it’s about rewiring marketing economics. Ready to turn your dormant customers into profit? Let’s talk.

(Pitch ends with a clear next step: scheduling the 90-day pilot and aligning on KPIs.)

Thinks 1597

SaaStr: “Every single app should have some sort of ChatGPT-like interface, some sort of co-pilot…This is how users want to interact – they don’t want to input data manually, hit refresh, or figure out complex UX anymore.  And if nothing else, they will soon expect you at least offer an AI of the level of quality of ours or better.”

Andrej Karpathy: “It strikes me as quite unique and remarkable that LLMs display a dramatic reversal of this pattern – they generate disproportionate benefit for regular people, while their impact is a lot more muted and lagging in corporations and governments. ChatGPT is the fastest growing consumer application in history, with 400 million weekly active users who use it for writing, coding, translation, tutoring, summarization, deep research, brainstorming, etc. This isn’t a minor upgrade to what existed before, it is a major multiplier to an individual’s power level across a broad range of capabilities. And the barrier to use is incredibly low – the models are cheap (free, even), fast, available to anyone on demand behind a url (or even local machine), and they speak anyone’s native language, including tone, slang or emoji. This is insane. As far as I can tell, the average person has never experienced a technological unlock this dramatic, this fast.”

NYTimes: “Recent data from China’s central bank shows that state-controlled banks lent an extra $1.9 trillion to industrial borrowers over the past four years. On the fringes of cities all over China, new factories are being built day and night, and existing factories are being upgraded with robots and automation. China’s investments and advances in manufacturing are producing a wave of exports that threatens to cause factory closings and layoffs not just in the United States but also around the globe. “The tsunami is coming for everyone,” said Katherine Tai.”

Christopher Penn: “n8n is workflow automation software. You and I use it to automate tasks, from the mundane to the exotic. If you’ve ever played games where you have to connect different nodes together (like that one game where you have to connect pipes to get water flowing), or build modular structures (like in SimCity/SimTower), n8n is a natural evolution of that kind of automation. What makes it different and useful in many ways is that n8n has both no-code and high-code options. Hardcore coders can use it and write in its native language (JSON) to quickly develop very elaborate workflows and automations, as well as write their own modules and nodes for it, making it infinitely extensible. Non-technical people can use its interface and pre-made connectors and blocks (called nodes) to piece together workflows.”

Larry Tisch: ““The most important thing is to stay focused on what matters. Most little things ultimately have no effect on an enterprise. It’s the big deals – and the big decisions that do. Don’t spend too much time on little things. The important choices and opportunities are the ones that move the dial.” [via Shane Parrish]