Thinks 2033

Paul Graham: “One of the biggest advantages of AI will be that it lets companies get further before they cross the lines (at about 10 and about 150 people) beyond which groups become less productive.” [via Arnold Kling] More from Arnold: “Experienced software developers are used to working in teams. They have gotten accustomed to relying on Cursor. But at some point, we will see the emergence of software developers who are used to working alone. Cursor appeals to software engineers who are used to working without AI and who want to be able to see the code. My prediction is that in a few years the best software engineers will trust the best coding AI’s Instead of Cursor, what will ultimately emerge are tools that optimize for communication between a lone developer and AI.”

FT: “Uniqlo releases only 800 new designs per year, and only about half of those are changed in its six-monthly renewal cycles. By contrast Zara, a fast-fashion pioneer, churns out thousands of designs every year, with new iterations arriving every fortnight. At Shein, thousands are released each day. Smaller ranges mean Uniqlo might end up selling a million units of a single T-shirt design versus, say, less than 100,000 at fast-fashion houses, generating scale and cost advantages when it comes to raw materials, sewing and dyeing. The resulting high-quality products at reasonable prices were a winning model in the deflationary market of post-bubble Japan. Some analysts believe its lower gross profit margin relative to Inditex indicated how Uniqlo passed the price and quality benefit on to its cost-conscious consumers.”

NYTimes: “[A study] suggests that the most dangerous times for investors are when the market is high — and we may be in such a time right now. The study, by Hendrik Bessembinder, a finance professor at Arizona State University, shows that most of the biggest losers since 1926 were tech companies. They included stocks that boomed during the dot-com era and in the halcyon days just before the financial crisis that began in 2007 — and many crashed when those boom cycles ended.”

WSJ: “Unlike in previous tech cycles, corporate adoption of AI rests on all employees—not just developers—picking up on the technology. AI is increasingly being billed by usage, and the price of tokens, the basic unit of AI computing, has been volatile. That all translates to higher costs for AI.”

The Pitch That Finished the Argument: A Progency Conversation

CAST

Arjun — NeoMarketing sales lead, Netcore. Same audit discipline as the first meeting. Three months on, he’s back with a different kind of page.

Maya — CMO of the same D2C fashion brand. The 90-day NeoMails test closed out. She isn’t asking whether the doctrine is real any more — she’s asking who is accountable for running it.

Setting: Maya’s office, three months after the pilot closed. Her REACQ% has moved. Her Real Reach has moved. This time, she requested the meeting.

Before the Meeting

Maya’s Monday starts the way it always has: a dashboard that looks busy enough to be reassuring. Campaigns shipped on schedule. Journeys are running. The agency sent its weekly update. Underneath the campaign layer, though, she’s started looking at a different number — 31,000 stalled KYC upgrades from the last quarter, sitting in a queue nobody owns. The dashboard didn’t lie about what went out. It just never measured what got finished. That’s the number she wants to talk about today, not the pilot recap.

1

The Handoff Problem

“So Now You’re Selling Me a Third Thing?”

Maya’s mental shift: proof of concept isn’t the same question as who runs it at scale.

Arjun sits. No printed page this time — he opens with a question instead.

Arjun:  Before I show you anything, tell me what broke when you tried to run the next stage yourselves.

Maya doesn’t hesitate. She’s been waiting to say this.

Maya:  Nothing broke. It just didn’t scale. My team ran the 100,000-ID test beautifully because it was 100,000 IDs and it had my best analyst on it for ninety days. My Rest base is 2.8 million. I don’t have four more of her. And it’s not just Rest — I pulled the KYC queue last week. Thirty-one thousand upgrades stalled, some for months. Nobody owns that number. It just sits there.

Arjun:  That’s not a people problem. It’s a bandwidth ceiling every in-house team hits at the same point — segment refresh, message variants, journey branches. It’s structural, not a reflection on your team.

Maya:  Fine. So who runs it? Because if the answer is a new vendor, I want to say now — I already have Netcore for the platform, I already have you for Atrium and Meridian. I am not adding a fourth relationship to manage a problem you told me was one system.

Arjun places a single card on the table — no deck, one page.

Arjun:  It isn’t a fourth relationship. It’s the delivery arm of the two you already have.

Maya:  Walk me through it. Slowly.

Arjun:  Meridian is the underwriting logic for your Best customers — Beta plus Alpha plus Carry, the outcome contract. Atrium is the same logic for Rest and Next. Neither of those is a team that shows up and does the work every day. Progency is that team — Martech Growth Engineers, running the actual interventions inside Meridian’s rules for your Best customers, and inside Atrium’s rules for your Rest base. One name. One accountable team. It doesn’t sit beside Meridian and Atrium — it’s how they get delivered.

Maya:  So when my Best customer’s renewal quote goes stale, that’s Progency working inside Meridian’s rules. And when a dormant subscriber needs winning back before I pay Meta for her again, that’s Progency inside Atrium’s rules. And my stalled KYC pool — those are engaged customers mid-upgrade, not dormant — so that’s Meridian’s side too.

Arjun:  Exactly right. We call the first two Finish and the second Recover. Different customers, different job, same team, same accountability line back to you.

Maya reads the card again. She just leaves it face up on the desk, which Arjun has learned to read as a good sign.

Maya:  There’s a political question underneath this too, and I want to ask it directly. My in-house team is going to hear ‘Progency’ and assume you’re taking over their job. How do I tell them that’s not what’s happening?

Arjun:  You tell them the truth, and it holds up: Progency doesn’t touch BAU. It only works declared leakage pools — named groups where your own team has already agreed the journey has stalled, the outcome is measurable, and there’s a clear baseline to beat. Your team keeps everything else: brand, strategy, the customers CRM already serves well. We’re not asking for their job. We’re asking for the pools they’ve already told you they can’t get to.

Maya:  That I can sell internally. Alright. I believe the structure. I don’t yet believe the economics. Let’s get into that.

Key Takeaway: Maya’s objection was never about whether the doctrine works. It was about vendor sprawl and internal politics. The answer that lands isn’t a better pitch — it’s proof that nothing new is being added to her stack, and nothing is being taken from her team.

2

Under Fire

“My Retargeting Already Does That. Why Do I Need You?”

Maya’s mental shift: from structural sign-off to pricing sign-off.

Maya pulls up her own dashboard — turning her screen so Arjun can see it.

Maya:  Here’s my abandoned-cart flow. Dynamic ads, product-level, running right now on Meta. You’re going to tell me Progency does this better, and I want to know exactly why, because on paper this already looks like one-to-one targeting to me.

Arjun:  It is one-to-one targeting. I’m not going to tell you adtech can’t do this — that claim doesn’t survive five minutes with your own dashboard open. What I’ll say instead: Meta is matching a device to a product probabilistically and charging you a CPM to show it again. We already know deterministically who this customer is, we know exactly which size and colour she left in the cart, the follow-up costs us next to nothing to send, and because it runs against a holdout you agree to upfront, you get a clean number for what it actually recovered — not an attribution model’s estimate.

Maya:  So the pitch isn’t ‘adtech can’t.’ It’s ‘we’re cheaper, more precise, and provable.’ Which also means cart probably isn’t where I should start — you’ve just told me my own baseline there is already decent.

Arjun:  That’s exactly right, and most brands miss it. Cart is the most-solved leak in the business, which makes it the worst place to prove Alpha — the gap between us and your current effort is narrowest exactly there. Your KYC pool is a better first test. Nobody’s retargeting a half-finished KYC form.

Maya sits back. This is the point in the last meeting where the conversation turned to money. She gets there faster this time.

Maya:  My finance team already killed one version of this. Someone on your side proposed a flat fee per email open on the dormant base. My head of ops called it ‘charging us to annoy our own customers.’ It was a hard no, and I don’t want to relitigate it.

Arjun:  You’re right to have killed it. That proposal was a mistake — an open is an impression, not an outcome. Charging for it is the exact thing Never Pay Fixed exists to stop, and I’d have told your ops team the same thing if I’d been in that room.

Maya:  Then what do I actually pay for?

Arjun:  A ladder, with names your finance team can actually look up. You never pay for an open. Pay-for-Action starts weak — a click, a reply — and climbs to strong: a completed KYC step, a qualified lead, a quote requested. Pay-for-Data sits alongside it — we hand back a qualified field your CRM was missing, like a renewal date, and it’s priced by usable fields, not raw data points. Pay-in-Email sits at the top, on the Beta-Alpha-Carry structure, whenever you’re ready for it.

Maya:  And if I never move past Pay-for-Action?

Arjun:  Then that’s what this pool is worth to you, and we don’t force the issue. But most brands climb the ladder once the first rung proves out — because the number that convinces a CFO is never the pitch, it’s the first quarter’s actual holdout comparison.

Maya:  One more thing before we move on. If I run both Finish and Recover, which one do I actually get first? I don’t have budget or attention for both to start simultaneously.

Arjun:  Finish, honestly. It’s not the bigger story — Recover, reactivating someone before Meta re-buys her, is the sentence that gets vendors like me in the door. But Finish has shorter cycles. A stalled KYC step resolves in weeks. Recover on a genuinely dormant customer takes longer to prove and longer to fund, since we’re not paid until the outcome lands. Start with Finish, let it pay for itself faster, and run Recover alongside it once the first cheque clears.

Maya writes one word on her notepad: sequencing. Underlines it once.

Key Takeaway: Maya’s finance team had already correctly rejected a flawed pricing model. Arjun’s job wasn’t to defend it — it was to agree it was wrong and show what replaced it. Conceding a bad idea landed harder than defending a good one would have.

3

The Close

“What’s Actually Yours, and What’s Everyone Else’s Too?”

Maya’s mental shift: from pricing sign-off to a test she can defend upward.

Maya leans forward — the question she always asks, arriving a little earlier than usual this time.

Maya:  Here’s what worries me longer term. The tooling you’ve described — tracking, templates, the AMP layer — none of that sounds hard for a competitor to copy in a year. What actually stops me from switching to whoever undercuts you next?

Arjun:  Nothing stops you, on the tooling. You’re right that any competent vendor can build similar utilities eventually. What they can’t copy is the record underneath it — every action Progency has run, on every type of stuck customer, across every brand we’ve touched, and what it actually produced. We call it the Decision Trace Graph. It’s inside our Context Graphs, and every intervention writes back to it. A year from now, the tenth brand we do this for benefits from what we learned on the first nine. A new entrant starts at zero.

Maya:  So the tools get me started. The trace record is what compounds.

Arjun:  That’s the honest version, yes.

Maya nods slowly — the same motion Arjun remembers from the end of the first meeting.

Maya:  Fifteen years in this industry. Every eighteen months someone tells me the delivery model has changed and this time it’s structural. Convince me this isn’t that, one more time, quickly.

Arjun:  I won’t try to convince you in the abstract. Give me one pool — not your whole Rest base, not a transformation programme. One declared leakage pool, a fixed window, a holdout your own team agrees to upfront. If it doesn’t beat the holdout, you’ve lost two months on customers who were already stuck. If it does, we’ve proven the delivery model on your own data, not a case study from someone else’s brand.

He places the second card of the meeting on the table.

Maya:  Stalled KYC upgrades. That’s the pool I already told you about — thirty-one thousand of them, and I know it’s been ignored for two quarters.

Arjun:  Then that’s the pool.

Maya:  Sixty days. No platform change, no new budget line, Pay-for-Action so my finance team doesn’t reopen the objection from last time. And I want the review to be more specific than ‘did it work.’

Arjun:  What does the review look like on your side?

 

Maya:  Five questions, not a deck. How many customers actually moved. What they actually did. What usable data we captured along the way. What revenue it produced, if any. And what happened next to the holdout. If you can’t answer those five cleanly at day sixty, I don’t care how good the pitch was.

Arjun:  Agreed — those are the right five, and they’re the same ones we’d hold ourselves to internally. One thing — do you want this framed as a Progency engagement in the write-up, or folded into the Meridian relationship you already have signed off?

Maya:  Fold it in. My board already approved Meridian. I’d rather this look like Meridian doing its job properly than a new line item.

Arjun:  Noted. It runs under Meridian.

Key Takeaway: Maya didn’t ask for a bigger commitment — she asked for the smallest one that would still tell her the truth, and she named her own success criteria rather than accepting Arjun’s. That’s the same shape as her first close, and it’s the shape Progency is built to survive: no transformation required, just a fair test on one real pool, judged on the buyer’s terms.

After the Meeting

Arjun leaves the cards on the table this time — Maya asked him to. She pulls up the KYC pool herself before her next meeting starts: names, stalled dates, how long each one has sat untouched. She’s seen this data before. She has just never looked at it as something with a price on either side of the ledger — what it’s costing her to ignore, and what it would cost to finally close. She forwards the pool definition to her ops lead with one line: “Sixty days. Five questions. Let’s find out.”

Thinks 2032

[Via Arnold Kling]: “The revolutions are led by the educated-but-blocked: young people with enough knowledge to understand the system and enough frustration to want to tear it down.”

FT: “The wisdom of crowds has never lain in the consensus. It lies in the disagreement. Once everyone thinks alike, crowds are error-prone. ”

NYTimes: “Bending Spoons is not the only firm chasing tech’s castoffs. Constellation Software, a Canadian company with $11.6 billion in annual revenue, specializes in buying business-oriented software and technology companies. A Los Angeles company called MediaLab, run by Michael Heyward, the founder of the anonymous social media app Whisper, has bought the assets of Imgur, the image-sharing site; Kik, the messaging app; and Genius, the music lyrics site. Since it was founded in 2013, Bending Spoons has purchased more than 50 companies. Last year it generated $1.3 billion in revenue.”

Ethan Mollick: “Being on an exponential means each change over a fixed window is larger than the one before it. If your organization wrote an AI plan any time before the winter of 2025, it described a system that could do a couple of hours of work with a fairly high error rate. A few months later, you can get sixteen hours or more of work from a single prompt. This is why AI keeps feeling like it is making leaps, even though it is a curve on a graph, we keep experiencing a steady doubling of capability as a series of shocks. We are very bad at feeling exponentials from the inside, and we are currently inside one.”

The Space Between: How Progency closes the gap between CRM and Adtech

1

The Gap No One Gets Paid to Close

A cart gets abandoned. A KYC form is left half-filled. A lead goes quiet after showing real interest. In most companies, the same thing happens next: CRM tries a few times, then stops. Weeks later, the same customer starts turning up in retargeting ads — the brand paying a platform to remind someone of a relationship it already owns.

This is the pattern behind NeoMarketing’s central complaint: brands routinely pay twice for the same customer — once to acquire them, again to remind them they exist. NeoMarketing’s Three NEVERs name the fix directly: Never Lose Customers, Never Pay Twice, Never Pay Fixed.

Turning that into a working system starts with a segmentation few brands do explicitly — BRTN: Best, Rest, Test, Next. Best customers — typically the top fifth, engaged within the last month — already deliver outsized value; the job is protecting and growing it. Rest customers have gone quiet over the past one to three months — not lost, just drifting; the job is stopping the drift before it hardens. Test customers have been silent for ninety days or more — the dormant base every brand carries and few will name; the job is reclaiming them on owned channels before adtech sells them back. Next customers haven’t been acquired at all yet. Most brands serve only Best and Next — they reward loyalty and celebrate acquisition — while the middle two segments, where sixty to seventy per cent of the base usually sits, are exactly where the leak lives. (Operationally, Test sits within Rest: two stations on the same slide from attention to silence.)

NeoCore is the engine built to run this structure. Meridian serves Best customers, underwriting outcomes to maximise lifetime value. Atrium serves Rest and Next, running an attention marketplace built to push the cost of reactivation and acquisition toward zero.

Why the relationship goes quiet in the first place

It helps to be precise about why CRM’s messages stop working, rather than treating drift as an unavoidable fact of life. Email has four jobs — SNDR: Sell, Notify, Digest, Relate. Sell is the commercial ask: an offer, a promotion, a conversion nudge. Notify is the service layer: an order confirmation, a shipping update. Digest curates the customer’s world — markets, destinations, ingredients, whatever the category knows well — with the brand as editor rather than subject. Relate builds the relationship itself: recognition, rituals, content that asks for nothing. Most brands send only the first two — and both are withdrawals from the customer’s attention, because every one either asks for something or merely reports a transaction. Digest and Relate — the two deposits — are the emails most brands have never sent. That explains something CRM dashboards usually hide: a customer can be technically “reachable” and still be drifting, because nothing in the inbox has given them a reason to keep opening. BRTN tells you where a customer has drifted to. SNDR tells you why.

What it costs to look the other way

The alternative to closing this gap isn’t free. At a typical 4-5x return on ad spend, a brand hands back roughly 20-25% of the revenue generated on that campaign, in fees, to the platform that delivered it. For a genuinely new customer, that’s simply the cost of acquisition. For a customer the brand has met before — whose email is sitting quietly in the CRM, unresponsive but not deleted — that 20-25% is money paid a second time for something already owned.

Between how CRM behaves and how Meridian and Atrium operate sits a gap most martech stacks quietly ignore. CRM’s automation gives up on a customer after a fixed number of retries — that’s how campaign tools are built. Adtech has the opposite economics: it takes over exactly when CRM stops trying, and starts charging the brand a media fee to reach the same person again. In between — after CRM has stalled, before the brand pays adtech to re-acquire — sits a stretch of unfinished value that neither system is actually built to close.

Call it the post-CRM, pre-Adtech gap. It’s also pre-call-centre, pre-agency, and pre-manual-escalation in a great many cases — any point where the brand still owns the identity, the history and the context, but has no accountable operator for what’s left unfinished. Nobody in the standard stack is accountable for it, priced for it, or even measuring it, because it falls between systems, each designed to hand it off rather than close it.

This is the specific space Progency exists to close. Progency is NeoCore’s managed-service layer, run by Martech Growth Engineers (MGEs) working with M-Agents — the agent collective that does the machine-scale work of cohort discovery, message variants, and journey decisioning, while the MGEs supply judgement, governance, and the accountability line back to the brand. The pairing matters: without the agents, a managed-service team is simply the client’s own CRM team outsourced — same bandwidth ceiling, same economics, same give-up point. With them, a small number of MGEs can run outcome-based interventions across pools no in-house team has the capacity to touch — exactly the customers CRM has stopped trying and adtech hasn’t yet re-bought. It isn’t a new platform and it isn’t a new segment. It’s a dedicated operating function sitting precisely in the space the rest of the stack leaves empty.

Naming the gap explicitly turns an invisible leak into something measurable, sellable, and priceable. Once you can point to this customer, this unfinished journey, this exact moment CRM gave up, you can ask a sharper question than “how do we get more customers?” You can ask: how much of the value we already have is leaking through this gap right now, and what would it cost to close it?

The answer differs depending on who the customer is. A customer who has gone quiet entirely is a different problem from one who was actively transacting right up until the journey broke. Progency treats them as two distinct books of business, priced against two different alternatives — which is where the next part picks up.

2

Two Books, Two Alternatives

Not every customer who falls into the post-CRM, pre-Adtech gap got there the same way, and treating them as one undifferentiated pool is the fastest route to underpricing the harder cases and overpaying for the easy ones. Progency splits the gap into two books.

Finish is for the engaged-but-stuck base — customers mid-journey when things broke: an abandoned cart, an incomplete KYC form, a lead that cooled after real interest, a quote never followed up. These customers haven’t drifted away; a specific transaction simply never completed. Here the alternative isn’t adtech at all — it’s whatever the brand’s own fallback happens to be: a call-centre follow-up, an agency retainer, a manual outreach queue, or in a lot of cases, nothing.

Recover is for the non-engaged base — lapsed buyers, dormant subscribers, one-time purchasers who never returned. For this book, the alternative the brand is weighing is almost always Adtech: pay a platform to put this same customer back in view via a paid ad. Recover’s job is to win the customer back on owned channels first, at a fraction of that cost, before the brand ever reaches for its ad budget. It’s priced against what paid reacquisition would have cost — a return equivalent to roughly 6x has proven realistic, or roughly half of what an equivalent paid campaign would run.

That distinction corrects a claim that’s tempting to make and doesn’t survive scrutiny: that these plays “never go to adtech, because adtech can only target cohorts.” That isn’t accurate. Dynamic retargeting — the kind that shows someone an ad for the exact product left in their cart — already does precise, one-to-one targeting. Adtech is entirely capable of chasing an abandoned cart.

The honest differentiator isn’t that adtech can’t do this. It’s that owned channels do it better, on four counts. Identity: Progency already knows exactly who this customer is, deterministically, with no probabilistic ad-matching involved. Context: it knows precisely what was left unfinished — which product, which form field, which step — not just a broad interest signal. Cost: another message to a known customer costs a fraction of a paid impression. Proof: because the intervention runs on owned channels against a proper holdout group, the lift is measured cleanly, rather than inferred through an ad platform’s own attribution model.

The declared leakage pool

Neither book starts with Progency simply being handed a customer list. It starts with a declared leakage pool — a specific, named group of customers where the brand, the in-house CRM team, and Progency agree on three things upfront: the current journey has genuinely stalled, the desired outcome is measurable, and the comparison baseline (what the brand’s own current best effort achieves) is clear. Incomplete KYC applications from the last quarter. Leads that went cold after a product demo. A suppressed email segment nobody has touched in six months. Each is a pool with a name, a size, and an agreed definition of success — not a vague mandate to “help with retention.”

That boundary does two jobs at once. First, it protects the in-house marketing team politically: Progency isn’t taking over BAU CRM, brand, or strategy — it’s working the specific pools the team has already agreed are stuck, dormant, or too costly to chase through existing methods. Second, it protects Progency from becoming generic services. Without the declared-pool discipline, any outcome-shaped request could get pitched as “Progency,” which dilutes the model into something that looks like an agency retainer with extra steps. A declared pool, an agreed baseline, and a measurable outcome are what keep this a specific, underwritten service rather than marketing-as-a-vague-favour.

Put simply: adtech can chase these moments. Progency finishes them — faster, cheaper, and with cleaner proof of what actually worked.

The practical upshot for a CMO is that Finish and Recover aren’t two versions of the same pitch dressed up differently — they solve different problems, against different competitors, on different customer states. Most brands run both problems simultaneously: a live stream of engaged customers falling out of half-finished journeys every day, and a Rest segment slowly decaying toward being repurchased by adtech.

Because the alternative each book displaces is different, the price for each has to be different too — and that’s where an earlier temptation, pricing everything the same way, runs into a problem the next part addresses directly.

3

Paying for Progress, Not Attention

One of the Three NEVERs is Never Pay Fixed — the idea that brands shouldn’t pay a platform for exposure regardless of whether it produced anything. It’s the core complaint against adtech’s CPM model: pay for the impression, hope for the result.

It would be easy for Progency to quietly reintroduce the same problem from the other side — charging a flat fee per email opened, regardless of what happens next. An open is a rendering event. It tells you the message reached an inbox and someone glanced at it. It doesn’t tell you whether the customer moved a step closer to finishing the KYC form, replying to the follow-up, or returning to the cart. Billing for it anyway would be paying for attention, not outcome — the exact pattern NeoMarketing exists to end, wearing a different logo. It would also make the pricing indistinguishable from a CPM by another name.

So opens stay where they belong: on the diagnostic dashboards NeoMarketing already runs to track attention health (Click Retention Rate, Real Reach, and the rest of the NEVER Metrics) — not on the invoice. What Progency prices instead is a ladder of named, verified commercial units, each closer to revenue than the last.

Pay-for-Action covers two of the rungs. At its weakest, that’s a click, an in-message tap, or a reply — a real, verified action, but not yet meaningful progress. At its strongest, it’s a completed form step, a qualified lead, or a quote requested — the customer visibly moving through the exact journey that had stalled. Pay-for-Data sits alongside it: a preference answered, a renewal date confirmed, a missing KYC field filled in — first-party information the brand didn’t have before, written back into the Customer Context Graph, priced by qualified usable fields rather than raw data points. At the top of the ladder, Pay-in-Email prices a transaction completed inside the message itself, and Carry pays a share of verified uplift on larger pools with a clean holdout.

Why the ladder needs more than one rung

Pay-in-Email is the cleanest outcome — money moves, the result is visible — but it can’t be the only rung, because plenty of brands hesitate to commit to it on day one. The hesitation is rarely about the economics; it’s operational. Finance wants to know who owns the payment flow. Legal wants sign-off on a new transaction path. Whoever runs the dormant base doesn’t want the first message a lapsed customer receives in months to ask for money — that reads as pushing them further away, not winning them back. None of that is irrational, and Progency shouldn’t need a brand to clear every internal hurdle before a pilot can start.

That’s the entire argument for the ladder existing: a brand that isn’t ready for Pay-in-Email can start on Pay-for-Action or Pay-for-Data, see the mechanism work on a small, safe slice of its Rest base or a single stuck-lead pool, and climb toward Revenue and Carry once trust is established. Underneath all four tiers sits the same contract logic NeoCore uses for Meridian’s Best-customer outcomes: a small baseline payment (Beta), an upside tied to verified lift above what the brand’s own current effort would have achieved (Alpha), and a payout on that lift (Carry) — always measured against a randomised, concurrent holdout, never against doing nothing at all. That comparison to the brand’s actual current best effort, not to silence, is what makes the lift figure defensible in front of a CFO rather than a marketing team’s own optimistic assumption.

What doesn’t change is the underlying discipline: every tier is still an outcome, verified against a holdout, never a payment for reach alone. The ladder makes the model easier to start. It doesn’t make it easier to cheat.

That leaves the practical question of where to start climbing — which pool to run first, and why the obvious answer usually isn’t the right one.

4

The Operating Layer

Progency shouldn’t begin by building a new customer engagement platform. Netcore already has the rails — email, CE, CPaaS, WhatsApp, RCS, CDP integrations, Unbxd. The right move is an intelligence and operating layer above what already exists, not a rebuilt stack underneath it. Every new idea is tempted to become a new platform; Progency has to resist that temptation deliberately, because the first version isn’t software sold to the brand — it’s an accountable operating system, run by people, that gets more automated as it proves itself.

The declared leakage pool is where every engagement starts — named, sized, with an agreed stall point and a known current best effort to measure against. From there, the action surface follows a simple discipline: email as the low-cost owned room for attention, data capture, and completing the outcome in place, with WhatsApp, RCS, and SMS held back as escalation rails for the moments that genuinely need immediacy — an urgent KYC deadline, a lead about to go cold for good. The rule is channel-fit, not channel-loyalty: use the cheapest owned or cooperative surface that can actually finish the job.

Underneath that sits the utility layer — the Living Email Factory, AMP components, Pay-in-Email infrastructure, tracking middleware, and the Attention Processing Unit (Magnets, Mu, ActionAds, and the Ledger that records it all). These tools are necessary. They are not, on their own, defensible, because a competent competitor can build broadly similar tooling given enough time and budget.

M-Agents and Martech Growth Engineers run the pool day to day. M-Agents handle the repeatable work — cohort discovery, message variants, channel selection, response scoring, test monitoring. MGEs make the judgement calls: what a specific customer’s context actually means, when to escalate a channel, how to read an ambiguous response, how to keep the brand’s tone and consent rules intact. Automation follows this pattern, rather than preceding it — the point isn’t to declare an all-automated system on day one, but to automate the runbook one proven outcome at a time: finish KYC, then finish leads, then finish renewals; recover dormant buyers, then recover old leads.

The Decision Trace Graph is what all of this writes back to — customer state, pool, context, channel, message, offer, holdout status, cost, response, outcome, and the customer’s next state, every time. This is the actual compounding asset, sitting inside NeoCore’s wider Context Graphs alongside the Customer CG and Product CG. Integrating many tools is the cost of building Progency. The corpus of verified decisions and outcomes is the moat — the record that makes the tenth brand’s first pilot smarter than the first brand’s tenth pilot, because every trace sharpens what the system already knows about which action moves which kind of stuck customer.

Choosing the first pool

A serious brand almost always already has an abandoned-cart flow, and often dynamic retargeting alongside it — which makes cart recovery the most familiar leak, and, for that exact reason, usually the wrong one to lead with. The brand’s current best effort there is already strong, so the incremental lift a holdout can prove is thin. Alpha is widest wherever the brand’s current best effort is weakest, not wherever the leak happens to be most visible.

Incomplete KYC and stuck leads make better first pools precisely because they’re less discussed: the current alternative is often a call centre, a manual queue, or nothing at all, which gives a randomised holdout real room to show a difference. Renewals and form completion follow — clear events, clear value, clear counterfactuals. Dormant-base recovery comes after: strategically the larger prize, but it requires re-earning attention before anything resembling revenue is realistic, which makes it a slower pool to prove first.

None of this is about permanently ignoring cart recovery or dormant reactivation — both matter, and both eventually run. It’s about sequencing the first proof where the brand’s own current effort gives Progency the least competition, so the first holdout comparison is unambiguous rather than marginal.

5

Where Progency Lives

 It would be tempting to describe Progency as a third pillar of NeoCore, sitting beside Meridian and Atrium as an independent offering with its own sales motion. That would be the wrong way to think about it — worth saying plainly rather than leaving vague.

Progency isn’t a third engine. It’s the delivery arm of the two engines that already exist.

Finish operates inside Meridian’s domain. Meridian’s job is protecting and maximising the value of Best customers — and a Best customer whose renewal quote goes unanswered, or whose KYC step stalls mid-upgrade, is exactly the leak Meridian is built to prevent. Finish is how that protection gets delivered day to day: MGEs and M-Agents running the specific interventions that stop a valuable, engaged customer’s journey from quietly dying in a queue.

Recover operates inside Atrium’s domain. Atrium exists to push the cost of reactivation and acquisition toward zero for Rest and Next customers. Recover is Atrium’s operating layer for the specific customers who have gone dormant and are drifting toward being re-bought by a paid channel — the same mission as Atrium, delivered as a hands-on managed service rather than a self-serve marketplace mechanic.

One name, one delivery team, two engines it plugs into, two pricing ladders reflecting the two different alternatives each book displaces. That’s a materially different structure than treating Progency as a stand-alone product line — and it has a real consequence: Progency doesn’t need a sales pitch separate from Meridian and Atrium. It’s the answer to “how does this actually get done” for both.

There’s a sequencing question worth being direct about, because the honest answer isn’t the tidy one. Recover — reactivating a customer before a platform re-buys them — is the story that gets a sceptical CMO into the room in the first place. No adtech vendor will ever offer to make itself unnecessary; that’s a structurally unique pitch, and it should stay the headline.

But inside an actual engagement, Finish often ships first. Its cycles are shorter — a stalled KYC form can resolve in weeks, while winning back a genuinely dormant customer takes longer to prove and to fund, since outcome-only pricing means the cost of delivery is carried upfront and collected only once results land. Running Finish first improves how quickly a pilot pays for itself, while the longer Recover proof cycle plays out alongside it. The story that opens the door and the plan that ships first don’t have to be the same thing — and pretending otherwise is how good doctrine quietly drifts.

Put together, the pitch is simple enough to say in one breath: before a known customer is handed to a call centre, an agency, a manual queue, or an adtech platform, give Progency the first right to finish or recover the outcome. You pay only for verified results.

That’s the whole idea. Not a new department. Not a new promise. Just the place in the stack where NeoMarketing’s outcome discipline finally reaches the customers who had been falling through the middle all along.

Thinks 2031

NYTimes: ‘A slew of factors goes into investments and status in Silicon Valley. Lately, an intangible one has pulled ahead as a predictor of success or failure: “signal.” If your behaviors are deemed high-signal: Congratulations, you’re coming across as a winner and rewards may follow. If your actions are seen as anti-signal: Sorry, you’re radiating cringey energy that may hamper your chances.”

Anindya Chatterjee: “What are engineering jobs that AI cannot do? Jobs that require skill with both computers and hands, travel to jobsites, human presence, unexpected connections between ideas, and situations where data is unavailable or confidential. These, more than entrance-exam ranks and offer-withdrawing recruiters, need thinking about.”

Noah Smith: “Over the last two years, I’ve felt like my job has become a bit less important than it used to be, for three reasons: (1) The rise of populism on all sides of the political spectrum in the U.S. means that smart ideas are simply not as likely to be implemented by the people in power. (2) The general shift to Substack and other monetizable direct-to-audience channels has made punditry less conversational. (3) The rapid proliferation of AI writing has increased the demands on readers’ attention (including my own).”

WSJ: “The memory armageddon has arrived…Buyers of consumer electronics are getting hit. The primary driver is the skyrocketing cost of memory and storage chips, especially those known as DRAM and NAND flash memory, which are essential for transferring data and storing information on devices. These chips are the same ones craved by artificial-intelligence companies, which use them to help train and run large language models, coding agents and other tools. As AI adoption has exploded, the memory-chip industry—dominated by just three companies: South Korea’s SK Hynix and Samsung Electronics and Boise, Idaho-based Micron Technology—is suffering from a major capacity crunch.”

From SEND to EARN: The New Business Model for ESPs

1

The Trap: Why Sending Alone Cannot Save Email 

How email service providers escape commoditisation by moving from delivery revenue to actions, outcomes and inbox media.

Email did not lose relevance. The companies that sell it lost imagination. For twenty-five years, email service providers built businesses around a single verb — send — and were rewarded for doing it reliably, at scale, with deliverability, routing, templates and reporting. That was not a mistake; it was exactly what the market needed. But the thing you are paid for is the thing you optimise, and an industry paid by the send spent a quarter of a century perfecting delivery while the email itself barely changed. The result is a category that is now judged by the very logic it taught the market to apply. This essay is in three parts: the trap, the ladder, and the business of climbing it.

The old bargain, and the ceiling it built

The original bargain was sound. Brands had databases they could not operate at scale and a channel — the inbox — that was the cheapest owned ground they possessed. They needed lists cleaned, domains protected, campaigns scheduled, events tracked, bounces suppressed, complaints monitored and messages delivered without breaking reputation or compliance. The email service provider became the operating layer for that channel, and it earned its keep. Email became the workhorse of digital retention because it combined three advantages almost nothing else could match: a known identity, a near-zero marginal cost, and genuine ownership — a brand could reach its own customer without renting an audience from a platform.

The business model followed the job. ESPs were paid for contacts, sends, volume and platform access; the input became the invoice, and the invoice quietly shaped the product. But the category made one consequential error: it confused the channel’s value with the provider’s value. The brand owned the customer. The mailbox provider — Gmail, Apple Mail, Outlook — owned the client software. The ESP owned only the sending system in the narrow middle. That position built a durable business and, at the same time, a strategic ceiling: the vendor could move the message but not easily change what the message was, could optimise the sending but not own the moment of opening, could report engagement but never guarantee a profit.

So ESPs did what infrastructure companies do — they made the infrastructure better. Faster sending, better routing, better templates, better deliverability monitoring, better APIs, better dashboards. All useful, all necessary, and all increasingly comparable across vendors. The better an ESP became at delivery, the more invisible it became — and invisible infrastructure is eventually priced like infrastructure. The ceiling was not a failure of execution. It was built into the position the category chose to occupy.

 Five reasons the category under-imagined itself

 Email did not become a commodity because email failed. It became a commodity because the vendor model under-imagined what email could become — for five reasons at once, each of which now points at its own way out.

The first was pricing. Paid on sends, ESPs optimised the world around sending: more contacts, more journeys, more triggered messages. Rational, and beside the point. The deepest customer problem was never “can this be sent?” but “is this worth opening, and will it cause the next profitable action?” A business priced on sends will never build the email that makes sends matter less.

The second was surface ownership. An email renders inside someone else’s client, so the ESP never owned the canvas the way an ad platform owns its unit. Concluding — correctly — that they could not control the client, vendors wrongly concluded they could not change the artefact, and improved the machinery around the email while the email stood still.

The third was the all-or-nothing mistake on interactivity. When interactive email arrived, support across clients was uneven, so the industry treated it as a campaign trick rather than a design principle. The better conclusion was available and never drawn: interactivity is one rendering path, not the whole strategy; the real job is to compose the best possible experience at open, with graceful fallback everywhere else.

The fourth was measurement. When open-rate reliability broke, the industry lost a familiar instrument and read the darkness as decline, instead of rebuilding around stronger signals — clicks, actions, replies, sessions, declared intent, transaction movement. The channel still held attention; the dashboard simply could no longer see it.

The fifth was cost. A genuinely useful email is not a template with a name inserted; it is a fresh decision made for a specific reader at a specific moment — what is true now, what to show now, what action to allow now, what to remember afterwards. For most of email’s history, composing that at scale was simply too expensive. A brand could handcraft one clever campaign, not operate millions of living messages a day. Put the five together and the verdict “email is tired” was a misdiagnosis: the patient was fine, the thermometer was broken, the treatment had not been invented, and the people who could have invented it were paid to do something else.

The commodity spiral

The trap has a cruel mechanism: excellence at the old job accelerates commoditisation. Deliverability, scale, compliance, routing, security, support — all of it matters, and all of it becomes harder to monetise the moment the buyer believes several vendors clear an acceptable bar. Then the conversation moves from value to benchmark. Procurement enters. Vendor diversification becomes policy. The customer asks for lower unit cost, more volume, more resilience and less dependency — and every one of those requests is reasonable.

Figure 1 — A single-rung business, priced on the input, is squeezed on the input. The pipe must be run well; it cannot be asked to carry the future margin.

The danger is that this position is comfortable for a long time. Revenue continues, renewals continue, campaigns and support tickets continue — and the category quietly loses altitude. The vendor becomes operationally important while becoming strategically replaceable: a line item to be optimised rather than a partner to be expanded. A company that sells only delivery will eventually be priced by delivery. Defending the pipe harder does not arrest the spiral; it deepens it, because every incremental improvement to an invisible utility is, by definition, hard to charge for. The escape cannot be found on the rung where the trap was built.

Why “more interactivity” is not the escape

 The obvious response is to make email more interactive — more AMP, better templates, more widgets, forms and calculators. That is directionally right and strategically incomplete, because it confuses a capability with a business model. If interactivity is sold as one-time development, it stays a services line; if an embedded calculator is sold like a campaign asset, it stays a cost; if a living digest is sold as a template upgrade, it stays inside the old budget. The artefact becomes modern while the economics remain ancient.

The distinction is subtle and decisive. Interactivity as a feature says: pay us to build a better email. Interactivity as an action surface says: use the email to capture intent, complete actions, move customers and prove incremental value. The same artefact can sit in either model. A broker’s in-email application flow can be a paid development project, or an outcome instrument measured against a control. A retailer’s replenishment email can be a clever template, or a repeat-purchase engine. A publisher’s digest can be content, or monetisable inventory. The question is never what the email contains; it is what the vendor is paid for. Adding features to a per-send contract produces a more expensive pipe, not a new business — which is why a decade of “do more AMP” has not moved the category’s economics an inch.

Why now — three unlocks converge

If the diagnosis is twenty-five years old, why act now? Because three constraints that held the old model in place have broken at roughly the same moment, and their convergence is the opening the category has been waiting for.

Figure 2 — Three long-standing constraints break at once, and converge on a single opening: a living email, paid on what it proves.

The first unlock is artificial intelligence. The reason a living email was never operated at scale was cost: composing a fresh, relevant message per reader at the moment of opening could not be done economically. AI does not magically save email, but it changes what is cheap enough to attempt — the old email was written at send and guessed what would matter; the new email can be assembled at open and check what is true.

The second is the measurement reset. The collapse of the open rate, which once looked like a loss, is in fact the forcing function: with the old vanity metric gone, the only credible thing left to measure is action and lift against a control — exactly the basis an outcome business needs. The instrument that broke was the one keeping the category honest about the wrong thing.

The third is the rising cost of rented attention. As paid channels became more expensive and less certain, the economics of re-buying a customer you already own turned from wasteful to indefensible, and the owned inbox — identity-linked, low-cost, permissioned — became the obvious place to recover and retain rather than re-acquire. None of these three would be sufficient alone.

Together they make a living, accountable, owned-attention business not only possible but overdue. The conditions that made the old model rational have expired; the conditions that make the new one rational have arrived.

The surface is an asset

Step back and the reframe is simple. The surface was never the product. The surface is an asset. An owned email relationship has four properties that make it far too valuable to remain trapped inside per-send economics: it is identity-linked, it is low-cost, it is repeatable, and it sits in a place the customer returns to, reads, decides and acts. Unlike a paid impression it is not rented for a moment and gone; unlike a notification it can hold content, context, memory and choice; unlike a landing page it begins from a known relationship. Delivery is merely the first way to monetise that asset — and the category mistook the first way for the only way.

The next model for ESPs is therefore not another feature bundle but a migration from SEND to EARN. EARN stands for Email, Act, Run, Network. Email names the owned surface and the infrastructure that delivers it; Act makes that surface useful and interactive; Run takes responsibility for outcomes on it; Network turns trusted attention into media and cooperative acquisition. There is a deliberate symmetry with the framework brands already use. SNR — Sell, Notify, Relate — is the brand’s grammar for what an email should do. EARN is the vendor’s model for how the same surface gets paid. One describes the message; the other describes the business. They are two views of the same owned attention, seen from opposite sides of the table — and the only question that matters for Part 2 is this: if the future ESP is not paid primarily per send, then what is it paid for?

**

The old email business earned from volume. The next one earns from value — and the difference is not a feature, it is a business model.

2

The Ladder: How the Email Business Climbs

EARN is a business-model migration, not a product roadmap, and the distinction is the whole point. Product roadmaps list things to build; business-model migrations change the unit of value. Each rung of EARN changes the buyer, the competitor, the pricing logic and — the word that matters most — the accountability the vendor is willing to take. The same owned surface remains underneath the entire way up. What rises is what the vendor is trusted, and paid, to do.

Figure 3 — The EARN ladder. One owned surface, four ways to be paid; value and accountability rising with each rung. The climb is the strategy.

E  Email — the infrastructure rung

Email is the floor: sending, routing, deliverability, reporting, compliance, APIs, rendering, suppression, authentication, reputation and operational support. Every serious vendor must run it well, because if this layer fails nothing above it matters. The buyer is procurement or marketing operations; the competitor is another ESP, an internal sending system or a cheaper delivery vendor; the pricing is input-led — per send, committed volume, platform access.

The strategic instruction here is counterintuitive and easy to get wrong: make Send efficient, and do not expect it to carry the future margin. There is no honour in pretending that sending is not infrastructure; it is. But infrastructure is not unimportant — roads are infrastructure, and everything travels on them. The error is not treating Send as essential; the error is worshipping it. The point of the Email rung is not premium pricing forever. It is to hold the owned surface through which the higher-value models can emerge, because an ESP that loses the send relationship usually loses the surface, the signals, the habit and the right to propose anything above it. So the pipe must be defended and run beautifully — and then deliberately treated as the cash engine and the distribution layer, not the destination.

A  Act — the capability rung

 One floor up, the email stops being a message and becomes a surface on which the customer can do something. It becomes live, current and able to remember: a digest assembled at open, a calculator personalised to the reader, a preference fork, a survey, a product selector, a renewal option, a claim status, a booking flow, a consent request, an intent signal. The point is not that every email becomes an app — it is that the inbox can now contain actions, not merely links to actions.

The buyer changes entirely: this is a marketing, growth and product conversation, not a procurement one. So does the competitor — here the vendor is up against agencies, dev shops, campaign studios, AMP specialists and the inertia of doing nothing, never another ESP. And so the pricing must change with it: a capability fee, a managed-innovation programme, a zero-development-cost pilot with upside participation, or a hybrid — anything but a return to per-send. The value is not the number of emails delivered; it is that the email can now capture an action, signal or preference that previously demanded a click-out, a login or a separate app session.

But Act has one discipline of its own: it is the on-ramp, not the destination. Its job is adoption and proof, not full outcome risk from day one. A new interactive surface usually needs to demonstrate that people engage with it, return to it and trust it before it can carry a revenue guarantee. A vendor that treats Act as the summit will over-invest in a thin-margin tier and call it transformation; a vendor that treats it as the path will use it to generate the evidence the next rung is priced on. Act helps the brand do more. Run takes responsibility for the result.

R  Run — the outcome rung

Run is where the model changes character. Here the vendor stops merely enabling the brand and begins operating for a result: recover a dormant customer, restart a relationship, drive a second purchase, reactivate a subscriber, convert a declared intent, bring a lapsing buyer back before paid media has to. The buyer is the CMO and, increasingly, the CFO, because the conversation is no longer about campaign performance — it is about customer economics, about money that would not otherwise have appeared. The competitor is no longer an ESP or even an agency; it is the paid channels a brand reaches for when its owned attention runs out.

The pricing follows the accountability. It is not input-led; it is based on verified lift — a defined cohort, a concurrent, randomised control group rather than a prior-period baseline, an attributable outcome, and a payout only on what was added above what would have happened anyway. This is where the lost margin returns, because proven incremental value is the one thing a commodity pipe can never be. A brand does not need another dashboard confirming an email was sent and clicked; it needs to know whether a customer likely to be lost was recovered without paying to win them back, whether an in-email action created revenue rather than merely harvesting demand that would have arrived anyway, whether attention was rebuilt rather than spent.

Run is a fundamentally different business from selling software access, and it is more demanding. It requires operators, measurement discipline, creative judgement, experimentation and commercial courage; it will look services-shaped before it becomes a repeatable system, and that is acceptable — most outcome businesses begin as expert operations. The non-negotiable is honesty of measurement. Without a control group, every outcome claim is attribution theatre; with one, the vendor can say here is the baseline, here is the intervention, here is the lift, here is the payment. That sentence is the bridge from a marketing promise to a finance-grade fact — and it is the rung where an ESP becomes an Email Alpha company.

N  Network — the media rung

 Network is the top rung, and it arrives last because it must be earned. A brand’s inbox attention is valuable only while the customer keeps trusting it, and that trust is not created by inserting advertising into every available slot — it is created by making the emails useful enough that people keep opening them. Only a surface that has earned attention can become media.

When that condition is met, the surface becomes inventory: first for the brand’s own offers, then for carefully governed partner demand, and eventually as a cooperative network in which one brand’s earned attention can help another recover or acquire a customer in a permissioned, brand-safe way. The buyer changes again — partnerships, media, advertisers — and the competitor is not an ESP at all but retail media, commerce media and ad networks. The pricing is revenue-share, yield and media economics. But the sequencing is the discipline: first-party before third-party; utility before monetisation; trust before inventory; relevance before scale. A broker uses action modules for its own products before it carries anyone else’s; a retailer moves its own customers across categories before it sells a slot; a publisher serves its own subscription goals first. Network depends on everything below it — without Email there is no surface, without Act no interaction, without Run no proof that attention converts — which is exactly why it is the horizon and not the opening move. It is what an ESP becomes when it stops being a sender and becomes a marketplace for owned attention.

Where ActionAds belong — a bridge, not a rung

 The most common confusion is where in-mail action units sit, and the answer is that they are a bridge across the ladder rather than a rung of their own. A first-party action unit — apply, renew, calculate, sample, upgrade, restart, declare intent — lives inside the brand’s own funnel: sold as a capability it belongs to Act; operated against a control and paid on lift it belongs to Run. The artefact has not changed; only the commercial treatment has.

Partner inventory is different. The moment a unit carries an outside advertiser or a complementary brand, it begins to become media, and it belongs to Network — provided the host brand keeps control of category, frequency, relevance and exclusions. The cooperative network is the endgame: many brands operating trusted surfaces, each able to carry relevant action units without degrading engagement, with the vendor coordinating demand, recovery and acquisition across them. The rule is short enough to remember: first-party proves value, partner inventory creates media, the network creates the marketplace.

The two laws that make EARN a strategy

 A ladder of revenue models is only a menu unless two laws hold it together.

The first: a thing’s rung is set by how you sell it, not by what it is. The same living email can be Act or Run. Sold as a build, a capability or a managed experience, it is Act. Tied to a defined cohort, measured against a control and paid on attributable lift, it is Run. The artefact did not change; the commercial model did. The discriminator is the counterfactual: a clean baseline and payment on lift makes it Run; the absence of one makes it Act. And on any single audience you charge for the capability or you take a share of the outcome — never both, because no brand will tolerate paying twice for the same value.

Figure 4 — The same living email is Run or Act depending only on whether a clean counterfactual exists.

The second law: the rungs only compound if each one graduates customers to the next. Email funds Act; Act proves into Run; Run builds the attention density that makes Network possible. The number that tells a vendor whether the strategy is working is therefore not revenue per rung but the graduation rate between rungs — how many Email accounts adopt Act, how many Act pilots become Run programmes, how much trusted attention becomes Network inventory. Without that movement an ESP does not have a ladder; it has four disconnected product lines, and the commodity gravity of the ground floor will drag the whole structure back down to a per-send argument. EARN is a strategy only if each rung feeds the next.

3

The Business: Making the Climb Real

A model is only as good as the business that can be built on it. The architecture of EARN is clear; what decides whether it becomes a company rather than a slide is harder — the economics of each rung, the way the organisation is wired, what the buyer actually experiences, and the objections honest enough to break it. This part is about the climb in practice.

The economics of the climb

 The four rungs do not merely earn different amounts of money; they earn different kinds of money, and the market prices each kind differently. Email is software-shaped at the commodity end: infinite scale, near-zero marginal cost, but benchmarked to the floor and valued as a utility. Act is closer to classic software economics — a capability sold repeatedly across a base — and earns a software multiple when it is productised rather than hand-built each time. Run is, at least at first, services-shaped: it carries real cost of delivery, demands talent and judgement, and is valued more cautiously until it becomes a repeatable system rather than a heroic engagement. Network, once it has density, earns the richest economics of all — media and marketplace yield with network effects — but only a handful of operators ever get there.

Figure 5 — Each rung earns a different kind of money. Value and the multiple the market pays rise as accountability rises.

Two consequences follow, and both are easy to miss. First, the rung that returns margin (Run) is also the rung that consumes capital and attention, because outcome work is funded in advance and collected in arrears, against proven lift. Working capital, not demand, is often the real constraint on how fast a vendor can scale outcome programmes — a queue of eager pilots can starve a balance sheet. Second, the rungs have opposing financial signatures — a high-multiple, low-touch floor beneath a lower-multiple, high-touch middle — which means running them on one P&L blends two businesses the market would value separately. The discipline is to let the software economics of Email and Act fund the services economics of Run until Run becomes systematic, and to ring-fence each so neither distorts the other. The climb is not just a value story; it is a cash-flow story, and the vendors that misjudge the second never finish the first.

The operating model

 A new business model needs a new operating model, because the four rungs cannot share a single incentive and survive. The Email team runs infrastructure and is measured on deliverability, reliability, reputation and margin. The Act team runs experiences and is measured on adoption, action completion, data capture and time-to-deploy. The Run team runs outcomes and is measured on verified lift, recovery, control-group discipline and repeatability. The Network team runs media and is measured on fill, yield, advertiser repeat and the health of the audience’s attention. They can share technology, data, design systems and account relationships; they cannot share a scorecard.

The reason is gravitational. If a single team is measured only on send revenue, EARN dies inside the company — every quarter. The urgent renewal always beats the uncertain outcome pilot; the platform quota always crowds out the network experiment; the infrastructure mindset makes every higher rung look like custom work to be avoided. Spare time is Send time, and EARN never gets built in spare time. The structure has to make the higher rungs someone’s actual job, with their own targets, their own definition of success and their own permission to behave unlike the cash engine — services-shaped where the cash engine is software-shaped, patient where the cash engine is transactional. Without that separation, the new business is quietly strangled by the old one’s metrics.

If you are the brand

 EARN is written from the vendor’s side, but it is at least as useful read from the buyer’s. For a CMO, the ladder is a way to stop having one undifferentiated argument about email — price — and start having four precise ones. The send is an infrastructure decision: settle it efficiently, keep it reliable, and do not let it consume the conversation. Everything above it is a growth decision, and it should be evaluated on growth’s terms, not procurement’s.

The practical implication is that a marketing leader should refuse to let the two conversations contaminate each other. Outcome work judged as a line-item cost will always look expensive; the same work judged against a holdout, paid only on proven lift, is the safest budget a CMO can hold — spend that, by construction, cannot lose money. So the buyer’s discipline mirrors the vendor’s: agree the measurement before the money, own the baseline and the control group, and treat “no lift, no fee” not as a vendor concession but as the brand’s protection. The brand that learns to buy outcomes instead of sends gets a partner whose incentives finally point the same way as its own. And the brand keeps the thing that matters most — the owned customer relationship — instead of renting it back from a platform every quarter.

The honest objections

A credible strategy names what could break it, and EARN has five real failure modes. The first is measurement. Outcome pricing rests on a clean control group living inside the brand’s data, and whoever owns the holdout, the baseline and the attribution effectively owns the invoice. The control must be concurrent and randomised, never a prior period — otherwise a seasonal swing or a market cycle gets mistaken for the vendor’s lift, in either direction. If measurement rights are not agreed up front, every payout becomes a debate — the vendor claims lift, the brand questions incrementality, finance delays payment. Measurement is not an analytics detail; it is the load-bearing wall of Run.

The second is that outcomes are capital- and trust-intensive, a services-shaped business beside a software-shaped one, which must prove itself repeatedly across accounts rather than once in a friendly pilot — a single success proves possibility, a business requires repeatability. The third is surface control: a vendor may concede delivery pricing and still win if it holds the strategic surface, but conceding the volume, data and events that feed the upper rungs is fatal, because the pipe is also the distribution layer for everything above it. Race the pipe to zero and you lose the right to climb.

The fourth is customer trust. Network is tempting because media revenue scales, and dangerous because the inbox is not a billboard; if monetisation degrades attention, the network eats the very asset it monetises. Control of category, frequency, relevance, labelling and exclusions is not optional. The fifth is organisational drag: incumbents resist model migration, and the easiest evasion is to rename old work in new language. That is not EARN. EARN begins only when the unit of value actually changes — when a vendor is paid, on at least one real account, for an outcome rather than a send.

The new scorecard

 The migration shows up most plainly in what gets counted. The old scorecard measures effort and delivery — sends, delivery rate, opens, clicks, complaints, campaign revenue, throughput. Those numbers still matter; they are the telemetry of the Email rung. But they cannot describe the future, because they count what the vendor did, not what the customer’s business gained.

The old scorecard The EARN scorecard
Sends, delivery rate, throughput Action completion inside the email
Open rate, click rate Declared first-party data captured
Complaints, unsubscribes Recovery and reactivation rate
Revenue per campaign Revenue proven above a control
List size Real Reach (the genuinely engaged base)
Cost per send Click Retention Rate; attention yield
Graduation rate between rungs

The last line is the one that tells a vendor whether it is escaping the trap at all. An Email customer who never adopts Act is still a send customer; an Act customer who never reaches Run is still a capability customer. When you change what you count, you change what the business is — the scorecard is not a report on the strategy, it is the strategy made visible.

The staircase of who values you

 There is a simple way to see the whole migration: it is a staircase of who values the vendor. Stay on the ground floor and procurement prices you. Climb to Act and marketing values you. Reach Run and the CFO trusts you. Earn Network and you become a media business. The surface beneath your feet never changes — it is the same owned email relationship the whole way up. What changes is what you are willing to be paid for, and therefore who decides what you are worth.

This is not a call to abandon the send. The Email rung remains the foundation — it funds the system, protects the relationship, supplies the data and grants the distribution that makes every higher rung reachable. The instruction is only to understand it as the floor, not the ceiling. The vendor that refuses to climb will not fail dramatically; it will simply keep renewing, keep supporting, keep delivering, and keep losing altitude until it is absorbed, at an infrastructure multiple, into something larger. The vendor that climbs changes what the email business is for. The old ESP was paid to move messages; the new one is paid to make the owned customer relationship more profitable.

Figure 6 — Two frameworks, one surface. SNR is how a brand decides what to say; EARN is how a vendor decides how to be paid.

**

SNR is the brand’s grammar for what an email should do. EARN is the vendor’s model for how the same surface gets paid.

The next email company will not be paid to send more email. It will be paid to make every owned open worth more.

Thinks 2030

WSJ: “When it comes to nutrition, science is converging on the following recommendations for longevity and health: a diet rich in vegetables, whole grains, nuts and plant-based unsaturated fats, moderate fruit and fish consumption, low red- and processed-meat consumption, and very low ultraprocessed foods and added sugars. While protein consumption gets a lot of attention, research suggests a low but sufficient daily intake of 0.37 gram per pound of body weight, or about 60 grams for a 150-pound person, of which at least 50% is plant-derived, is ideal.”

Paul Kedrosky: “Job loss in the United States is more threatening than anywhere else in the wealthy world. It turns what should be a setback into a potential cascade — income, insurance, mortgage and child care, all at risk at once. Meanwhile, A.I. chief executives won’t stop telling Americans A.I. is coming for them. The technology is a missile aimed at the most fragile part of the American socioeconomic bargain. No wonder Americans are pessimistic about A.I. While better messaging will not fix this, decoupling health care from employment might. Building an unemployment insurance system that replaces income at a meaningful level might. Americans’ pessimism about A.I. is largely rational, about a technology tailor-made to crack their crumbling and antiquated social compact.”

FT: “[China’s] working-age population aged 15 to 64, which peaked at 1bn in the last decade, is due to fall to just 300mn by 2100, according to UN figures — a decline that could prevent China from becoming the world’s biggest economy. Beijing now sees AI-enabled machines as a way out of the demographic trap. Last year the country installed more industrial robots than the rest of the world put together; it also makes most of the world’s humanoids.”

WSJ: “Three questions confront American capitalism at this crossroads, the resolution of which will shape the lives of future generations. Will America deliver economic opportunity to more of its people—or will the gap between the extraordinarily successful and struggling widen? Will America continue building walls to the world—or will it build new bridges? And will America strike the right balance between competition’s creative destruction and the government’s regulatory guard rails—or will it tilt too far in one direction or the other?”

NeoMarketing’s Three Biggest Innovations

A new way to see the customer base, a new surface to act on it, and a new model to get paid for the outcome.

The lens and the surface

Every new category needs more than a product. It needs a new way of seeing the world — because without one, even the best product becomes a feature inside someone else’s frame. NeoMarketing begins with that reframe.

For two decades, marketers have treated the customer base as a list: names, emails, numbers, segments, journeys, campaigns. The list grew, the campaigns multiplied, the channels spread from email to push, SMS, WhatsApp, RCS, apps and paid media — and through all of it the core question never changed: what should we send next? That question is now too small.

  1. A new way to see — Owned Attention and the TAT.

The customer base is not a list; it is a portfolio in motion. Some customers are strong — still listening, browsing, returning. Some are weakening — drifting before the revenue loss shows up. Some are lost — known to the brand, but no longer reachable through ordinary CRM. Across a second axis, some have never bought, some bought once, some repeat. Those two dimensions — transaction depth and attention state — form the map we call the TAT (Transaction-Attention Table), and it turns marketing from a campaign calendar into a customer-state discipline. It shows where value is created, where it is leaking, and where the brand is about to pay twice. A customer sliding from strong to weakening is not merely less engaged; she is becoming future reacquisition cost. A customer who falls into lost is one the brand may soon rent back through Google, Meta or a marketplace. That is AdWaste: paying again for a relationship you already earned. The job is no longer to send more campaigns; it is to move customers to better states — Capture, First, Second, Repeat, Protect, Recover.

Three innovations at three altitudes, the vision above and the Three NEVERs beneath.

  1. A new surface to act — Living Emails.

If the TAT says which state a customer is in, the next question is where the movement happens. For years the answer was “channels” — but channels were treated as pipes, carrying messages written earlier to people whose context had changed by the time they opened. Email suffered most, because it stayed static: composed at send, priced by volume, judged by broken metrics. Brands concluded the inbox had lost relevance. The sharper truth is that customers did not abandon the inbox; they abandoned boring brand emails. A Living Email reverses the logic. It is composed at open: it checks what is true now — availability, price, status, reward balance, the right next step — and decides whether the customer needs Sell, Notify, Digest or Relate. It can show a replenishment to one customer, a useful digest to another, a recovery path to a third, and complete the purchase in the inbox by UPI or a saved card. This turns email from a message into a surface: the owned room where a customer can see status, take a useful action, redeem a reward, reorder, resume a relationship — and leave a trace. WhatsApp is the knock; email is the room.

Together the first two form the operating spine: the TAT tells you what state the customer is in; Living Emails give you the surface to move them.

The model and the horizon

  1. A new model to get paid — Alpha and Progency.

A better lens and a better surface are not enough; martech is full of better tools that became line items rather than shifts. The third innovation changes the commercial model itself. Traditional martech is paid for access, seats, contacts, sends or services; agencies are paid for activity; adtech is paid for reach — and none of them is aligned with the only question a CMO and CFO actually share: did marketing create profit above what would have happened anyway? NeoMarketing is paid for proven profit. Beta is the baseline. Alpha is the verified lift above it, measured against a holdout. Carry is the partner’s share of the Alpha, and only the Alpha — no lift, no payout, no attribution theatre. Progency is the vehicle: the Profits Agency, an accountable operator that runs Recover in the lost column, Protect in the weakening, and Repeat in the strong, and earns on the lift it can prove.

This is where the three click together. The TAT defines the state and the counterfactual; the Living Email creates the intervention at the moment of attention; Alpha pricing proves whether it worked. And because the same surface that creates the action also writes back the result, every state, message, holdout and outcome becomes part of the system’s memory.

The three innovations as one loop — and the memory that compounds with every cycle.

**

The horizon. That memory points somewhere: an Artificial General Marketer. AGM is not the product sold today; it is the direction of travel. A generic AI agent can write copy, choose an audience and optimise a campaign — that will soon be table stakes. The durable advantage is not the agent; it is the operating memory beneath it. Every decision is written back, so the system learns what actually moves a customer — from lost to recovered, weakening to protected, one to repeat — against which counterfactual, at what cost, in which category. That is what the three innovations compound towards.

Why they matter together. The Three NEVERs stop being slogans and become measurable. Never Lose Customers means detecting and protecting attention before revenue disappears. Never Pay Twice means recovering known customers before paying adtech to reacquire them. Never Pay Fixed means paying for proven Alpha, not activity. Marketing has spent years becoming faster, more automated and more channel-rich; NeoMarketing asks it to become accountable — not more sends, journeys or dashboards, but more customers moved to better states, and more profit proven.

The lens without the surface is just analysis. The surface without the model is just product. The model without the lens is just pricing. Together they become the Anti-Martech system: see the leak, act in the owned surface, prove the profit — and let every decision make the next one smarter.

**

NeoMarketing introduces a new way to see the customer base, a new surface to act on it, and a new model to get paid for the outcome — and, with every decision written back, it compounds towards a marketer that can run all three.

Thinks 2029

WSJ: “[Consulting] firms have primarily focused on two alternatives to the hourly model: fixed fee and outcome-based pricing. Under fixed fee, firms guarantee a specific, predictable cost for a defined output or project scope, regardless of the hours spent. Outcome-based pricing generally means consultants get paid if they achieve certain mutually agreed-upon metrics for the client, or a range of outcomes based on over- or underperformance…“The shift towards fixed-fee and value-based billing has put considerable pressure on consultancies to produce more output,” said GPTZero CEO Edward Tian. “But if that comes at the expense of basic fact-checking, the reputational damage for the firms themselves and the clients who commission their work is enormous,” Tian said.”

Business Standard: “AI agents are expected to become a new workforce layer, forcing companies to rethink the traditional fresher hiring pyramid that powered India’s IT and consulting industries for three decades. Many executives have been talking about the pyramid reshaping into a diamond, requiring fewer people at the bottom and an AI-native experienced layer in the middle.”

FT: “Holmes is regularly high on the lists of fictional characters most portrayed on screen, up there with Father Christmas and Dracula. Even if you’ve never read one of the stories, you know who he is. And you’re only going to see more of him, because Conan Doyle’s works are now out of copyright, so the character is anyone’s to play with.”

Mint: “India stands at the threshold of a new investment-led growth phase that could redefine its economic trajectory over the coming decade. Much like the investment boom of 2004-08, the country is again seeing the early stages of a broad-based capital expenditure upcycle. This time, however, the foundations appear stronger, more diversified and strategically aligned with long-term national priorities. At the heart of this emerging cycle is a shift towards domestic capacity building. Policymakers are increasingly focused on reducing dependence on imports in critical sectors such as energy, defence, technology and industrial supply chains. Combined with strong domestic demand, supportive reforms and healthy corporate balance sheets, this strategy is laying the groundwork for a sustained rise in investment and economic growth.”

Email’s Next Act: Outcomes, Not Sends

Published July 22, 2026

1

How Living Emails turn the inbox into Progency’s owned profit surface.

Stop renting back your own customers.

Email did not go quiet because customers left the inbox. It went quiet because the email never changed, got priced on sends, and was measured with instruments that broke — so brands misread a measurement failure as a channel death, and began renting their own customers back through adtech and WhatsApp. Artificial intelligence changes what an email can be: composed at the moment it is opened, it becomes the one owned surface where a brand earns attention, completes the action, and proves the profit. Progency — the Profits Agency — operates that surface for outcomes, not sends.

**

Arun’s inbox

Arun is not thinking about marketing when he picks up his phone at 7:42 on a Tuesday morning. He is clearing the overnight scroll before the day takes over — a bank alert, a school message, a delivery update, a payment reminder — and among them, two emails from brands he has actually bought from.

The first is familiar. The subject line says “Weekend Sale — 30% off.” It arrived three days ago. The products inside are the same for Arun as they are for thousands of other people. One of them is already out of stock in his size. The discount is still live, but nothing in the message knows that he bought a similar product last month, returned one item, and has not browsed the brand since. It is technically personalised, because it says “Hi Arun.” It is behaviourally blind. He swipes past it without a thought.

The second looks ordinary too, until he opens it — because it was sent yesterday, but it was not truly written until this morning. The instant Arun opens it, the message checks what is true now. His refill window is due. The product is in stock. The price is current. His reward balance can be applied. So instead of a generic promotion, it shows the one useful next action: reorder the thing he is about to run out of, delivered Thursday — and pay for it right there, inside the email. There is also a small question: would he prefer the next reminder in 25 days or 30? He taps once. The order is done before the kettle boils.

That last move matters more than it looks. This is a repeat purchase, so the brand already has Arun’s address and his payment details on file. A second order does not need a journey back to an app or a website and a re-login and a re-entered card; it needs a single confirmation. In India, UPI turns that into a one-tap approval. Elsewhere, a stored card does the same. The transaction completes in the place where the attention already is.

The difference is not personalisation. It is timing — the decision, and the payment, made at the moment of open.

The first email was a message. The second was a surface. The first tried to push a campaign into Arun’s morning; the second used the moment of attention to decide what mattered, and let him act on it without leaving. That is the difference between email as brands have used it for twenty years and email as it can now become.

So the question is not whether customers still open the inbox. They do; Arun just did. The question is why almost every brand email still behaves as if nothing has changed since the era of batch campaigns. This series is about that gap — why the old world failed, why WhatsApp rose, why email was misdiagnosed, and how a living, transacting inbox becomes the surface where a brand finally moves from activity to profit.

Key takeaway: One email was written last Tuesday. The other was written the moment Arun opened it.

 2

The portfolio and the leak

Step over to the brand on the other side of Arun’s screen. Most brands still think of their customers as a list — a large one, perhaps segmented and scored and wired to a data platform, but a list all the same: contacts waiting for the next campaign. That model is too small for the economics brands now face. A customer base is not a list. It is a portfolio in motion. Some customers are attentive and active. Some bought once and never formed a habit. Some repeat, but only in one category. Some were valuable and are quietly weakening. Some have gone silent. And some are being celebrated as freshly acquired inside an ad platform — even though the brand had already paid to acquire them once before.

You can lay that portfolio out on a simple map. One axis is how deep the relationship runs — none, one, or repeat purchases. The other is how alive the attention is — strong, weakening, or lost. Those two dimensions matter more than most demographic segments, because they tell you what to do next. We call this map the TAT (Transaction-Attention Table), and for this essay that is all you need to know: it shows where each customer stands, and which way they are sliding.

Across that map a brand has six moves. Capture turns an anonymous or intermediated relationship into a known customer. First moves a known non-buyer to a first purchase. Second turns a first buyer into a repeat one, where habit begins. Repeat grows frequency, category and margin. Protect stops a weakening customer sliding into the lost column. Recover brings a lost customer back before the brand pays to buy them again. These are not campaign names. They are state movements — and the difference is everything. A campaign asks, “what should we send this week?” A state movement asks, “which part of the portfolio is leaking value, where should those customers move to, and how will we prove the lift?” Only the second question is one a CFO can fund.

That is the bridge from Beta to Alpha. Beta is what would have happened anyway — the sales, repeats and returns the current machine would have produced. Alpha is the verified lift above that baseline. It is not attribution theatre; it is measured against a held-out group of customers you deliberately left alone. It is customer-state improvement turned into profit.

And here is where the money leaks. When customers drift rightward — strong to weakening to lost — most brands notice nothing, because nothing in the dashboard reports it. Then, once a customer is well and truly gone, the brand pays an ad platform to win them back: a customer whose email address has been in its own database the whole time. The dashboard may call that growth. The P&L knows it is a tax.

The map: every customer sits somewhere on it, and the six moves push them toward a better state.

Key takeaway: The goal was never more campaigns. It is moving customers to a better state at lower tax than today.

3

Pull, and the cost of getting it back

The best customer is not the one who responds to the cleverest campaign. The best customer is the one who comes back without being chased — who opens the app from habit, searches for the brand by name, reorders when they run low. That is pull, and it is the highest-quality outcome in marketing because it costs the least and taxes the least.

But pull is not spread evenly across the portfolio, and it does not last. A few customers return on their own; most need a nudge; and as attention decays, the force required rises with every step. Picture a ladder of four rungs. On the bottom is pull — free, owned, the customer arriving by themselves. One rung up is prompted pull — a light owned nudge to someone still listening: an email, a push notification, a message. Higher still is earned push — you cannot ask for the sale yet; you have to earn attention back first, through usefulness, recognition or service. And at the top is paid push — renting reach from an ad platform, a marketplace or a retargeting pool.

Every rung up is more expensive than the one below, and less yours. Adtech sits at the very top: the costliest, least owned form of reach there is — and most often aimed at people whose email address you already hold. Most brands blur the rungs. They treat everyone who did not buy this week as fuel for the next campaign or the next retargeting pool, and so a customer who could have been brought back with a near-free owned nudge gets pushed into a high-tax channel instead. That is how AdWaste begins.

So the discipline is the reverse of the instinct. Not “how do we push harder?” but “how do we drag customers back down the ladder, toward pull, so we stop paying to push them at all?” Move paid push back to earned push, earned push back to a prompt, the prompt back to pull. That is what refusing to pay twice for the same customer actually looks like in operation. Push is not a virtue to be maximised. It is a bill — the bill that arrives when pull runs out.

The four rungs of reach. The higher you climb, the more you pay and the less you own.

Key takeaway: Push isn’t the goal. Push is the price of attention you let slip — and adtech is the most expensive way to pay it.

4

The knock and the room

Be fair to WhatsApp, because it earned its place. In India especially it became the natural rail for business messaging, because it sits where people already live. It is phone-native, immediate, two-way, and it feels personal. For a knock — a one-time password, a delivery update, “your table is ready” — nothing beats it. A marketer understands the appeal in ten seconds: the message lands where the customer already looks all day.

So the case for email cannot be nostalgic, and it cannot be “email beats WhatsApp.” That is the wrong fight. The sharper distinction is this: WhatsApp is the knock; email is the room. A knock interrupts, reminds, alerts. A room holds: it has a body, a memory, layout, search, status, content, choice, payment and proof. Seen through the four jobs of an email — Sell, Notify, Digest and Relate — WhatsApp is strong at Notify and can push Sell hard, but it is weak at Digest and Relate, the two that build a relationship rather than spend it. Email can run all four.

And then there is cost, which is no longer a worry on the horizon. Meta has retired the old model where a day’s conversation counted once, and now charges for every marketing message delivered, with no volume discount.  India’s marketing rate rose roughly ten per cent in January 2026. And Meta is rolling out a max-price bidding system for marketing messages — in limited beta from mid-2026, opening more widely later in the year — in which the price to reach each person is set by how valuable the platform judges that person to be.

That does not make WhatsApp bad. It makes it a platform, and platforms follow a pattern: they begin as reach, and over time they segment that reach, filter it, and price it. Read the bidding feature plainly and the pattern is unmistakable — you will soon bid, in an auction, to reach a customer who already gave you their number and their permission, at a price the platform sets. That is the adtech model arriving inside the chat window: pay more, each quarter, for less of the reach you used to get for free.

Email’s economics run the other way. You own the list; the marginal cost of one more useful email is a rounding error; and it is the one channel with a room large enough to carry a relationship and let the customer act inside it. The right architecture is therefore not email or WhatsApp. It is WhatsApp to knock, email to hold: the knock for urgency and service, the room for Digest, Relate, commerce, memory, proof and recovery. A brand that treats WhatsApp as the whole relationship will inherit platform economics. A brand that uses the knock to bring customers into a room it owns keeps control of its attention, its data and its margin.

What each surface can hold. The two jobs that build the relationship are the two WhatsApp cannot run.

Key takeaway: When you have to bid to reach a customer who already gave you permission, that isn’t a chat app any more — it’s adtech in a chat bubble.

5  

Why email never had its moment

If email is this good — owned, cheap, the one channel with a room — why is Arun’s inbox still full of the email he ignores? The lazy answer is that brands did not try hard enough. The real answer is more uncomfortable: the email category was structurally built to under-imagine itself. The incentives, the surface, and the instruments were all wrong at the same time.

Email was priced on sends. An email service provider earns more as you send more — more contacts, more volume, more throughput. So the whole industry optimised the thing it bills for: deliverability, speed, segmentation, list size. It did not optimise the thing that actually matters, which is whether the email was worth opening. A business priced on sends will never build the email that makes sends matter less.

The surface was never the provider’s to change. An email is a block of HTML rendered inside someone else’s software — Gmail, Apple Mail, Outlook. Unlike an ad platform, where the unit, the auction and the measurement all live in one system, the inbox belongs to the mailbox providers. So providers concluded, correctly, that they could not change the client — and quietly stopped trying to change the email. The artifact has barely moved since around 2010.

The one real attempt was a half-door. Interactive email arrived as a glimpse of what the medium could be, but client support stayed uneven: Apple Mail and Outlook never supported it the way Gmail did, so it reached a fraction of the audience and demanded a full ordinary fallback anyway. Marketers heard “not universal” and stopped. The better conclusion — that interactivity is one rendering path, and the real strategy is to compose at open with a graceful fallback — was never drawn.

Then the instrument broke. In 2021 Apple began pre-loading the images in every email before the recipient opened it, which made the open rate — the number the whole industry watched — unreliable. Brands lost the ability to see the attention they were still getting. Their dashboards went dark, and they read the darkness as death, while WhatsApp handed them clean delivery counts and crisp read receipts. The contrast that drove the great migration was never attention versus no attention. It was measured versus unmeasured.

And the thing that would have changed everything was too expensive. Composing a genuinely different, current, relevant email for every reader at the moment they open — not a template with a name dropped in, but a fresh decision — simply could not be done at scale. Until artificial intelligence made it cheap, which happened roughly the day before yesterday.

Put those five together and the industry’s conclusion — “email is dead, move the budget to WhatsApp and ads” — was a misdiagnosis. The patient was not dead. The thermometer was broken, the treatment had not been invented, and the people who could have invented it were paid to do something else entirely.

Key takeaway: Customers didn’t abandon the inbox. They abandoned boring brand emails — and the industry misread that as the inbox dying.

6

Living Emails and SNDR

So here is what changes. The old email is a bet placed in advance. A marketer chooses the segment, the copy, the products, the send time, and then freezes all of it, hoping the context still holds when the customer opens. Often it does not: the price moved, the item sold out, the customer already bought, the moment passed. The email that looked intelligent at send looks stale at open.

A Living Email reverses that logic. It is composed at the moment of open. It checks what is true now — the customer’s state, the live price, what is in stock, the reward balance, the last action, the best next step — and assembles itself for that person, then. It can show Arun one thing at 7:42 and a different thing at 9:30. It can switch from Sell to Relate if his attention has weakened. It can hide an offer he has already taken. This is not personalisation as the word is usually meant — a name in the subject line, a category branch in a journey. It is closer to decisioning: the decision is delayed until the customer actually pays attention.

A surface that makes decisions needs to know which decision to make, and that is the job of SNDR — the four jobs of email. Sell asks for the transaction. Notify carries trust: the order confirmation, the alert, the statement, and it is the one email everyone still opens. Digest earns attention by being useful even when there is nothing to buy. Relate rebuilds the relationship before any ask. Most brands send only Sell and Notify, and then wonder why attention erodes — they only ever spend it, never deposit. A weakening customer does not need a louder discount; that is just spam with good intentions. The rule is simple: the attention state picks the job, and the move you want picks the ask. The Living Email composes both, at open.

One of those mechanics deserves to be pulled to the front, because it is where attention turns into money: paying inside the email itself. When a customer can complete the purchase in the inbox — no detour to an app, no re-login, no re-entered card — the gap between intent and transaction nearly disappears. This is most powerful for repeat purchases, where the brand already holds the address and the payment details, so a reorder is a single confirmation rather than a checkout. In India, UPI makes that a one-tap approval; elsewhere, a stored card does the same. The inbox stops being where you announce the offer and becomes where the sale actually closes. The other mechanics — small interactive units, visible rewards, a status line, a written-back record — matter too, but they are the vocabulary. The point is that the email stops being a message and becomes a surface you operate.

Attention state picks the job; the move picks the ask. The Living Email composes it at open.

Key takeaway: A static email is a prediction made at send. A Living Email is a decision made at open.

 7

The Living Emails Factory

A fair objection: if Living Emails are so obviously better, why does almost nobody make them? Because they are hard to make. One interactive, always-current, composed-at-open email today means creative, code, an interactive version and an ordinary fallback, testing across a dozen clients, plumbing into live product and payment data, approvals, a held-out control group, and a measurement setup to read the result. That is weeks of work for a single email.

Placing an ad on Meta or Google, by contrast, takes minutes: choose an audience, drop in creative, set a budget, go. The platform carries the production system, the auction, the measurement and the feedback loop. Email never had an equivalent. So adtech won part of the budget not because it was better, but because it was easier, and brands defaulted to static templates and repeated journeys — the old email survived because it was easy to make, not because it was good.

The Living Emails Factory is the missing production system. Its job is to make the advanced email as easy to create as the old one. A marketer — or a Progency operator — chooses the customer state, the move, the guardrails, the product feed and the outcome. The Factory generates the email, picks the SNDR job, assembles the right blocks, handles the interactive version and the fallback, wires in the live data and the in-email payment, sets up the holdout, and writes back what happened so the next email is smarter than the last. The brand does not have to become an email-technology shop; it describes the outcome and the Factory produces the surface.

This is where a martech company can own the category. Not by crafting the single cleverest email — anyone can do that once, by hand — but by building the authoring and operating environment that makes the clever email routine, repeatable, and as easy to launch as a campaign on an ad platform. The next email company will not win by sending cheaper or adding an AI copywriter to an old tool. It will win by removing the friction that kept the better email from ever being built.

The Factory turns a long wish list into one production system, from surface to proof.

Key takeaway: Composing a Living Email should be as easy as placing an ad on Meta or Google. Make that true, and the reason brands fled to adtech disappears.

8

The two future plays

Once the inbox becomes a surface customers genuinely open — daily, by choice, because the email is worth their sixty seconds — two things become possible that no ordinary send channel can do. But they must be sequenced with discipline, because getting the order wrong is fatal.

The first is that earned attention can be monetised. Not banners stuffed into emails, which would poison the very thing that makes the surface valuable, but action-led, relevant, brand-safe units placed inside a surface the customer already values: a partner benefit inside a financial digest, a sample inside a weekly training email. This is the exact inversion of adtech. In adtech the brand pays a platform to reach customers; here the brand that has earned the attention is paid for it, and that revenue can fund still more useful email.

The second is that earned attention can be pooled. When many brands hold genuine, opted-in inbox attention, those surfaces can cooperate — one brand’s living inbox helping another reach or recover a customer before either goes to the auction, through a one-tap subscribe, a trial, a sample or a recovery path. It is the cooperative alternative to rented reach, built out of owned surfaces.

But the sequence is the strategy. Earn attention first. Monetise it later. Network it last. A dead inbox has no inventory to sell and no attention worth pooling; monetise before you have earned the open and the customer simply stops opening, leaving nothing to monetise at all. These are the high ceiling of the idea, not the day-one pitch — the reason the surface, built properly, compounds in value instead of decaying like a list.

The order is not a preference. It is a constraint.

Key takeaway: Earn attention first. Monetise it later. Network it last — get the order wrong and there’s nothing left to monetise.

9

Progency: the Profits Agency

A better email surface, left alone, becomes just another feature — another demo a busy CRM team never fully uses. Progency changes the commercial frame so that cannot happen. It does not sell email software. It operates the surface and is paid on the profit it can prove. Progency is a Profits Agency: an accountable operating layer that sits after the CRM and before the auction, takes responsibility for defined customer states, runs the interventions, measures against a holdout, and earns only on verified lift.

It runs three mandates, one per attention state, and each is really a bet against a different counterfactual — a different answer to “what would this customer have done anyway?” Recover is for customers gone dark; the counterfactual is adtech, the money the brand would otherwise spend to buy them back. The email begins with connection, then recovered attention, and only then conversion. This is the wedge, because it attacks the most expensive leak and the one almost nobody else fixes. Protect is for valuable customers whose attention is cooling; the counterfactual is drift — left alone they become lost and later expensive to reacquire — and the email is Digest and Relate, arresting the slide before it is irreversible. Grow is for the attentive; the counterfactual is a slower next purchase and margin left on the table, and the email is Sell and Notify made live — the right next purchase, completed in the inbox via UPI or a saved card, with the customer suppressed from paid retargeting because they are already reachable for free.

Three mandates, one per attention state — each a bet against a different counterfactual.

The model is simple enough for a CFO. Beta is what would have happened anyway. Alpha is the verified lift above the holdout. Carry is Progency’s share of the Alpha, and only the Alpha — no lift, no fee. The old service-provider invoice was tied to usage; the old agency retainer to activity; the adtech bill to rented reach. Progency’s payout is tied to profit improvement, full stop.

This is also why the surface has to be a Living Email and not a send. Because the email is composed at open and every action — including the payment — is written back, the surface both produces the intervention and records its trace. It knows what state the customer was in, what was shown, what was held out, what action was taken, and what revenue followed. That is the operating memory a competitor cannot copy by bolting an AI copywriter onto an old tool. Email stops being a line item priced by volume and becomes the place where marketing finally proves its profit, one customer at a time.

The surface produces the action and writes back the proof — Beta, Alpha, Carry, in one loop.

Key takeaway: Email stops being something you pay for by the send. It becomes the surface you pay for by the profit.

10

Maya’s dashboard

We began with Arun, the customer. We end with Maya, the marketer who runs this surface for her brand.

Maya’s old dashboard was busy: sends, opens, clicks, click-to-open rate, attributed revenue, deliverability, unsubscribes, journey performance, WhatsApp delivery, retargeting return. Everything moved, and yet the one question that mattered stayed hard to answer — did marketing make the customer base more valuable, or did it just run more activity through more channels? It measured effort, not effect. And much of it went half-dark the day Apple stopped reporting opens.

Her new dashboard begins with the portfolio. How many customers are strong, weakening and lost. How many moved from one purchase to repeat. How many weakening customers were protected before they slipped away. How many lost customers were recovered before adtech bought them back. How much paid push was avoided, and how much Alpha was generated above the holdout. Her Monday question used to be “what campaign do we send this week?” It is now “which customer state must improve this week — and what will move it?” That single change in the question is the whole change in the discipline; it is the difference between managing campaigns and managing a portfolio, and it changes her conversation with the CFO from opens and clicks to recovered customers, protected customers and profit above baseline.

Not effort, but effect: state movement, Alpha above holdout, and the waste avoided.

This closes the loop that began with Arun. The Living Email he acted on was not a clever message; it was a small state movement. He moved from attention to action, and paid in the inbox. The email wrote back the trace. The holdout proved the lift. The dashboard showed the Alpha. Maya did not have to argue that email mattered. She proved it.

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Summary

The arc, in three acts

Act I — why email went quiet. It was not the inbox that died. The customer base was treated as a list; pull decayed into paid push; WhatsApp won the knock; and email was misdiagnosed because the surface stagnated while the measurement broke.

Act II — the new surface. A static email is a prediction made at send; a Living Email is a decision made at open. SNDR governs which decision, in-email payment closes the sale, and a Factory makes the whole surface as easy to produce as an ad — removing the friction that sent brands to the auction in the first place.

Act III — outcomes. Progency operates the surface and is paid on proven Alpha, across Recover, Protect and Grow. Email stops being a cost measured in volume and becomes the place where profit is earned and proven — before brands rent their customers back from the auction.

The whole picture on one slide — from the leak to proven profit, and the future that compounds. (Two perspectives)

Key takeaway: Email’s next act isn’t sending more. It’s earning attention, composing action, and proving profit — before brands rent their own customers back from the auction.