Rajesh Jain

Recover the Rest — and how it should be bought

Which brings us to the play with the most money in it, and the one nobody owns.

Today the lost column is handed to adtech by default, and the mechanism is worth watching in slow motion. You pay a platform to retarget. The platform re-shows your own customers to themselves — people already in your CRM. Some of them re-buy, which is revenue you would have had some share of anyway. And the measured performance of that campaign raises your acquisition cost benchmark, so next quarter you pay more for the same trick. For most brands around seventy per cent of repeat transactions come back through this rented channel, at roughly a third of the transaction value, which is exactly what a return on ad spend of three means.

It hides under different names in different industries. In banking and insurance the same tax appears as aggregator commissions and comparison-site payouts. In telco it is dealer reactivation spend. Different collector, same leak.

Here is where most teams go wrong when they try to fix it in-house: they treat recovery as a harder win-back campaign. But by the time a customer is in the lost column the channel is still open and the customer has simply stopped listening. Sending a sharper offer down a channel no one reads only trains them to ignore you faster. Recovery is not a better campaign. It is a different machine.

That machine runs a different sequence: attention, then repetition, then conversion. It re-earns the open, builds the habit of opening, and only then asks for the sale. Relate carries no offer at all — it is a reason to open, not a discount, and its only job is to rebuild reachability. Digest turns a re-opened inbox into a habit. Sell comes last, when the customer is paying attention again, and it closes in the channel, with no detour to a website where the intent leaks away. The CRM team starts at conversion, because that is what it was built to do. Recovery starts at attention, and earns the right to sell.

The sequence, the capability, and the only acceptable way to buy it.

The sixth play deserves an owner that does exactly this, and nothing else. Call it a Team 6: a small pod with one number to hit, working the lost column on owned channels, before the auction. The name carries the number. Adtech recovery runs at a return on ad spend of about three, which is a tax of roughly a third. Owned recovery runs at roughly half that tax, which is roughly double the return — a six. Team 6, because its job is a ROAS of 6.

Illustrative and conservative. The ₹-per-customer reacquisition cost, the recovered share and the margin are all yours to replace with your own figures.

A brand can staff this two ways. Build it in-house — three or four people who own the outcome with agents running the volume underneath — or buy the outsourced version, which is what I have called Progency, delivered by MarTech Growth Engineers who bring vertical expertise, sit close enough to the business to understand its context, and own the number rather than the campaign calendar. Same function, same measurement, two ways to staff it. Nothing else about the model changes between them.

Both halves are load-bearing, and it is worth being precise about why. The agents supply scale: cohort discovery, analysis, content variants, channel choice, timing, and continuous learning from what happened. The engineers supply the other half: domain knowledge, business judgement, governance, exception handling, and ownership of the result. Agents without accountable humans are automation without judgement. Humans without agents simply recreate the arithmetic constraint that caused the problem in the first place.

What must not change is how it is bought. Never Pay Fixed is not a slogan about discounts; it is a statement about where the risk sits. A named group of lapsed customers is worked. A matched group is left alone alongside it, still receiving whatever you do today. Concurrent, randomised, and measured against your current best effort — never against last quarter, which measures the season as much as the work. You pay a share of the difference, and only the difference.

No improvement, no invoice. No control, no claim. That single mechanism is what separates this from a vendor’s spreadsheet: the number is measured against a control the brand audits and the vendor cannot move. And it is the cleanest test you can apply to anyone selling you outcomes, including me. Ask whether they will hold back a control group and take their fee only on the lift. The answer tells you whether they believe their own deck.

There will be cases where hybrid economics are the sensible answer, because delivery and infrastructure do cost something before any lift exists — a baseline plus a share of the alpha. That is a reasonable structure. What must survive intact is the principle underneath it: the upside paid to a partner comes from measured incremental value, never from activity dressed up as performance.

The honesty has to travel with the limits, so here they are. Recovery at a return of six is strongest for replenishment-led categories — beauty, supplements, grocery, pet — where the timing is predictable, and for high-value customers where the relationship was real before it went quiet. It is weakest for one-off, high-consideration purchases with no repeat logic. And gross margin governs a separate question from the saving: the saving from re-routing revenue more cheaply is the same at any margin, but whether a recovery is worth running at all depends on the return clearing one divided by your gross margin — comfortable at seventy per cent, demanding at fifteen. Scale is reached by stacking cohorts that each clear the bar against their own control, never by averaging good cohorts and bad ones into a blended promise.

One more constraint belongs in the open, because it shapes how fast any of this can go. Outcome-only pricing means funding the delivery upfront and collecting in arrears. That caps how many pilots can run at once, for the vendor and for the brand’s patience alike. It is a real limit, and a model that does not name it is not being straight with you.

The arithmetic of the whole essay lands here. A business on a ten per cent operating margin that recovers something like thirty per cent of its revenue through paid media today is paying roughly a third in tax on that share. Move it to owned recovery at roughly a sixth and you save about sixteen points on the recovered share — a cost you simply stop paying, so it falls straight to profit. Tighten the five owned plays and add perhaps five per cent of revenue on top. Ten per cent operating margin becomes something close to twenty. On $100m of revenue, roughly $10m of profit becomes roughly $20m — and none of it required a bigger budget.

The test of whether a partner believes its own numbers is whether it will hold back a control and take its fee only on the lift.

The largest ground you own is the email inbox

If context compounds only on owned ground, the practical question becomes which ground you own the most of. For almost every consumer brand the answer is the one nobody wants it to be.

Seventeen crore Indians open an email every month. Thirteen crore click something inside one. You own that channel outright: no platform can change the rules, raise the price, or switch off your reach overnight. It costs fractions of a paisa a message, against a per-message fee on every other channel you run. And it is already permissioned — you have the address, the consent and the relationship, with nothing to rent back from anyone.

One caveat deserves stating before anything else, because for some brands it ends the section. If your forms capture a mobile number and not an email address, none of what follows is available to you, and fixing the capture form is the whole of your first quarter’s work. Capture is play one for a reason.

Now, the reason nobody in your marketing team believes any of this. For twenty-five years, an email could do exactly one thing: click out. It was written on Monday, it was true on Monday, it was sent to everybody, and the only real action available took the customer out of the inbox and onto a page where most of them never arrived. Every email innovation for two decades made that single verb prettier. Better templates, better subject lines, better send-time optimisation — all of it in service of a click that leaked most of the intent it created.

That constraint has gone, and it has gone in stages worth naming, because most brands stop one rung too early and conclude the whole thing was overhyped.

Most brands reach L1, call it interactive, and stop. The inflection is two rungs further up.

L0 is the ordinary email you send today. L1 adds an interaction inside the message — a calculator, a poll — which is where the phrase “interactive email” usually stops. L2 writes the input back: forms and declared data land in your record. L3 is app-like and multi-step: an OTP, a checkout, a KYC step, completed without leaving the message. L4 is the one that matters. A living email is composed at the moment it is opened, not at the moment it is sent.

The inflection is L3 to L4, and it is a change of kind rather than degree. Fixed-at-send becomes composed-at-open. That is the precise moment an agent stops drafting a campaign and starts making a decision — with the real price, the real stock, the real balance and the real availability fetched at open, and again on every tap. It is also the moment the two halves of this essay join: the context layer is what the message is composed from, and the message is what deposits the next piece of context back.

Take an ordinary case. Arun is sent a replenishment email on Monday and opens it on Thursday. The old email shows him what the brand decided on Monday — a price that may have moved, stock that may have gone, an offer he may already have used. A living email asks what is true on Thursday. Is the product in stock now? Is he inside his replenishment window? Has he already bought it elsewhere in your estate? What is his reward balance at this second? Does he need a transaction at all, or would something useful serve the relationship better today? The message stops being a message and becomes a viewport onto the live relationship.

So much for capability. The business case is separate, and it has three parts, because email today sits on your P&L as a cost line — a per-message fee, a list you rent access to, and an open rate nobody can spend.

Yes-in-email. The lowest-friction action there is. Consent, an application, a lead for the next product — captured inline and validated with an OTP, with no landing page in between. Nothing leaks between the intent and the record, which means more of the intent you already paid to create survives to the record.

Pay-in-email. The transaction ends where the attention already is. Bills, renewals, repeat orders, restarts, top-ups. You created the intent and then asked the customer to travel for it; the click-through was never a step in the journey, it was the leak. Six chances to lose them become one.

Pre-adtech recovery. The lost column, worked on a channel you own, before a single rupee goes to a platform to rent back a customer already sitting in your database. This is the sixth play, and it is large enough to get its own section.

There is a fourth thing, and it is the one almost nobody does. Most brands have two or three useful things to say in a week and send twelve emails anyway. The daily digest is the opposite: something useful, on a rhythm, whether or not there is anything to sell. For a bank or a broker, the money note — where the portfolio moved, bills due this week, the SIP that went through, one thing worth understanding, with numbers current at the second the customer opens it. For retail or fashion, what came back into stock in the size they buy and the two colours they own. For travel, where their points stand and what the fare is on the route they always fly.

It looks like a soft play and it is the hardest-working one on this list, for two reasons. It earns you the right to be opened on the day there is something to sell. And it quietly feeds the context layer every single week, at almost no cost, on ground you own.

Put all four together and the cost line changes sign. Start with delivery and content. Subtract what capability earns — the yes and the pay completed in-channel. Subtract what outcomes earn. Subtract, eventually, what a channel people open is worth to a third party. Net cost lands at or below zero. The order of those terms is the order of the build, and it is not negotiable: capability earns first, outcomes earn next, and only a channel people already open is worth anything to anyone else. You cannot begin at media.

EARN is a business-model migration, not a feature list. The sequence is the substance.

And one rule keeps the whole ladder honest, because without it EARN becomes a way of billing the same brand twice for the same work: never charge for both capability and outcome on the same audience and the same intervention. Pick one, per cohort, and say which.

At which point the real objection arrives, and it is always the same sentence: nobody on my team can build forty of these a month. Correct. And it is not a talent problem or a budget problem — it is the same arithmetic problem from section four, with the same answer. Roughly sixty to seventy per cent of use cases sit at L0 to L2: calculators, quizzes, polls, capture. No integration, nothing calling your servers, nothing for compliance to review, live in twenty-four to forty-eight hours. L3 and L4 are the handful of moments that touch money, on your own rails with secure token exchange and a graceful fallback underneath. The volume comes from agents composing against context and the brand wiki, with humans approving and holding the veto. The reason most brands stop after one clever email is not that the second one is harder. It is that nobody can make the fortieth by hand.

Four unglamorous things sit underneath all of it, and they are the multiplier on every number above. Land in the primary inbox, because everything downstream is a fraction of what arrives somewhere a person might see it. Count people rather than machines, because privacy proxies and security scanners have made the raw open rate close to fiction. Assemble at open, not at send. And degrade gracefully — not every client renders an interactive message, so every one of these needs an ordinary version underneath, and nobody ever sees something broken. Deliverability is not a feature. It is the multiplier.

For twenty-five years an email could do one thing: click out. The change is not that it got prettier. It is that the message is now composed at the moment it is read.

Context is the moat — and you pay twice

 Here is the objection that ought to follow, and it is the right one. If agents are what changed, then everybody gets agents. The models are the same models, available to your competitor on the same terms, at the same price, next quarter. Whatever advantage you buy on Monday is commodity by the following Monday.

That objection is correct, and conceding it fully is what makes the rest of the argument work. Intelligence is becoming a commodity, and commodities do not differentiate. Anyone selling you an agent as a moat is selling you a rental agreement.

What is not rented is the context. Only you have this customer’s history — what they bought, what they returned, what they browsed and abandoned, which of your messages they opened at seven in the evening and which they have ignored for four months. It deepens every single day. It cannot be bought at any price, only accumulated. And it is the input the model needs to be worth anything on your particular business.

Which produces the sentence to take away from this section: two brands with identical agents will not get identical results. The one that knows the customer wins. Same models, same prompts, same vendor — different outcomes, because the models are answering questions about different people with different amounts of knowledge behind them.

Now the turn, and it is the reason this edition exists. Context is not bought — it is accumulated, one interaction at a time — and it accumulates only on surfaces where the interaction belongs to you.

Before the comparison, a fair word about the rented surfaces, because the argument is stronger without a caricature. Google finds demand you could not have found. Meta reaches a consumer whose attention you have already lost. Marketplaces create discovery and convenience at a scale you will never build. None of these channels is bad, and none of them should be abandoned. The claim is narrower and harder to argue with: their economics are different, and the difference is not only the fee.

The same transaction, two surfaces. Only one of them leaves you anything to compound.

A rented surface returns a transaction. The platform saw the behaviour, not you. You get the sale and none of the memory. Which means next time costs exactly what last time cost, and the time after that costs more, because the auction inflates. An owned surface returns a customer. Every open, every tap, every configuration and every silence is yours, recorded as a fact attached to a person, consented and governed. The record compounds. Next time costs less and works better.

So the sentence that has anchored this doctrine needs upgrading. Never Pay Twice was always a pricing claim: do not buy the same customer from a platform you already sold to. It is more than that. You pay twice — once in margin, and once in memory. Adtech takes roughly a third of the transaction and keeps what it learned. Meta knows what happened on Meta. You do not. So the next recovery costs you exactly what the last one did, forever, because you never got to learn anything from paying for the first.

That reframes the tax ladder. It has always measured what each route to a transaction costs you. It also measures what each route leaves you with.

Route to the transaction	Tax (cost as % of revenue)	What you keep
Organic · direct	~0–5%	The transaction, the identity and the full record
Owned CRM	~5–10%	Offer tax only — every interaction recorded
Recovery, pre-adtech	~17%	Half the adtech tax, and the context is retained
Adtech	~33%	The sale. The memory stays with the platform
Intermediated · marketplace	~35–40%	Often not even the identity — and no context at all

Read down that third column and the strategy writes itself. The job is to move transactions down the ladder toward the cheapest proven route, and to spend adtech last — for what nothing cheaper could reach. But the second reason is the one that compounds: every transaction you move down the ladder does not just cost less this quarter, it makes the next one cheaper by leaving you something to learn from.

The two arguments, joined. Agents lift the arithmetic that kept the plays from being run. Context is what stops agents from being a commodity. And context compounds only on ground you own — which is why the owned-channel argument stops being about postage and starts being about the only asset in marketing that appreciates.

You pay twice. Once in margin. Once in memory.

Your job moves up.

 Not out. Up. This distinction matters more than any other sentence in the essay, because it is the one every marketer is privately testing while they read the rest.

The judgement stays exactly where it has always been — with the people accountable for the number. What moves is the execution of the instances.

The line between what a human decides and what an agent runs. Four of these five human items are things no model can decide for you.

Humans own the outcome: which number you are accountable for this year, what a good offer is and what it costs the business, what the brand sounds like, which trade-offs are acceptable, and — the item nobody should ever delegate — what must never be sent and when to stop. Agents own the instances: which of the six plays this particular customer needs, on the channel they still respond to, at the moment they are paying attention, with content assembled for them, ten million times over, every single day.

Underneath that line the architecture is simpler than the vocabulary suggests. There is an orchestrator — a unified co-marketer that you brief and that executes nothing itself; its job is to hold the team, call whichever specialists a task needs, sequence them and hand the result back. There is a decisioning engine, which is not an agent but the thing every agent calls: it scores the next best move for each individual, in real time, against the goal you set.

And there are the specialists. An insights agent that reads every campaign and reports what performed and why. An audience agent that builds and refreshes the segments worth targeting — and refreshes them, which is the part humans never get to. A content agent that drafts from master content, on brand, for hundreds of micro-segments rather than ten. A scheduler that delivers to each person at their moment on their channel. A shopping agent that carries a customer from discovery to checkout. And, increasingly, custom agents a brand builds itself for the jobs only its business has.

One agent decision deserves special mention because it is the one humans almost never make: suppression. Should this customer be left alone entirely, because she is already likely to transact without any intervention at all? A marketing team measured on sends will never choose that. A system measured on incremental profit will choose it constantly, and the saving is real.

Judgement enters at the top. Everything below it is execution — and everything comes back as memory.

None of this works without memory. The context layer has to remember what was sent, what was rejected, what a human overruled and what happened next — the decision traces. Those traces are what make an agent’s choice explainable after the fact: why this offer, to this person, on this channel, and what the outcome was. And explainability is not a compliance nicety. It is the precondition for autonomy. A system whose reasoning cannot be inspected does not get to be trusted with more, and should not be.

Which is why autonomy should be earned in rungs rather than granted in one decision: advisor first, then co-pilot, then semi-autonomous within tight guardrails, then autonomous only where the outcomes have been measured long enough to justify it. Start with a cohort. Keep a holdout. Widen what the agents may decide as the evidence accumulates, and not before.

There is a corollary for vendors, and it is uncomfortable for most of them. If a platform is confident enough to make these decisions on a brand’s behalf, it should be confident enough to be measured on the result. The honest version of the agentic pitch is not another agent to buy. It is a willingness to move from vendor to owner — to take on the KPI, within agreed parameters, and to link part of the compensation to the outcome. Everything else is a demonstration.

The last era of martech gave marketers more software. The next era takes work away from them.

Nothing here is hard. There is just too much of it

 The answer is not talent, and it is not effort, and it is not budget. It is arithmetic — and arithmetic is the one thing that has changed.

Take a play. Any of the six. Executed properly, it is one decision, for one person, on one channel, at one moment. Now multiply that out across a real business.

Nine cells on the grid, ten million customers, six plays, five owned channels, three hundred and sixty-five days.

Billions of individual decisions a year is what the grid demands if every customer is to get the right play on the right channel at the right moment. A very good marketing team, working hard, makes a few hundred campaign decisions a year — each one briefed, argued over, approved, shipped, and made brilliantly by people who are excellent at their jobs. The distance between those two numbers is not a performance gap. It is a category error.

This also explains something that has puzzled the industry for a decade: why retention has consistently underperformed its own business case. The answer is an asymmetry in how the two halves of marketing got automated.

The same marketer, the same budget, two completely different amounts of work per decision.

Hand a budget to Google or Meta and the system does the work. Targeting, bidding, creative rotation, frequency management — all automatic, running overnight, at any scale, without a brief. The effort per decision is close to zero. Now look at the other side. Every segment needs analysis, then content, then a campaign build. Every send needs a brief, an approval and a report. The effort per decision is a person for most of a day. So ten segments get built once and left in place for months, because eleven would cost another person.

Put those side by side and the last decade explains itself. Martech got hard, so it did not get done, and the money went back to the channel that made it easy. Not because anyone believed adtech was better. Because adtech was the only one that could absorb the volume.

There is a second consequence, and it is the one worth sitting with. The campaign itself was never a strategy. It was a workaround.

Nobody ever chose to talk to a segment. We invented the segment because talking to a person, one at a time, at scale, was impossible to afford. One team, millions of people — so we grouped people who are not alike, sent the average to all of them, and called the compromise a strategy. A segment is a compression algorithm. It was the right answer to a real limit.

The limit has lifted. Per-person is now affordable. Per-moment is now possible. Per-channel is now automatic. The constraint that created the campaign is gone, and the campaign is the only thing still standing on top of it.

What replaces it is not a better campaign calendar. It is a different operating model, and the differences are worth setting out line by line, because every row is a place where a habit has to be given up.

	Human-operated martech	Agentic martech
The base	Millions of customers	Millions of customers
Grouping	Humans build a handful of segments	Machines evaluate individuals continuously
Rhythm	A campaign calendar	Continuous decisioning
Content	Built once, per campaign	Assembled per customer, per context
Channel	Chosen by the programme	Chosen by expected outcome
Humans	Operate every step	Set goals, guardrails and exceptions
The metric	Optimise activity	Optimise movement between customer states

Read the last row twice. It is the one that changes what gets reported upward. Activity metrics tell you the engine was busy. Movement between states tells you whether the base got healthier — which is the only thing the P&L eventually responds to.

Every objection to owned-channel retention for the last ten years — it is too manual, it does not scale, we cannot resource it — was correct. That is why it deserves a straight answer rather than an argument. The constraint was real. It is the constraint that has changed, not the conviction.

The gap was never talent. It is arithmetic — and arithmetic is the one thing that has changed.