The last piece in this series derived a floor. In a market with zero cost, perfect fit and equal numbers on both sides, 36.79% of possible matches still fail. Every supplier in that model was identical, which is what made the arithmetic clean. It is also the one assumption a brand exists to break. Break it, and the same equation says a supplier holding 5% of a market's attention ends a period with nobody 62 times less often than a supplier holding a fair share. Procter and Gamble put $9.2 billion into advertising last year to hold positions like that. What follows is which part of that money buys something unavailable by any other route, and which part is lying in the open.

Start with the question most people actually ask, because it turns out to have a testable answer. When a very large brand wins, is it winning because the product is better?

The assumption the last piece made on purpose.

The urn-ball model (a hundred balls thrown into a hundred buckets, counting how many buckets stay empty) assumes every ball is thrown at random. No bucket is more attractive than any other. That assumption is doing enormous work. It is what produces 1 over e, and it describes a market in which no supplier has any prior claim on anyone's attention.

Real buyers do not throw at random. They throw at what they can already name.

So replace the uniform throw with a weighted one. Each supplier now carries a probability of being chosen, call it p, its share of consideration (the chance that a given buyer, at the moment of choosing, thinks of you at all). A supplier with no reputation holds whatever a fair split gives them, 1 divided by the number of suppliers. A brand holds more. Everything in this piece falls out of that one substitution.

The chance a supplier finishes a period with nobody becomes (1 minus p), raised to the power of the number of buyers.

That is the entire model. One line.

What share of consideration actually buys.

Put a hundred buyers into a market against a hundred suppliers, hold everything else identical, and vary only p.

At a fair share of 1%, a supplier gets nobody 36.60% of the time, which is the floor from the last piece arriving on schedule. At 2%, that falls to 13.26%. At 5%, it falls to 0.59%. At 10%, it is indistinguishable from zero.

Read those twice. Five times the share of consideration does not produce five times the result. It produces sixty-two times fewer failures. The returns are superlinear (the output rises faster than the input that produced it), and that single property explains why the spending looks irrational from outside and is perfectly rational from inside.

A big brand does not take its share. It takes the tail.

Now watch what the same arithmetic does to everybody else. Let one brand hold a share w, and let the remaining ninety-nine split whatever is left.

When the big brand holds 1%, everyone fails 36.60% of the time and nobody has an advantage. When it holds 10%, its own failure rate is 0.003% and the others have moved to 40.12%. When it holds 40%, its failure rate is effectively zero and the others sit at 54.45%.

The big brand's position improves by very nearly everything available. Each individual small supplier is worse off by about eighteen points. The prize is concentrated in one place and the damage is spread thinly across ninety-nine, which is precisely why nothing ever organises against it. This is the congestion externality from the last piece wearing different clothes. The extra share is not stuck in the jam. It is the jam, for everybody behind it.

How much is actually enough.

Here is the part that makes this a workable problem rather than a complaint.

You do not need a large brand's share. You need enough to clear a threshold, and the threshold has a closed form. Set the failure rate to a coin flip, solve, and the required multiple of a fair share comes out as the natural logarithm of 2, multiplied by the number of suppliers per buyer.

In a market with one supplier per live buyer, you need 0.7 times a fair share. You are already past it. At five suppliers per buyer, the crowded case from the last piece where 81.87% of suppliers end up empty, you need 3.5 times a fair share. At ten per buyer, 6.9 times.

Three and a half times. Not four hundred times. In the crowded market the last piece spent seven thousand words describing, the distance between invisible and a coin flip is a factor of three and a half in one variable.

That number is the reason this piece exists.

So is it the product, or is it the fame?

Everything above is arithmetic. Arithmetic can tell you that a difference in share of consideration produces a violent difference in outcome. It cannot tell you where that difference came from. If large brands hold attention because their products are genuinely better, the advice is simple and boring: make a better product.

Marketing science has been testing exactly that question for sixty years, and the answer is not the flattering one.

The finding is called double jeopardy (the observation that a smaller brand is punished twice, once for having fewer buyers and again because those buyers are also slightly less loyal). William McPhee described the pattern in 1963, Andrew Ehrenberg found that it generalised to brand purchasing, and Ehrenberg, Goodhardt and Barwise formalised it in 1990. It holds, with few exceptions, across a very wide range of categories, countries and time periods.

The load-bearing part is what it implies. If product quality were driving brand advantage, loyalty would vary independently of size. A small, excellent brand would show low penetration and high loyalty. That combination is rare to the point of being an anomaly. Loyalty tracks size. The Ehrenberg-Bass Institute states the consequence plainly: growth comes from acquiring category buyers rather than from holding on to the ones you have, and acquisition is roughly twice as important as reduced defection.

Which means large brands do not look more loved because they did something clever about being loved. They look more loved because they are large.

There is a second reason to treat this as structure rather than opinion. The model underneath double jeopardy is the NBD-Dirichlet (Goodhardt, Ehrenberg and Chatfield, 1984), which predicts a brand's performance measures from its market share alone. NBD stands for negative binomial distribution, which is a Poisson process with the rate allowed to vary from person to person. The last piece derived its floor from a Poisson process. This is not a framework borrowed from a neighbouring field. It is the next term in the same equation.

What the largest brand in the category actually spends.

It is worth being exact here, because the folk version of this story is wrong in a way that will lose you the room.

Procter and Gamble's annual report for the year ended 30 June 2025 states it directly. Advertising costs, charged to expense as incurred, include television, print, radio, digital and in-store advertising expenses, and were $9.2 billion in 2025, $9.6 billion in 2024 and $8.0 billion in 2023.

Against roughly $84.3 billion in revenue, that is 10.9%. The filing is explicit that consumer promotions, product sampling and aids sit outside that figure, on top of it.

For comparison, the most recent CMO Survey puts marketing budgets at 9.0% of revenues, and that number covers the entire marketing budget rather than advertising alone.

So the large brand is not quietly spending less. On the single line that buys share of consideration, it spends more than the average company spends on everything. Anybody planning to argue that the giants win through restraint should stop here.

What they do differently is not the amount. It is the timing, and the target.

The $200 million that went missing, and the 10% that appeared.

In 2017, Procter and Gamble removed roughly $200 million from its digital advertising, about $100 million in the quarter to June and another $100 million through December. The first tranche, by the company's own account, had little appreciable impact on the business. The reduction was reported to have increased the company's reach by 10%.

They spent less and were seen by more people.

One measurement from that review explains it. The average dwell time on an advertisement in a mobile newsfeed was 1.7 seconds.

The money had been going into precision. Narrower targeting, more intermediaries, more measurement of an event lasting under two seconds. Removing the precision did not remove the presence. It removed the tax on the presence.

This is the single most useful thing in this piece for anybody without a budget, because it is an experiment run at nine-figure scale on the question you cannot afford to test yourself: which half of the spending was carrying the value? The answer was the cheap half. Broad, unglamorous presence carried it. The expensive apparatus in front of it came out without loss.

Reach, retrieval and fit.

Share of consideration is not one thing, and taking it apart is where a small supplier finds a lever. It separates into three factors that multiply together.

Reach is the fraction of buying situations you are present in at all. Bought, with money, at scale. It is the nine billion dollars. Treat it as unavailable.
Retrieval is the chance you are brought to mind, or returned by a system, given that you are present. Partly bought, partly engineered.
Fit is the chance you survive the shortlist once retrieved. Almost entirely a function of whether your specifics are legible, precise and checkable. Free.

Hold reach completely fixed. Change nothing about budget or presence. Move only the last two terms, in a market running five suppliers per buyer.

A supplier at 0.2% share fails 81.86% of the time. Three times better on retrieval and fit puts it at 54.78%. Five times better puts it at 36.60%.

Same money. Same reach. From four failures in five to fewer than two in five. That is the three-and-a-half-times threshold from earlier, arrived at from the other direction, and it sits entirely on the terms that carry no price.

The ninety-five per cent they are paying for and you are not.

Now the timing, which is the real difference between the two kinds of company.

Buyers on a five-year purchase cycle are in the market for a small fraction of any given period and out of it for the rest. The Ehrenberg-Bass work behind the 95:5 rule puts it at about 5% in a given quarter. The last piece worked that as a duty cycle: an annual event plus a note to the base leaves you present for roughly 1 of the 20 quarters in which the decision actually gets made.

A large brand's advertising is not aimed at the 5% buying today. It is aimed at the 95% who are not, so that the memory is already in place when their moment arrives. It is not a purchase of demand. It is the purchase of an asset that pays out later.

The small supplier does the reverse, almost always for a defensible reason. Nothing is spent during the 95%, because nothing is happening and budget is short. Then a live opportunity appears and money goes into interrupting a buyer at the most crowded and most expensive moment there is, against everybody else who also just noticed.

That is the whole asymmetry, and it needs no numbers at all: they pre-pay, you pay at the counter, and the counter is where the price is highest.

Why a machine changes the arithmetic.

Which brings us to the one genuinely new thing, and the reason any of this is actionable rather than merely true.

Mental availability lives inside human memory, and there is no way to install yourself in a few million of those without a few billion dollars. If human recall were the only retrieval mechanism, this piece would end with a shrug and an invoice.

It is no longer the only mechanism, and the replacement has a different failure mode.

An ungrounded language model composing an answer out of what it absorbed in training is a machine that has read the internet, and the internet over-represents large brands enormously. Asked to compare suppliers using nothing but its own memory, it reproduces the fame distribution. It hands the incumbent the shortlist at no charge. Ungrounded generation amplifies the brand advantage rather than levelling it, which is the last piece's warning restated: if the evaluating model is ungrounded, it composes the comparison, with a purchase order attached.

A grounded system does something else. It queries live records at the moment of the question. It holds no memory of who is famous, no impression of who is established, no accumulated sense that one name feels safer than another. It has a query and an index. A name absent from the index does not rank low. It is simply not there.

That is the opportunity, and it is narrow and specific. Retrieval by a machine is the only channel found so far in which p is not weighted by fame. An index is built once and answered from at the moment of the question, at effectively no marginal cost. It is a small supplier's version of pre-paying, the same structural move a large brand makes with memory, executed against a system that can be written to rather than a population that has to be persuaded.

The window is open because it is early. It will not stay open, because indexes fill.

What this looks like on a $2 million budget.

Numbers on a page are easy to nod at and hard to feel, so put a real department behind them.

A marketing team with $2 million a year. Their category holds 500 credible suppliers and produces 5,000 live buying situations across the year. That is five suppliers for every live buyer, the crowded case from the last piece.

Their fair share of consideration is one in five hundred: 0.2%. That is what competence buys. Present, credible, unremarkable. Run it through the model above. Across any hundred buying situations they are absent from 81.86% of them, and five thousand situations at a 0.2% share comes out at ten a year.

Two million dollars, ten clients. $200,000 to land one.

Nothing is wrong with that department. The creative is fine, the team is good, the product does what it says on the page. That number is what the structure charges, and it was settled before anyone was briefed.

Now change one variable, and not the budget. Move retrieval and fit by a factor of five, the two terms the section above priced at almost nothing because they are specifics written down rather than media bought. Share of consideration goes from 0.2% to 1.0%. Absence across a hundred situations falls from 81.86% to 36.60%. Five thousand situations at 1.0% is fifty.

Same two million dollars. $40,000 to land one. Five times the clients, a fifth of the cost each, and the media plan never changed.

It is worth being exact about where that money is not going. Suppose the two million splits the way most of them do, with the large majority in reach, the media and the events that put you in the room, and the remainder spread across everything else. The five-fold move sits inside the remainder. It is a data pass and a discipline rather than a line item, which is precisely why it keeps not getting done. Nobody is promoted for making the specifications legible.

There is a second lever in the same budget that also costs nothing. If the two million goes out in bursts around one annual event, the department is present for 1 of the 20 quarters in which a five-year decision actually gets made. Spreading the identical money across the year buys no additional reach. It buys more of the ninety-five per cent, which is the part the large brand is already paying for.

Neither move needs a bigger budget. That is the whole point of the threshold: three and a half times a fair share, in the one variable that carries no price.

What actually moves the number.

Stop paying for precision before you have presence. The nine-figure test has already been run, and narrow targeting in front of a 1.7-second impression was the removable part.

Be present during the 95%, rather than louder during the 5%. The duty cycle is the lever, and it costs time rather than money.

Make your specifics machine-legible. Prices, stock, minimums, lead times and capabilities, in a form a system can retrieve and quote. This is the fit term, and it has no price attached.

Concentrate rather than spread. Match probability depends on density in the one place a buyer actually looks, and a flat budget across seven channels thins the reagent in all seven.

Stop trying to be recalled and start being retrievable. The first needs a budget you do not have. The second needs a decision you have not made.

None of this closes a nine-billion-dollar gap. It does not have to. The threshold was three and a half times, not four hundred.

What this all means, in plain language.

Strip the mathematics out and here is what is left.

Large companies are not winning because their products are better. If they were, their customers would also be more loyal, and sixty years of measurement says they are not. They are winning because more people can name them, and being nameable compounds. Twice as well known is not twice as good. Five times the share of attention is sixty-two times fewer empty periods.

They did not get there by being careful with money. The largest advertiser on earth puts about eleven cents of every dollar of revenue into advertising alone, while the average company spends nine cents on all of marketing put together. The story that the big ones quietly spend less is simply not true.

What they do differently is when. They spend during the long stretch when nobody is buying, so the name is already in place on the day somebody is. Everyone else spends when the order is live, at the most crowded and most expensive moment there is, against every competitor who just noticed the same thing. They pre-pay. You pay at the counter.

You cannot outspend that, and you do not have to. To reach even odds you need to be roughly three and a half times better known than an average competitor in your category. Not four hundred times. Three and a half is a target a real company can hit in a year.

And a third of it is free. Being considered is three things multiplied together: whether you are present at all, whether you are brought to mind or returned by a system, and whether you survive the shortlist once you are. Presence costs money. Surviving the shortlist costs nothing but discipline, because it is only whether your prices, stock, minimums, lead times and capabilities are written down somewhere clear, specific and checkable.

That used to be worth very little. The thing doing the retrieving was a human memory, and you cannot install yourself in a few million of those without a budget. It is worth a great deal now, because more of the retrieving is being done by a machine that looks things up rather than one that remembers. A machine that looks things up has no sense of who is famous. It reads what is in front of it. If your details are legible it can find you. If they are not, it does not rank you low. You are simply not there.

So, concretely, and in the order that matters. Stop buying precision before you have presence. Be present during the quiet stretch rather than louder during the rush. Write your specifics down where a machine can read them. Concentrate in the one place your buyer actually looks instead of thinning yourself across seven.

None of that closes a nine-billion-dollar gap. It was never nine billion. It was three and a half times, in the one variable nobody else is bidding for.

About us.

Hako Shikin LLC has been making things for other people's brands since 1997, out of Virginia Beach, Virginia. It is the brand partner for brands that cannot afford a bad headline: one house that stays accountable from the first conversation to the pallet on the dock, rather than a chain of vendors each holding a piece and none of them holding the date. Four arms do the work. Huang Goodman for public relations, strategy and program management. Hako Shikin for production, routed across more than 1,400 vetted American manufacturers. POPS4 for the catalogue, 70,000+ products across 200+ brands. Prosecco4 for events. The people who call are usually holding something that matters and a date that will not move, and what they are looking for is rarely a proposal. It is somebody who picks up, gives them the real number, and is still standing there when the truck arrives.

If you are building from what is left, you are not finished.

-Jenny Huang Goodman MPA MSc MHSA jenny@huanggoodman.com