The 3 Us: Users, Usage, + Uses
Because we've usually only maximized 1 of these 3 growth levers
Hey friends - it’s Sam + welcome back for your regular Saturday edition of Marketing Meditations where I dig into a marketing observation, idea, or lesson I encountered recently.
Today is a special edition as it’s the first official “guest post” on here + it’s one I’m incredibly proud of as it’s coming from Elie Daccache, a member of my team at Loxo. Funny enough, it was through this very newsletter a couple of years ago that Elie + I started emailing back and forth each week, him sharing his thoughts about the newsletter with me + helping to sharpen the things I was learning.
Elie has one of the most insatiable growth mindsets I’ve ever encountered, so when he asked me a few weeks ago if I’d be open to having him collab on a newsletter here, the answer was an immediate yes. What follows is something he’s recently learned from a mentor of his when it comes to finding new growth levers, even when you think you’ve tapped out what’s at your disposal.
So without further ado, I’ll let Elie take it from here…
My mentor, the general manager of a $300m fast-moving consumer goods division at Fattal, one of the largest distributors in the Levant, spent a week sitting in the living rooms of strangers, watching women clean their houses. He didn’t need to. He had analysts, panel data and a market-research budget most chief marketing officers would envy. He chose instead to spend a week on the sofas of married, stay-at-home women across several regions of Lebanon, notebook in hand, watching them wipe floors and scrub sinks. By the end of the week he had the insight that would grow one of his brands sevenfold in two years, and it came from noticing something no dataset had thought to record: the woman in front of him already owned a product that could clean her entire house, and had bought half a dozen others to do jobs it already did.
That one observation contains the whole argument, so it’s worth seeing how he got there.
The problem nobody prepares you for
Most of us spend our careers trying to win a market. My mentor inherited the opposite problem. The portfolio handed to him was made up of brands that had already won, several sitting at around 88% market share and one higher still. At that altitude the familiar playbook stops working, because there’s little meaningful share left to take from competitors who have almost none, and no obvious way to enlarge a number that’s already pressed against its ceiling. So he faced two difficulties at once: preserving the extraordinary share he’d inherited, and still growing sales in markets everyone around him considered saturated.
If you run B2B software marketing, you know this one in your bones, even if the products couldn’t be more different. It’s the plateau. The obvious ideal-customer profile has been worked through, pipeline flattens, and sooner or later someone says the market’s been saturated and the room accepts it as a fact of nature.
That conclusion is almost always premature, and the reason is the framework my mentor built to escape it, which he called the 3 Us. His premise was that market share isn’t a single number but the product of three separate levers, and that a business convinced it has run out of room has usually exhausted one of them while leaving the other two untouched. The first is Users, meaning how many people use the product. The second is Usage, meaning how often they use it. The third is Uses, meaning how many different jobs they use it for. Each brand in his portfolio happened to be stuck on a different lever, which makes them an unusually clean way to watch all three at work, and each one translates with surprising directness into a growth motion you can run in software.
How he grew Dettol’s sales 7x in 2 years
Back to the living room. In the Middle East at the time, Dettol carried a reputation problem disguised as a strength. Everyone knew the brand, and everyone knew it for exactly one thing: it was the disinfectant you used to clean a bathroom. It also sold at roughly four times the price of the nearest detergent competitor, which made it premium, respected and thoroughly boxed in. A product understood to have a single job can only be bought for that job, and its ceiling gets set accordingly.
Rather than commission a repositioning campaign from behind his desk, my mentor borrowed the method of “Blue Ocean Strategy” and went looking for the uncontested space himself. He set up an observational study of the core audience, the married women who ran these households, and embedded with them for a week to watch how the cleaning actually happened.
And what he saw resolved the whole problem. The women used Dettol for the bathroom, and only for the bathroom, exactly as its reputation dictated. For every other surface in the house, the floors, the sinks, the fixtures and the wood, they reached for a different bottle, and had accumulated half a dozen of them under the counter. Yet the contents of those bottles were, chemically, almost identical to the Dettol already sitting in the cupboard. What separated one product from the next wasn’t the formula but the degree of dilution. The customer was buying five extra products to do jobs the one she already owned could handle, had anyone bothered to tell her the right dilution for each.
That’s the lever he called Uses, and it relocates where growth actually comes from. The additional sales weren’t waiting in a new customer or a new product but in the unused capacity of the product already on the shelf. Two questions fall out of it, and both are worth keeping. How many more ways can the same customer use the product? And what different customer might use the very same product for an entirely different job?
So Dettol got un-boxed. From the bathroom disinfectant it became a multi-surface, multi-room product suitable for floors, walls and fixtures, and even for the kind of hygiene prep appropriate to an operating room. The molecule didn’t change; the number of jobs it was sold for did. Sales grew sevenfold within two years. Der General, another brand in the portfolio run on the same logic, tripled.
Uses have a metabolism
Then he did something most brand marketers wouldn’t have bothered with, and it’s the part that turns a tidy anecdote into a forecasting method. A new use doesn’t merely add a reason to buy; it adds a rate of consumption. During the same study his team logged how often the women cleaned each part of the house, broken down by region and by age group, and how much product each job consumed. A bathroom cleaned twice a week at three bottle-caps a time accounted for six caps weekly; floors cleaned three times a week at a single cap each accounted for three more. Sum that across every use a given segment had adopted, and you could see how quickly a household would empty a bottle and therefore when it would need to buy the next one. Purchasing frequency, segment by segment, derived from what people actually did rather than guessed from a trend line.
This is the muscle B2B technology is about to need. Software has long been forecast on the basis of seats, which are convenient because a seat is a headcount that renews on a predictable annual cycle. The industry is now moving fast toward usage and consumption-based pricing, and AI products in particular tend not to bill by the seat at all but by the token, the run, the workflow or the outcome. In that world per-seat forecasting doesn’t merely lose accuracy; it stops describing the business. What replaces it is exactly what he built with a notebook on a stranger’s sofa: a bottom-up model of consumption that asks how many distinct jobs a segment runs the product for, how heavy each job is, and how often it recurs. Answer those questions and you get more than a cleaner lifetime value. You get timing, an estimate of when a given account will hit its next genuine need, which is the single most useful input a retargeting or expansion campaign can have, because it lets you show up the moment the bottle runs dry instead of broadcasting to the whole list at once. In a consumption-priced market that bottom-up plan, built from the 3 Us and plain old qualitative research, becomes the forecast itself rather than a supplement to it.
There’s a more immediate reason the Uses lever matters to a marketer, which is that every new use is a fresh universe of demand. While Dettol stayed the bathroom disinfectant it competed for a single cluster of intent, one set of keywords and queries and one position on the shelf. The moment it became a floor cleaner, a wood-surface cleaner and an operating-room prep, each of those uses brought its own keywords, its own search volume, its own audiences, its own ad sets and its own content. A new use adds a whole addressable surface to go compete for. So when paid search plateaus and the keyword list feels tapped out, the more productive question usually isn’t how to bid harder on the terms you already have but which use of the product you’ve never actually advertised.
Because each unadvertised use is untapped volume sitting in plain sight.
The Durex problem: nowhere to go but usage
Durex presented the opposite constraint. It held 88% of its market, which left essentially no room on the Users lever, since a number that high can’t absorb many new customers. Nor could the brand plausibly invent a portfolio of new Uses, there being only so many jobs a condom can be sold for. Unless you’re a little creative, of course.
Two of the three levers were, for all practical purposes, pinned in place, which left Usage: getting existing users to use the product more often.
The complication was that he was working in a devout Lebanese market where sex is taboo, hardly a subject a brand can address with a straightforward instruction to buy more. So growth took the form of education and awareness aimed largely at younger people, normalising the conversation and funding the kind of advertising that raises the frequency of the behaviour the product depends on, without ever being able to fall back on the blunt commercial message a less sensitive category would use.
The parallel in software is the lever most teams under-invest in, because raising usage is less glamorous than winning new logos. When the Users count is saturated and no new Uses are available, growth has to come from frequency: activation, feature adoption, the formation of habits and the depth of the relationship with the accounts already signed. Under consumption pricing this isn’t a soft metric but the revenue itself, since more usage of the same use by the same users flows straight into the bill. Durex could add neither users nor uses and so competed entirely on frequency; plenty of software companies could grow substantially without signing a single new customer if they did the same.
The OMO problem, solved in a supermarket aisle
The third lever produced the story where the general manager left the building most literally. In late 2019 Lebanon suffered the sharpest economic collapse in its history. The currency fell apart and government-subsidised consumer goods flooded the shelves, which for a portfolio of premium brands was close to an extinction event, as subsidies and acute price sensitivity commoditised the category and set off a race to the bottom. Among his brands the weakest position belonged to OMO, a laundry detergent owned by Unilever, hovering at around 2% market share.
The move available from the desk was to cut price, protect margin and concede the year. My mentor drove to the supermarkets instead. The general manager of a $300m division went from shop to shop across the country to see for himself what was happening at the shelf, and in every location he found the same scene: crowds gathered around the subsidised goods, each of which wore a bright red-and-yellow sticker reading مَدْعُوم, Arabic for “subsidised”. Shoppers weren’t comparing brands or reading labels; they were navigating by the sticker, which had become the most valuable piece of shelf real estate in the country. He would have never realized this had he not stood right in the aisle.
There was the play. He talked the executive team and the board into giving him a budget to subsidise OMO with Fattal’s own money, undercutting the government’s price and putting the brand in the same discount conversation, and then printed the very same red-and-yellow sticker the subsidised goods carried, adding beneath it the words “subsidised by Fattal”. He borrowed the visual cue shoppers had already been trained to trust and pointed it at his own struggling brand. The forecast tells you how little anyone expected of OMO: even assuming the experiment worked, the plan was to sell ten shipping containers of product across the entire year. They sold out in a week, roughly fifty-two times the annual forecast in seven days.
Several lessons sit inside that result, each with a direct analogue in technology. The first is to go down to the market yourself no matter how senior you are, because a $300m general manager standing in an aisle saw what no report would have surfaced; a report averages away the very detail that mattered, and the most reliable market research is still the kind you do with your own eyes at the moment of purchase. The second is that shelf space is itself a touchpoint rather than neutral inventory, working at once as an advertisement, a trust signal and a decision-making environment. Its digital equivalent is everything surrounding the moment a prospect decides: bottom-funnel search, whether an AI assistant recommends the product, on-page experience and navigation, all the surfaces a buyer touches while actively weighing a purchase, and most software teams leave them to chance while obsessing over the top of the funnel. The third is that shelf share correlates with market share, since the more effortlessly available a product is at the point of decision, the more it sells, which for software means earning presence on the surfaces that genuinely matter to your buyer rather than the ones a category report happens to list, or intuition assumes, or best practice recommends. The last is to borrow from markets that look nothing like your own: his edge came from lifting a government’s subsidy sticker and re-aiming it at a detergent, and the most defensible promotional ideas tend to come from outside your own category, in a mechanism that works somewhere else and can be adapted before anyone nearby thinks to.
Why the 3 Us resist automation
Seen together, the three stories share a quality that matters now in particular. None of the insights existed in a dataset. The Dettol breakthrough came from a week spent watching dilution habits on a sofa; the OMO play came from noticing which sticker a crowd gravitated toward; the Durex motion came from understanding a specific cultural taboo well enough to work around it. Each one needed primary observation and a creative leap, the act of going somewhere, watching something, and connecting two things that weren’t obviously related.
That’s the work a language model can’t do on your behalf. A model will happily generate a hundred variations of the keywords you already have, but it can’t spend a week in a stranger’s living room and come back understanding that the customer is buying five products to do one product’s job. The raw material for a new U is gathered in the field and assembled with imagination, which is the part that stays scarce precisely as everything downstream of it gets cheap to automate. The framework is defensible against AI because its inputs are.
For the same reason the 3 Us work as a brainstorming engine for marketing, not just for product development. When growth stalls, you can run the portfolio against three questions: which segments of Users have we never gone after, which Uses of the product have we never advertised, and how could we get existing users to higher Usage. Most teams, hitting a plateau, reach only for the first of these, chase more users, and conclude the market is tapped out when that lever gets stiff. My mentor’s career is a sustained argument that the ceiling you run into is rarely the market’s, and far more often the two levers you forgot you were holding. Nothing in the data said a premium brand known for a single job, in a market widely judged mature, had a sevenfold gain sitting inside it. It had been there the whole time, in the gap between what the customer bought the product for and what the product could actually do.
See you next Saturday,
Sam
Amazing insights , thank you!