Down the Whole Tree
Get the market broken into three layers — the total market, the slice you can serve, and the share you can realistically win — each a number, not a hand-wave.
Get a market size you can defend — TAM, SAM, and SOM with a source behind every number and a model you can open.
Below, in order: how deep the crawl goes, what shape it returns in, how you narrow it, which stores it works on, what you can do with the file, and what a second sweep adds.
Get the market broken into three layers — the total market, the slice you can serve, and the share you can realistically win — each a number, not a hand-wave.
AllyHub sizes it both ways — segmenting an industry total from the top and building up from price times customers — so the two methods cross-check instead of resting on one guess.
Each figure carries a clickable source and the steps that produced it, so a skeptical reader can trace the number back to where it came from rather than taking it on faith.
Move an input — adoption rate, price, addressable population — and the whole model updates, so you can pressure-test the size instead of defending a single fixed figure.
Point it at the authorities you trust — a statistics bureau, an industry association, a public company's filings — and it pulls the inputs from there, not from whatever a model half-remembers.
Take it as a working .xlsx where every assumption is a cell you can change — hand it to an investor and they can audit the math, not just read a number.
One category link becomes a full-tree product dataset in three steps.
Tell AllyHub the product and the market you're sizing, and name the data sources you want it to rely on if you have preferences.
It builds TAM, SAM, and SOM top-down and bottom-up, pulls each input from your sources, cites every figure, and lays it out as an editable model.
Flex the assumptions, check the two methods against each other, and export the model. Save the setup as a Recipe so your next sizing starts from your method.
Where competing category scrapers stop, and what stopping there costs you.
An AI that spits out a TAM gives you a number you can't defend; a blank calculator makes you source everything yourself. AllyHub does the research and keeps the receipts, so every figure has a link a reviewer can open.
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Static calculators multiply inputs you had to find; fixed datasets can't be changed. AllyHub both gathers the cited inputs and hands you a model where every assumption is yours to adjust — you don't have to pick between sourced and editable.
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A single approach hides its own errors. AllyHub runs top-down and bottom-up side by side, so when the two converge you have confidence, and when they diverge you know exactly where to dig.
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Save your sizing method and sources as a Recipe and the next market — or a revised estimate — skips setup. Because your AllyHub never starts from scratch again, each model costs less and lands faster than the last.
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Analysts, launch teams, buyers, and sourcing scouts who need the category whole, not sampled.
Someone asks how big this category is and you have an impression, not a number you trust. Work from the full node instead and the answer is countable — how many products, at what price tiers, with what review depth behind them.
You are about to commit a first order into a category you have only browsed. Size the field before the money moves, and read what it actually takes to get seen here rather than discovering it from a listing nobody finds.
Assortment shifts every quarter and your evidence is last quarter's screenshot. Keep dated sweeps of the same node and shelf movement becomes something you can show a supplier, not something you argue about from memory.
The gaps you find are the ones you happened to scroll past, which means the best one is probably still sitting there unseen. Read the whole node and the thin spots surface because you covered everything, not because you got lucky.
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Questions that come up when a browse node turns out bigger than it looked.
TAM is the total market for a product, SAM the portion you could serve, and SOM the share you can realistically capture — three narrowing layers. A market sizing tool works out all three; AllyHub does it with a source behind each figure.
Yes — a single sizing is free. Deeper research across authoritative sources, sensitivity models, and saved sizing Recipes are covered by paid plans.
Both — they catch different errors. Top-down segments a published industry total; bottom-up multiplies price by customers. AllyHub runs the two together so they cross-check, which is exactly what a careful reviewer looks for.
Every input traces to a source you can open. AllyHub pulls from the authorities you name — statistics bureaus, industry bodies, public filings — and tags each figure with its citation and the steps that produced it, so no number sits in the model unexplained.
Investors often want a TAM large enough to matter and a SOM that's a credible slice of the SAM — but the size that convinces isn't the biggest one, it's the one you can source and defend. AllyHub's job is the defensibility, not inflating the figure.
It researches the inputs and cites them, sizes top-down and bottom-up, and hands you an editable model instead of a locked number — and, saved as a Recipe, it gets faster every time, so the next estimate is quicker than the last.