Your number
So what does that number mean?
Five bands. Most established businesses land between 25 and 55. Nobody hits 100.
Bands are interpretive. The formula itself is published below.
The fixes
Six ways you are losing ground, and what each one costs.
This applies to any business that sells in more than one place. Several locations, several metros, several categories, or a product line carried by other people's stores. If your market is a map rather than a single storefront, you have cells.
A cell is one product category in one local market. A single line in a single metro. A format in one trade area.
Most businesses are not one market and one ranking. They are several hundred of these, and almost all of them are invisible in a channel report, because a channel report is organized around the seller's departments rather than the buyer's geography.
Share of Map scores every cell a company depends on, weights each one by demand and strategic value, then rolls them up into a single figure. A cell can be lost for six different reasons. Each has a different fix, a different cost and a different payback.
Hover the field to inspect a lost cell, or a row below to isolate its failure mode. Illustrative distribution.
The six ways a cell is lost
The load-bearing decision
Retention multiplies. It does not average.
A company can win every map in its footprint and still leak the customers it wins. Averaging retention into the other three pillars lets strong visibility hide that. Multiplying makes the number tell the truth.
If you do not keep them, you do not own the map. You rent it.
The real number
Sliders are a guess. Get it measured.
We score every cell your business depends on using your own analytics, search console, point of sale and CRM, joined to live search and competitor data. You get the number, the six failure modes ranked by what they cost you, and the arithmetic behind all of it.
- Your real 0 to 100 score, per market and per category
- Which of the six failures is costing you most
- What returning retention to benchmark is worth in points
- No obligation, and the method is public either way
Send us the estimate and we will score it properly.
Request a scored map →Opens Heady's contact form with your score attached, so the conversation starts from your numbers instead of a blank page.
Below this line
The methodology, in full.
Everything above runs on the arithmetic below. It is published rather than licensed, so you can check it, argue with it, or run it yourself without us.
The formula
Position, multiplied by whether you keep it.
Two different kinds of measurement. Position is a share of a finite surface, observed from outside. Retention is a rate, drawn from a company's own data. Keeping them structurally separate is what stops the number becoming an average of unlike things.
Position score
+ 35% long-tail share
+ 25% capture rate
Retention factor
÷ category benchmark
capped 0.50 – 1.25
Effective share of map
per company,
capped at 100
Composition
Four pillars.
Three of them describe position. The fourth describes whether position is kept. The weights are published so the arithmetic can be checked.
Grid share
Not one rank. Share of the visible slots across a geographic grid, on every surface that behaves like a map in the category: the local map pack, plus the marketplaces and directories buyers actually browse. For companies that sell through others, this is presence across the listings that carry them, multiplied by position within those listings.
Long-tail share
The laborious pillar most measurement skips. Rather than contest head terms, score the full category query universe by market, plus brand and product searches, plus citations in AI answers to questions of the form “where do I buy X in Y.”
Capture rate
A jump ball is demand nobody owns yet: an open cell, a competitor delisting, a new category arriving, a demand spike. Capture rate is the share of detected opportunities where a company reached the top three in that cell within 45 days. It converts speed from a claim into a scored outcome.
Retention factor
Repeat rate divided by benchmark, capped between 0.50 and 1.25 so a single soft quarter cannot zero out a score and a standout is rewarded without running away with it. Repeat purchase is structurally low in some categories and high in others, so the comparison has to be relative to a benchmark rather than to 100%, otherwise every company looks broken.
Worked example
Run it against your own numbers.
The point of a published formula is that someone can run it against their own numbers and argue with the result. Here it is with illustrative ones.
| Pillar | Weight | Score | Weighted |
|---|---|---|---|
| Grid share | 40% | 38 | 15.2 |
| Long-tail share | 35% | 24 | 8.4 |
| Capture rate | 25% | 61 | 15.3 |
| Position Score | 38.9 | ||
| Retention factor | × | 22% ÷ 26% | × 0.85 |
| Effective Share of Map | 33 |
This company holds 39 of the position available to it, but keeps customers at 85% of the market rate, so its effective Share of Map is 33. Returning retention to benchmark is worth +6 points with no new visibility work at all.
That is the whole argument for the multiplier. The cheapest six points on the board are the ones the company has already paid to acquire.
Objections
Arguments with the metric.
A metric only becomes a standard if the people it measures can check the arithmetic and contest the choices. Here are the choices worth contesting.
Why are the weights 40, 35 and 25?
Because that is the order in which the three failures cost money. Grid share is weighted heaviest because absence from the visible surface is unrecoverable: no amount of downstream work rescues a cell you are not in. Long-tail share is second because it is the largest addressable surface and the one most companies have not seriously tried to hold. Capture rate is third because it measures speed rather than position, and speed only compounds once the first two are real.
The weights are published so they can be disagreed with. If you re-weight, publish the weights you used.
Why is the retention factor capped between 0.50 and 1.25?
To stop one quarter from deciding the score. Uncapped, a company with a broken measurement period zeroes out real position it took years to build, and a company with an unusually loyal cohort posts a number that visibility work did not earn.
The cap keeps retention decisive without letting it become the only thing the metric reports. A company sitting at either cap should be reading the raw ratio, not the score.
Why 45 days for capture rate?
Because that is roughly the point at which an open cell stops being an opportunity and becomes someone else's position. Shorter than that and you are measuring luck and crawl timing. Longer and you are measuring whether the company eventually got around to it, which every company eventually does.
Why not just track rank?
Rank is one position, on one surface, for one query. It cannot tell you what share of a market you hold. It does not see the marketplaces and directories buyers actually browse. And it has no access to what happens after the click.
A rank tracker cannot report churn. Share of Map is built to report it.
Why score per cell instead of per channel?
Channel reporting is organized around the seller's departments. Buyers are organized around geography and category. A channel report can show organic up and paid down while a company is quietly losing every cell in its second-largest metro, because no line in that report is shaped like a metro.
Cells are shaped like demand.
What exactly is a cell?
One product category in one local market. A single line in a single metro. A format in one trade area. A company with six locations across three metros and twelve categories has roughly a thousand of them.
Can a company score 100?
In practice, no. A score of 100 requires holding every visible slot on every surface in every cell and winning every open opportunity within 45 days.
100 is also a hard ceiling. Because position is already a share of a finite surface, a retention factor above benchmark closes the distance to the ceiling faster but cannot push a company past it. A company whose position and retention both sit at the top of the scale should be reading the raw ratio, not the score.
The number is useful as a ceiling to measure distance from, not a target to reach. Most established operators sit well below it.
Who maintains Share of Map?
Share of Map was developed by Heady and is published rather than licensed. Version 1 is dated 2026. Changes to the weights or the cap are versioned rather than applied silently, so a score from version 1 remains a score from version 1.
Inputs & citation
What it runs on.
Connected first-party data: analytics, search console, point of sale and CRM, combined with external search and competitive data across the markets that matter. That combination is what lets the score see churn, which no rank tracker can, because rank trackers have no access to what happens after the click.
The methodology is published rather than proprietary. A metric only becomes a standard if the people it measures can check the arithmetic.
Cite this
Share of Map (v1, 2026)
Effective Share of Map =
min(100,
(0.40 x grid share + 0.35 x long-tail share + 0.25 x capture rate)
x clamp(repeat rate / category benchmark, 0.50, 1.25))
Result is capped at 100. Scored per cell, where one cell is
one product category in one local market.
Developed by Heady. https://shareofmap.com
Machine readable: formula.json · llms.txt