Methodology | Rate My Ratings

We don’t sample the market. We read all of it.

Most tools hand a business back its own reviews. We read the whole market — every competitor, in the words customers already wrote after they paid. The field below is one market’s reviews. A survey only ever sees the dashed corner; you get the entire field.

Positive Neutral Critical

Illustrative — one mark = one review

Why this is different

What a local business gets here that a star average, a survey, or a consultant’s slide deck simply can’t give them.

The whole market — not just you

Most reports show a business its own reviews. We show you everyone’s.

Your scorecard tells you how you’re doing. The whole competitive field tells you where the opening is — who’s winning, on what, and where nobody has planted a flag yet. That’s the difference between a mirror and a map.

Real voice

Built from what customers already said

Thousands of reviews written after people actually paid — what they truly experienced, not what a survey panel says it might do.

Local & specific

Your category, your area

Not “small-business best practices.” The real expectations, language, and rivalries of your market — a Leeds dentist gets Leeds-dentist intelligence.

Affordable depth

Boardroom insight, corner-shop price

The kind of market intelligence national chains keep analysts on staff for — delivered to a single independent operator for the price of a report.

Ends in action

A plan, not a dashboard

Every finding narrows down to a short list of prioritised moves — what to do first, why, and how you’ll know it worked.

Four lenses on your market

The same complete market, read four ways — each lens answers one question you can act on this week.

Lens 01Experience

What your customers actually reward

Stop guessing what to fix — see what this market’s customers praise and complain about.

What you see

The things customers judge you on — wait time, billing, front desk — and how positively or negatively the whole market talks about each.
Which way the market is moving — whether customer sentiment is climbing or slipping over time, so you catch shifts early.
Widespread complaints vs one-offs — the exact phrases customers use, and how many businesses each issue hits.
The feeling behind the stars — delight, disappointment, or confusion — not just a number.

What it means for youYou spend your effort on the improvements customers actually reward — not the ones you assume matter.

What customers judge — positive / neutral / critical

Wait timen=412

Front deskn=388

Value for moneyn=506

+47Net sentiment · −100…+100

Lens 02Persona

Who you’re really serving

Know exactly who your customer is — without a research budget.

What you see

A real portrait of your typical customer — what they want, what frustrates them, and what earns their loyalty — drawn from thousands of reviews, not a workshop guess.
The questions worth asking them — and how they’d likely answer, in their own voice.
How likely they are to recommend you — grounded honestly in your market’s real ratings.

What it means for youSharper marketing, better service calls, and a shared, evidence-based idea of “our customer” the whole team can rally around.

Likelihood to recommend

8/ 10Passive

0 · DetractorPromoter · 10

Grounded in 62% 5★ · 11% 1–2★

Value-consciousTime-poorLoyal if trusted

Lens 03Benchmark

Exactly where you stand

Your true position against every competitor — not a vanity star average.

What you see

Where you sit against the whole field — hidden gem, fragile leader, or genuinely at risk.
Who’s quietly rising — great ratings, still small — before they become a threat.
Loud vs genuinely loved — review volume separated from actual quality, so reputation isn’t mistaken for size.
Who owns which strength — so you can pick a lane where there’s real room to win.

What it means for youYou compete where you can actually win, instead of chasing every rival on everything at once.

Where every competitor stands

Lens 04Strategy

A plan, not a data dump

Leave with what to do first, why, and how to measure it.

What you see

An honest read of your market — strengths to use, gaps to exploit, and threats to watch — from the operator’s seat, not a textbook.
Five prioritised moves — ranked by how much they’ll matter and how soon, each tied to the evidence behind it.
A concrete action for each — with a timeline and a measurable target, so progress is checkable.

What it means for youYou walk away with a Monday-morning to-do list you can act on and measure — not a dashboard to puzzle over.

From a complaint to a measurable fix

The market says

Slow first response to enquiries

so we prioritise

Priority 01

Compress first-response time

Impact · HighDo now

with this action

Your move

Introduce an enquiry triage rota

Target · median reply < 4h

Why you can’t get this anywhere else

How the census compares to the tools a local business usually reaches for.

What matters	The usual options	The Review Census
What you see	Your own reviews, or a star average	Every competitor in your market
Where it comes from	A survey panel or gut feel	Thousands of real customer reviews
How specific	Generic small-business advice	Your exact category and area
What it costs	A consultant’s day rate	The price of a report
What you walk away with	A dashboard to interpret	A prioritised plan to act on

The method, in detail

The census above is the what and the why. Below is exactly how each figure is produced, where it comes from, and its limits — the same language that appears in the appendix of every delivered report.

Data source

Every figure in a Rate My Ratings report comes from public reviews on Google Maps. Reviews are public, attributed to the business that received them, and presented in aggregate.

We collect reviews using established scraping tools that respect Google's public surface. We do not authenticate as a Google user, we do not collect anything that requires a login, and we do not pay for elevated API access. Every byte we read is what an unauthenticated visitor to the same Google Maps page would see.

What we include

For every business in the competitor set, we collect the following:

Business name, address, category, phone number where public, and website where listed.
Average star rating and total review count, as Google displays them.
Every public review with text, star rating (1–5), posted date, and language.
The business's reply to the review, where one was posted, with its date.

The competitor set is defined by category and a 3–5 mile radius from your postcode, with a minimum of 12 comparable businesses. The competitor list appears in full on page 03 of every report.

What we exclude

We exclude, on principle:

Reviewer personal data beyond the public attribution shown on the review (display name only — never email, phone, or any private contact).
Anything behind a login. No Google account, no authenticated profiles, no private business dashboards.
Reviews flagged or removed by Google between collection and publication, even if our snapshot pre-dates the removal.
Reviews from accounts with no other public activity and a single review on the business in question, where the pattern fits a known cluster of suspected fakes. Removed reviews are noted in the methodology page of the delivered report.

Sample size

A typical urban report covers between 20 and 80 competing businesses and between 200 and 2,000 reviews. The minimum we consider statistically meaningful is 12 businesses with at least 10 reviews each.

Market type	Businesses	Reviews
Single-postcode small market	12–25	150–500
Mid-density urban category	25–60	500–1,500
Dense regional category	60–120	1,500–4,000

If your market falls below the minimum, we tell you before charging. Roughly one in twenty requested markets is below the threshold; in those cases we suggest a wider radius or refund any deposit.

Freshness

Each report is built on a snapshot taken at the start of the work. The cover page records the exact date of collection. We typically deliver within two working days of collection, which means the data in the delivered report is between two and four days old.

We do not refresh the snapshot after delivery. If you would like the report re-run a year later — to see how your numbers have moved — you commission a new report. There is no subscription and no automatic re-delivery.

Bias and limits

Public review data has known biases. We don't pretend otherwise; the methodology page of every delivered report flags the same limits, in the same language. The most important to be aware of:

Reviews skew to the extremes. Customers leave reviews when they're delighted or annoyed; the middle is under-represented. The distribution analysis on page 07 reflects this and frames the comparison accordingly.
Volume varies sharply by category. Restaurants attract many more reviews per customer than, say, accountants. Cross-category comparisons are not meaningful and we do not run them.
Non-English reviews are translated for analysis. The original is preserved; the analysis runs on a machine translation. Where translation confidence is low, the review is excluded from theme analysis and noted.
Themes are identified by structured read of every review, not by keyword count. Each review is tagged against a fixed taxonomy of themes built for the category, with a human spot-check on a 10% sample of every report.

How we analyse

A report has two halves: a calculated half, drawn directly from the reviews, and a written half, generated by a language model from a representative sample of review text plus the calculated stats. Every report's Appendix section repeats this in the same language.

Calculated figures

Ratings, volume, distribution, per-business sentiment, aspect-level sentiment, dominant-emotion counts, competitor benchmark, top phrases, and the competitive map are all computed from the reviews directly. Sentiment is scored automatically — positive, neutral, or negative — at both the review level and the aspect level. Consistency reflects how tightly a business's ratings cluster around its average; higher numbers mean a more uniform experience.

Written paragraphs

The executive summary, market-structure narrative, sentiment themes, customer-language tags, aspect derivation, the synthesised customer persona and its Q&A, the persona NPS reading, the SWOT, the strategic priorities, and the recommended actions are written by a language model. Each generation runs on a representative sample of review text together with the calculated stats; any section may be omitted when the call fails or the data is insufficient.

The synthesised persona

Every report includes a Persona section: a portrait of the market's composite customer, written from a representative sample of reviews across all businesses in the market. It is not a real person, a forecast, or a statistical aggregate; it is the review base's centre of gravity, rendered as a single voice.

The persona also answers a short interview and the standard 0–10 recommendation question. The NPS shown is the persona's own answer to that question — not a directly-measured survey result, and not a claim about your real customer base.

The Strategy section

The Strategy section contains a SWOT, a list of strategic priorities scored for impact and urgency, and a set of recommended-action cards with timeline, key activities, success metrics, estimated resources, and risk mitigation. These are written by a language model from the calculated stats and the themes it surfaced.

Treat them as a structured starting point for an internal conversation. They are grounded in the data we collected, but they are not bespoke advice and they are not a substitute for your judgement.

What we do not do

The list below is non-negotiable. If we ever change any of these, this page changes first.

We do not contact reviewers, ever, under any circumstance.
We do not write fake reviews, suppress real reviews, or advise on either.
We do not sell data on to third parties. The reviews collected for your report are used to produce your report and are then retained only so we can answer questions about it.
We do not respond to reviews on your behalf.
We do not run reputation-management or review-removal services. If that's what you need, we'll point you elsewhere — but it isn't us.