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Market & pricing intelligence for local services

tallywire is built to see local-service supply across the booking platforms: who operates where, what every service costs, how it moves, and the whole physical market it sits in. This page is the full inventory: every datapoint we collect and every analysis we run on it.

The sample is the real thing: the London market mapped venue by venue, price benchmarks with disclosed sample sizes, chain concentration, plus the actual data files: real venues with addresses, ratings, and 1,800+ priced menu rows. This is what arrives for your market.

450,000+ provider records·~17M priced service listings·80+ countries·collected on a rolling basis
The data model

From fragmented listings to a comparable market view

The same salon lists on Fresha, shows up on Google Maps, and runs a second location on Treatwell: three records, three name spellings, three menus. No single platform can see that. On the deep-report metros tallywire joins those listings into one venue record against the map layer, maps every menu line (“Ladies cut & finish”, “Wash, cut & blow dry”) to one comparable treatment, and only then computes a benchmark , so a number like “London haircut: £35 median” means one defined thing across the covered market:

3
platform listings for the same venue
1
canonical venue record with provenance
36
messy menu names mapped to comparable treatments
1
market view: benchmarks, fragmentation, change

Collect the visible market · resolve providers · normalize menus & prices · refresh on a rolling basis. Cross-platform entity joining runs on the 24 deep-report metros today; sitewide headline counts are per-source provider records until that merge is validated everywhere. Full detail: methodology.

The raw material

Every datapoint we collect

One normalized record per venue, joined across platforms. Business data only: no consumer or reviewer identities, ever.

DatapointWhat it isCoverage
Identity & location
venue name, address, postcode, lat/lon, geo-bucketed to neighborhood
every venue
Platform
which booking platform(s) the venue runs on
every venue
The priced menu
every published service with list price, currency and category. The core asset
~17M services
Service attributes
treatment category, duration, and price type (fixed / from / on-request) per menu line
where published
Rating & review volume
average rating + review count as quality and traction proxies
where published
Business endpoints
public website, booking link and business phone, where the venue publishes them
where published
Operating status
active / churned per listing, with first- and last-seen dates from the collection cycle
every venue
Price history
every price change captured as a dated, preserved series on monitored markets
all venues
The map reference layer
the full physical market around our roster: denominators, closures, chains
24 metros, growing
How it is built

Four steps, every market

01

Collect the visible market

Business, venue, service, price and location data across covered booking and map sources.

02

Resolve providers

Duplicate listings and locations matched into canonical provider and venue records, with source provenance.

03

Normalize menus & prices

Inconsistent service names mapped to comparable treatment categories; prices become benchmarks by service, area and platform.

04

Refresh & preserve

Source observations are collected on a rolling basis. Monitored markets receive a preserved monthly comparison snapshot: new, removed and changed listings, chain activity and price movement.

Coverage

What “covered” means

Every number on the site maps to exactly one of these universes, labeled per page so it always reconciles. No mixing counts.

UniverseWhat it isScale
Provider records
one venue on one covered platform, deduplicated per source (not yet cross-platform)
450,000+
Priced services
service rows with a published, usable list price
~17M
Published markets
cities with a public market page (data floor met)
growing
Deep-report metros
metros with a full public-map reference pull
24 metros
Monitored
rolling collection; monitored markets keep preserved monthly comparison snapshots
rolling
The intelligence layer

The analyses we run on it

Every card shows a real number from the latest completed collection, not an illustration.

Benchmarks

Pricing distributions

Median + interquartile range for every treatment, city and segment. The spread is the signal: where does a target price against its market?

London haircut: £30 median, £21–£49 IQR across 6,400+ hair & beauty providers
The roll-up read

Fragmentation & chains

Brand-grouped across the whole visible market, not just our roster: how many operators run 3+ locations and how much they hold. The consolidation thesis, quantified per metro.

London: 103 service chains hold just 3.3% of 12,591 visible venues with 97% single-site
The digitization read

The three-layer market

Every metro, cross-referenced against public map listings: the physical market, the online-bookable slice, and the supply with no map listing at all, visible only through the booking platforms.

London: 12,591 venues visible · 13.2% offer online booking · ~⅓ of our roster has no map listing
The distress signal

Closure watch

Venues flipping to permanently-closed, month over month: churn visible before it reaches any registry. Openings and price moves ride the same diff.

London today: 11% of map listings already marked permanently closed
The compounding asset

The price series

Every price change, dated and preserved. Monitored markets build a consistent month-over-month price index per treatment per metro.

Monitoring starts with a current baseline; subscribers own the series from month zero
What you receive

The deliverable, exactly

Every Market File arrives as a decision-ready report plus structured data, the same files as the London sample.

FileContents
market_report.pdf
the analyst read, benchmarks, map, fragmentation, target list
providers.csv
one row per venue: identity, location, platform, rating, menu size
services.csv
one row per priced service, joined on provider_id
README / data dictionary
column definitions, universes, coverage notes, methodology
Scope, honestly

What the data measures, and what it does not

tallywire measures observed provider supply, listed services and published prices across covered booking and map sources, and how they change. It does not measure transaction volume, bookings or audited venue revenue. Review counts are a digital-traction proxy, not throughput. Coverage per market is disclosed on every page; universes are defined in the methodology.

Pricing

One-off, or ongoing

A Market File shows what a market looks like now; Market Monitor shows how it changes. Full detail under pricing.

 What you getPrice
Market File
one-off
One standard market scope (one metro × one segment), generated on request from the latest completed collection: the analyst read, market map, pricing distributions, platform dispersion, fragmentation, venue list + named data files and a coverage appendix. Exact row count or a sample before you pay. Credited in full toward a Market Monitor agreement signed within 30 days.From $1,500
one standard market scope
Market Monitor
ongoing
Current data plus a preserved, comparable history of how your markets change: rolling source collection, monthly comparison snapshots, new and removed listings, status and chain changes, price movement, watchlists, scheduled delivery and periodic analyst review.From $1,500/month
billed annually · up to three scopes

One standard market scope means one metro × one service segment, such as London beauty services. Countrywide, multi-segment, multi-market and custom geographic scopes are quoted as bundles.

Need the data in your own product or workflow? API and data-feed access are available with Market Monitor or as a separately scoped enterprise agreement. Explore the API →

Browse live market reports

Every report is backed by the full distribution. Or query the same data via the API.

Get this for your market

Everything above, scoped to the metros and segments you care about , delivered in days, with an exact row count and a free sample before you pay.

tallywire · the local-service supply feedIntelligence
tallywire is not affiliated with or endorsed by the platforms shown. Platform names and marks belong to their respective owners; data is observed from public listings.