E1: SMS reminders raise attendance
RR 1.14 (1.03–1.26), 67.8%→78.6%; RR 1.08 without one outlier trial; SMS ≈ phone (RR 0.99)
Strength: strong · Type: peer-reviewed, transferable · Date: 2013 · Scored in: R1
Source: Cochrane CD007458
Evidence library · reviewed 2026-10-21
Salon no-show evidence, graded
23 sources behind our Policy Score, Policy Builder and guides: 9 peer-reviewed, 10 vendor figures. Each one says what it shows, how strong it is, and which scoring rule uses it.
How we grade
Every source page was opened and checked unless noted. Transferable = healthcare or restaurant evidence, not salons. Vendor = a platform's own data with no published method. No peer-reviewed salon or beauty no-show study was found. Conflicting evidence does not change Policy Score points until it is reviewed.
Machine-readable copy: /evidence.json (same data, updated with this page).
What the Policy Score counts, and why
| Rule | What scores | Max points | Strength | Evidence |
|---|---|---|---|---|
| R1 | Automated reminders for every appointment | 30 | Strong (transferable from healthcare) | E1, E2 |
| R2 | Two reminders beat one | 12 | Moderate (transferable from healthcare) | E3, E2 |
| R7 | Reminders state the specific value of the slot | 10 | Weak–moderate (transferable; 1 RCT found an effect, a 2026 replication found none overall) | E6, E23 |
| R3 | A payment commitment at booking (size not scored) | 15 | Weak–moderate (uncontrolled vendor data; the only RCT found no effect) | E10, E11, E13, E7 |
| R6 | Target friction at new clients, past no-shows and far-ahead bookings | 12 | Moderate (transferable from healthcare) | E4, E5, E3 |
| R5 | Waitlist / backfill for cancellations | 11 | Weak–moderate (vendor data) | E16, E17 |
| R4 | Written policy shown at booking, notice window ≥24h | 10 | Weak (no comparative evidence) | none (no comparative study) |
| R8 | Confirmation requests: not scored | 0 | Weak | E18 |
Sources
E2: Text notifications cut no-shows; multiple beat single
No-shows 21%→15% (RR 0.75); multiple > single; voice > text
Strength: strong · Type: peer-reviewed, transferable · Date: 2016 · Scored in: R1, R2
Source: Robotham, BMJ Open
E3: Two reminders beat one
Missed: 3d+1d 4.4% vs 1d 5.3% vs 3d 5.8% (n=54,066). High-risk: 20.5% vs 24.2–25.0%
Strength: moderate · Type: peer-reviewed RCT, transferable · Date: 2018 · Scored in: R2, R6
Source: Steiner, AJMC
E4: Lead time and prior no-shows predict no-shows
105 studies; mean 23.0% (4.0–79.2%); high lead time and prior no-show history the most common determinants
Strength: moderate · Type: peer-reviewed review, transferable · Date: 2018 · Scored in: R6
Source: Dantas, Health Policy
E5: Shorter booking horizon
7.8%→3.9% after the maximum booking horizon was cut from 28 days to 1 day (one practice)
Strength: moderate · Type: peer-reviewed, transferable · Date: 2021 · Scored in: R6
Source: Margham, BJGP
E6: Specific-cost wording
11.1%→8.4% (OR 0.74) in Trial 1; Trial 2 kept the cost message as reference (8.2%) with no control arm, so it is not a replication (see E23); vague "general cost" wording 9.9%; social-norm message raised cancellations from 8.8% to 10.5%
Strength: moderate · Type: peer-reviewed RCTs, transferable · Date: 2015 · Scored in: R7
Source: Hallsworth, PLoS ONE
E7: A fine didn't help
€34 fine: 5% vs 5% (130/3,333 vs 131/3,413)
Strength: moderate · Type: peer-reviewed RCT, transferable · Date: 2018 · Scored in: R3
Source: Blæhr, BMJ Open (BMJ site returned 403; abstract read via SDU)
E8: Card guarantee cut no-shows and bookings
Both fell significantly (p<.001); 6 hotel restaurants
Strength: weak · Type: dissertation, transferable · Date: 2015 · Not scored
Source: Hernandez, Walden
E9: Deposit size
£50 deposit: "zero no shows" for about a year; cutting it to £5 brought them back (one restaurant)
Strength: weak · Type: anecdote · Date: 2023 · Not scored
Source: Drinks Business
E10: Deposits (Phorest)
5.4%→1.9% (−65%); typical deposit is 30% of price. Same year in trade press: "−47%"; UK no-shows 5% (counties 4.1–9.4%)
Strength: weak · Type: vendor · Date: 2021 · Scored in: R3
Source: Phorest, Estetica
E11: 100% deposits (Kitomba)
−29% cancels/no-shows vs no deposit
Strength: weak · Type: vendor · Date: 2024 · Scored in: R3
Source: Kitomba
E12: Card on file (Fresha)
"89% fewer no-shows" / "up to 90%"; reminders "up to 30%"; ~10% late cancels + no-shows
Strength: weak · Type: vendor · Date: 2022–23 · Not scored
Source: Estetica, Fresha
E13: Fees (Square, Booksy)
Square −21% cancels/no-shows; 5% of sellers had fees on in 2021, "nearly tripled" by 2023. Booksy −20% cancellations, "no significant impact on bookings"
Strength: weak · Type: vendor · Date: 2024 / 2021 · Scored in: R3
Source: Square, Booksy
E14: Deposits (GlossGenius, Zenoti, Boulevard)
GlossGenius +32% successful appointments; Zenoti "95% drop"; Boulevard "up to 71%" (first 90 days)
Strength: weak · Type: vendor · Date: 2025 / 2026 / 2022 · Not scored
Source: GlossGenius, Zenoti, Boulevard
E15: UK benchmarks (Fresha, >3M appts)
All 3.8%; barbers 21.16%; brows/lashes 6.55%; beauty 3.59%; nails 3.55%; hair 3.16%
Strength: moderate (sample disclosed) · Type: vendor, via trade press · Date: May–Aug 2024 · Not scored
Source: Professional Beauty
E16: US/CA benchmarks (Zenoti), cancel / no-show
Salons 8/3%; nails 16/1%; barbers 2/4%; membership spas 14/1%; non-membership spas 11/1%; medspas 16/5%
Strength: moderate · Type: vendor · Date: 2024 data · Scored in: R5
Source: Zenoti
E17: Backfill
GlossGenius waitlist fills "12% more cancellations". Zenoti, 2025 data: nails cancels 16%→11% while no-shows rose 1%→4%
Strength: weak · Type: vendor · Date: undated / 2025 · Scored in: R5
Source: GlossGenius, Zenoti
E18: Two-way texts
RR 1.03 (0.95–1.12) for attendance vs standard care; 5 trials, Africa
Strength: weak · Type: peer-reviewed, transferable · Date: 2022 · Scored in: R8
Source: Ødegård, PLoS ONE
E19: Owner voice
"50% deposit… drastically reduced… no shows"
Strength: weak · Type: anecdote · Date: undated · Not scored
Source: r/Esthetics (source page not opened by us; quoted from a secondary summary)
E20: Consumers accept salon no-show fees
Canada, n=1,001 (online, weighted, MoE ±3.1): 53% call a barber/salon no-show fee justified; 8% missed a barber/salon appointment in the past year; 4% paid such a fee; 18–34s miss most (43% any appointment). Per person-year, not a per-booking no-show rate
Strength: moderate (acceptance only) · Type: independent poll · Date: 2024-08-07 (fieldwork Jul 5–7) · Not scored
Source: Research Co.
E21: UK cancellation notice and losses (self-report)
Clients who cancel: 62% give <24h notice; 22% cite forgetting. Owners: 56% lose <5% of monthly revenue, 29% 5–10%, 15% 11–20%
Strength: weak · Type: vendor survey · Date: pub. 2026-02-02 (data Dec 2025; ~200 businesses + 500 clients) · Not scored
Source: Fresha survey
E22: Self-service cancellation vs no-shows by booking channel (Japan)
June 2026, all shops on Reservia: client self-booked web cancel 17.61% but no-show 1.80% (n=206,014); staff-entered bookings 15.37% / 4.87% (n=144,018); external booking sites 9.47% / 4.14% (n=60,077). Same direction in all 6 segments (hair 17.24% vs 15.36% cancel). No-show = cancelled by the shop on the day
Strength: moderate (correlational; Japan) · Type: vendor platform data, full count, definitions disclosed · Date: data 2026-06 (pub. ~2026-08) · Not scored
Source: Reservia
E23: Specific-cost and social-norm wording did NOT replicate
Denmark, 1 hospital, 3 outpatient depts, 20,867 appointments (Oct 2019–Mar 2020), SMS ≤2 days before, wording rotated every 2 months (time-blocked, not randomised). Overall: neither cost nor social-norm wording reduced no-shows; cost wording raised advance cancellations 2.45%→3.42% (OR 1.41). By dept: social norm cut no-shows in Cardiology 5.23%→4.03% (OR 0.76); cost wording raised them in Endocrinology 3.94%→5.09% (OR 1.31). Men 5.13% vs women 3.62%
Strength: moderate (large n; not randomised) · Type: peer-reviewed quasi-experiment, transferable · Date: pub. 2026-04-23 (data 2019–20) · Scored in: R7
Source: Hansen et al., Behavioural Public Policy
Gaps and conflicts
- Benchmarks conflict. Barbers are 21.16% in the UK (E15) but 4% in the US/Canada (E16). Booksy's "10–15%" average has no source (Booksy). Zenoti's E16 page gives both 3% and a "widely cited… 10 to 15 percent". Use E15/E16 with region and year. Never quote 10–15% or 30%.
- Thin segments. Lashes rest on a single figure (Fresha, UK, summer). Spas have Zenoti data only. No source reports *late* cancellations under a defined window; Zenoti counts all cancellations.
- Deposit effects are uncontrolled. Phorest reports both −65% and −47% for the same feature in the same year. Vendor figures range from 20% to 95%, and they come from opt-in, before/after comparisons. The only RCT tested a fine, not a deposit, and found no effect (E7). Whether deposits cost bookings is unresolved: E8 says yes, Booksy (E13) says no.
- Untested choices. Deposit size (25/30/50/100%), 24h vs 48h windows, and SMS vs email in salons have no evidence. Vagaro's "as much as 40%" and "66%" give no method (Vagaro). GlossGenius's "about 40%" last-minute cancellations is unsourced.
- Confirmation requests. E18 compares two-way texts with standard care, not with one-way reminders. One secondary blog (PandoraBot) states it as "vs one-way". That blog's other figures ("79%" of fines unpaid; a two-way head-to-head trial) were not verified.
- Not scored. Patients writing down their own appointment cut DNAs 18% (Martin, JRSM 2012), but the study was uncontrolled before/after.
The salon no-show letter
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