SaaS vs Custom

Three-salon eyelash & brow group (Brisbane CBD, Southbank, Bulimba; 12 senior technicians, 6 treatment pods, $120k monthly revenue, 2000+ active clients, 70% lash fills [recurring every 2–3 weeks], 20% full lash sets, 10% brow design + tinting): Fresha booking software ($100/month + 2.19% per transaction). Monthly transaction volume: $120k. Fresha fee: $120k × 2.19% = $2,628/month = $31,536/year. Client Mia: books lash fill (30 min, $120). Fresha deducts: fee ($120 × 2.19% = $2.63). Salon receives: $117.37. Technician Emma: 30-min appointment is $45 rate (Fresha doesn't track commission). Emma's commission: manual spreadsheet (manager calculates: Emma 40 hours × $45 = $1,800, minus shared pod $300 = $1,500). Rebook reminder friction: Mia (wants lash fill in 3 weeks). Emma's calendar: booked (no 30-min slot for 4 weeks). Mia books: 4 weeks out (doesn't want to wait). No rebook reminder sent (Mia forgets). Appointment gap: 7 weeks (loses 2 fills worth $240). Style reference friction: Mia (loves "Russian volume, dark, full-length"). Emma: remembers last time (10-min review of notes). No photo reference (Emma leaves). New technician Kate: doesn't know Mia's exact style. Mia gets: "usual" but inconsistent quality (Kate's Russian volume different). Mia disappointed: "Doesn't look like last time." Churn risk: 0-star review. Inventory friction: 200 lash boxes, 50 glue bottles, 30 brow dyes. Manager's process: spreadsheet tracking. Glue shelf-life: 3 days once opened. Manager forgets: glue bottle A still in use. Sarah: applies expired glue (clients: irritation, red eyes). Client complaints: salon liable. Inventory waste: 15% stock expires unused ($2,400 lash/year + $400 glue = $2,600/year wasted). Gift voucher friction: Jessica gets: gift voucher $100 (physical card). Friend visits, voucher handed to receptionist. Receptionist notes: spreadsheet ($100 balance). Friend redeems: $95 (balance $5, noted). Week later: friend returns ("I have $5 left"). New receptionist Lauren (spreadsheet lost, no record). Dispute (friend loses $5). Digital loss: 8 vouchers/week × 8% loss = $64/week = $3,328/year. Intro package friction: new client Alex (intro: full lash set $150 + free aftercare kit + 20% off next fill). Alex buys: $150 (includes 20% next fill discount). Receptionist: "Your next fill is 20% off, just mention it." Alex: doesn't write it down. Alex books: 3 weeks later (receptionist new). Receptionist processes: normal price $120. Alex: "I got 20% with intro!" Receptionist: "I don't see it." Dispute (Alex leaves negative review). Intro loss: 20 packages/month × 8% loss = $38/month = $456/year. Instructor commission friction: 3 "beauty educators" (teach new techs). Rate: $50/hour teaching + $10 per mentee trained. Manager's process: spreadsheet (teaching hours only, no mentee tracking). Instructor Rose: 40 hours × $50 = $2,000. Mentees trained: 2 (no commission, $0). Rose: underpaid (doesn't know bonus structure). Commission disputes (Rose "Why no mentee pay?"). Rose leaves: competitor (replacement $8k onboarding + 4-week productivity loss). **Total friction: $18k+ annually** (Fresha fees $31.5k, rebook gap $5.4k, style reference loss $2k, inventory waste $2.6k, gift voucher loss $3.33k, intro loss $456, instructor commission disputes $4k).

Why Fresha's 2.19% Cut Bleeds Recurring Beauty Revenue

Fresha's model: $100/month base + 2.19% per transaction. $120k/month salon group: $2,628/month in Fresha fees = $31,536/year. Fee structure: Fresha's 2.19% includes payment processing margin (Stripe ~2.2%, Square ~2.75%), but Fresha's lock-in: all payments must process through Fresha (no alternative processor). Fresha profit model: take 2.19% + hidden processor margin (~1.5%), total cut ~2.5%. 3-salon group: revenue $120k/month. Fresha/processor margin: $120k × 2.5% = $3,000/month (hidden cost beyond 2.19% displayed). Fresha's gap: no recurring auto-rebook system (clients book manually, forget, churn). No style preference storage (inconsistency, client satisfaction drops). No inventory integration (waste, product liability). No digital gift codes (8% loss). No intro package automation (56% annual loss). No instructor commission tracking (turnover, disputes). Custom platform advantage: own Stripe processor relationship (1.5% typical for established merchants). $120k/month salon: Stripe cost ~$1,800/month = $21,600/year (vs Fresha $31.5k = $9,900/year savings). 3-salon group: Year 1 Fresha fee savings alone = $9,900 (before automation value).

Six Custom Features That Beat Fresha

1. Recurring Fill Auto-Rebook — Smart Rebook Windows (Every 2–3 Weeks Based on Lash Type), SMS/Email Reminders (7 Days Before + 24 Hours Before), Technician Continuity Preference, Cancellation Auto-Reschedule, Waitlist Automation

Current: Fresha calendar (basic month view, no auto-rebook, manual booking friction). Mia: books lash fill 30-min, $120 (today). Fresha shows: Emma's availability (2-week view). Emma: booked (next 30-min slot is 4 weeks out). Mia: doesn't want 4-week gap (books 4 weeks, forgets to book again). Appointment gap: 7 weeks (loses 2 fills worth $240). New system: recurring auto-rebook. Mia: books lash fill (today). System calculates: optimal rebook window (Russian volume lash fills: every 3 weeks optimal for retention + client preference data shows: Mia books every 2.5 weeks). System sends: reminder 7 days before (SMS + email: "Mia, your lash fill is next Wednesday 10 am with Emma. Ready to book your next fill? Slots available: 9 July (Emma), 10 July (Kate), 12 July (Sarah) [links]."). Mia receives: reminder (clicks 9 July, books with Emma [instant, avoids 4-week gap]). System logs: next appointment scheduled (today → 9 July = 16-day gap [perfect, Mia happy]). 24-hour reminder: SMS "Mia, your lash fill tomorrow 10 am with Emma, pod 2. See you then!" Mia: receives (confirms, doesn't cancel). Technician preference: Mia loves Emma's work (Emma's style matches Mia's Russian volume preference). System tracks: Mia's technician preference (Emma flagged). System shows: Emma's next slots first (9 July with Emma highlighted). Mia: books Emma (consistency guaranteed). If Emma unavailable: system suggests next choice (Kate, same training level). Mia: books Kate as backup (trusts training standard). Technician continuity: Mia's fills always Emma or Kate (zero style inconsistency). Cancellation auto-reschedule: Mia (emergency, needs to cancel 10 am Wednesday). SMS: "Mia, we understand! Need to reschedule? Next slots with Emma: 16 July, 23 July, 30 July [links] or other techs: 9 July Kate, 12 July Sarah." Mia: clicks 16 July Emma (instant reschedule, zero lost revenue). Waitlist automation: Mia's friend Sofia (wants Friday 2 pm, no availability). Sofia: joins waitlist. Cancellation: Thursday, technician Kate cancels her Friday 1 pm (30-min). System detects: cancel (triggers waitlist). Sofia (top waitlist for Friday): system sends SMS (within 1 hour: "Sofia, your waitlist slot! 30-min lash fill, Friday 1 pm with Kate. Confirm within 1 hour?" Sofia confirms: booked, zero manual work). **Value: recurring automation (zero booking friction, 100% rebook rate), technician continuity (style consistency, client satisfaction +25%), cancellation mitigation (instant reschedule), waitlist automation (zero manual notifications). Payback: 2 weeks.**

2. Client Style Preference Gallery — Photo Storage Per Client (Russian/Classic/Hybrid Reference Photos), Technician Notes (Pin Thickness, Volume Density, Curl Pattern), Before/After Photo History, Style Consistency Dashboard, Export Client Profile for New Technician Onboarding

Current: Fresha notes (basic text field, no photo storage, inconsistency when technician changes). Mia: books with Emma (Emma remembers: "Russian volume, dark, full-length, loves feathered effect"). Mia's next appointment: Emma unavailable (Kate assigned). Kate: reads Fresha notes ("Russian volume, dark, full-length"). Kate's interpretation: different pinning technique (higher thickness = heavier look vs Emma's softer Russian style). Mia receives: fills (heavier, doesn't match last time). Mia: "This doesn't look like Emma did it, what happened?" Churn risk: Mia considers switching salons. New system: style gallery. Mia: books with Emma. Emma: captures 3 reference photos during fill (client's lash line, style detail, final result). Photos saved: Mia's profile under "Emma's technique" folder. Emma: adds notes (Pin thickness: 0.18mm, Volume density: 4-6D per natural, Curl pattern: D-curl, Faux-lashes effect on inner corner). Emma's build time: 10 min notes (adds style specificity). Mia's profile dashboard: shows "Emma's preferred style" + 3 reference photos + detailed notes. Mia's next appointment: Kate assigned (Emma unavailable). Kate: opens Mia's profile (sees Emma's photos + technical notes). Kate: applies same pinning (0.18mm thickness, 4-6D density, D-curl). Kate: matches Emma's technique (same visual result). Mia receives: consistent fills (looks identical to Emma's work). Mia: "Perfect, same as always!" No churn (client retained through consistency). Before/after history: system auto-archives (every appointment: 2 photos before + after, tagged with technician). Mia's profile: shows 20-appointment history (client sees: timeline of her own fills, proud of lash journey). Style evolution: Mia (after 6 months): "I want my Russian volume darker." Emma: pulls Mia's history (shows progression). Mia chooses: month 3 photo as reference (darker density). Emma applies: custom adjustment (Mia loves the new direction). Mia: "I love my lash evolution journey" (posted on Instagram, salon tag [free marketing]). Technician onboarding: new hire Jess (joins team). Manager: exports profiles for clients Jess will service (5 VIP clients assigned). Each profile: includes style photos + technical notes. Jess: studies profiles (1 hour learning client preferences, no trial-and-error appointments). Jess's first week: 5 clients booked with her (clients prepared for new technician via manager's intro email: "Jess is trained in your preferred style, we've shared your reference photos with her"). Clients: confident (Jess has homework done). Jess succeeds (zero client complaints, smooth onboarding). Churn prevention (experienced clients often leave when preferred technician unavailable, style gallery prevents 15% of this churn = 30 clients × $120 × 8 fills/year = $28,800 value). **Value: style consistency (zero inconsistency complaints), technician transitions (smooth onboarding, zero client churn), before/after documentation (client marketing, Instagram-worthy), learning tool (Jess gets trained vs learning on clients). Payback: 3 weeks.**

3. Digital Gift Voucher + Intro Package System — Unique Gift Codes, Customizable Denominations ($50, $100, $200), Auto-Expiry Tracking (12-month validity), Intro Package Automation (Full Lash Set $150 + Aftercare Kit + 20% Next Fill Discount Auto-Applied), Redemption History, No Lost Balances, Fraud Prevention

Current: physical gift vouchers + intro package manual tracking (spreadsheet, receptionist notes, 8% loss rate = $3,328/year loss, intro discount loss = $456/year). Jessica's friend receives: physical gift voucher $100. Friend visits (voucher handed to receptionist). Receptionist notes: spreadsheet ($100 balance). Friend redeems: $95 service (balance $5 noted). Week later: new receptionist Lauren (spreadsheet lost). Friend: disputes $5 (reputation damage). Intro package: new client Alex (intro: full lash set $150 + free aftercare kit + 20% next fill). Alex completes: lash set. Receptionist: "Next fill is 20% off, mention it next time." Alex: forgets. Alex books: 3 weeks later (receptionist new). Receptionist: normal price $120 (Alex expected discount). Alex: disputes (leaves negative review). New system: digital gifts + intro automation. Jessica (buys gift voucher for friend, $100). System generates: unique code (GIFT-2406-KL9M2). Jessica: shares code (SMS or email to friend). Friend receives: code (GIFT-2406-KL9M2, $100 balance, expires 13 June 2027). Friend visits: salon. Receptionist: "Do you have a gift code?" Friend: "Yes, GIFT-2406-KL9M2." Receptionist enters: code (system loads: valid ✓, $100 balance, expiry 13 June 2027 ✓, friend's name). Friend books: $95 service. System deducts: $100 – $95 = $5 remaining. System logs: redemption (code, redeemed $95, remaining $5, date). System sends: auto-email to friend (immediately, "Your gift voucher balance: $5 remaining, expires 13 June 2027"). Week later: friend returns (uses $5 balance). System logs: final redemption ($5 → $0, code expires). No manual notes (zero loss). Intro package automation: new client Alex (intro package purchased: full lash set $150 + free aftercare kit + 20% next fill discount). System flags: Alex's profile (intro discount $24 [20% of $120 next fill] auto-applied, expiry 12 weeks from today [standard validity]). Alex completes: full lash set. Receptionist: shows Alex's next-fill discount (automatically loaded, no manual mention needed). Receptionist: "Your next fill is 20% off, ready to book?" Alex: books next fill (date locked). System reminder: 2 weeks before next fill (SMS: "Alex, your next fill is in 2 weeks, and you have 20% discount applied! Book your slot [link]."). Alex books: appointment auto-applies 20% discount at checkout (Alex sees $96 charge [20% off $120], happy). Alex returns: full-price client henceforth (intro discount expired, Alex became regular client). Zero intro discount loss (100% redemption). Voucher expiry: system sends reminder 30 days before (email: "Your $100 voucher expires 13 June 2027, $20 remaining, use it before expiry!"). Friend uses: last $20 (skincare product purchase). Voucher fully redeemed (zero waste). Bulk corporate vouchers: salon sells: 50 gift vouchers to corp client @ $50 each = $2,500 sale. System generates: 50 unique codes (batch BULK-2406-A1 through A50). Corp client: distributes codes to employees. Employee James: redeems code (books $45 fill). System logs: James used $45 of $50. Manager's dashboard: batch BULK-2406 (20 redeemed, 30 unused, $2,250 revenue captured, 30 pending [expiry 13 June 2027]). **Value: digital tracking (zero manual loss), fraud prevention (code authentication), intro automation (100% discount redemption, churn prevention), expiry reminders (zero abandoned balances), bulk sales tracking. Payback: 3 weeks.**

4. Inventory Management — Lash Extension Stock Tracking (200 boxes, track usage per client/style), Glue Bottle Shelf-Life Management (3-day expiry once opened, auto-expire in system), Brow Dye Stock Levels, Low-Stock Alerts, Waste Tracking (identify expired unused stock), Supplier Reorder Automation

Current: spreadsheet inventory (manager manually tracks, glue expiry forgotten, product liability risk, 15% annual waste = $2,600/year loss). Manager's process: 200 lash boxes, 50 glue bottles, 30 brow dyes. Glue shelf-life: 3 days once opened. Manager notes: "Glue bottle A opened Thursday." Glue expires: Monday (3 days). Manager forgets: bottle A still in use. Technician Sarah: applies expired glue (client allergic reaction, red eyes, irritation). Client complaint: "Why are my eyes red?" Salon liable: product liability claim, reputation damage. Inventory waste: 15% stock expires unused (lash boxes $200/month wasted = $2,400/year, glue $400/year = $2,600 total waste). New system: inventory automation. Manager: stocks 200 lash extension boxes. System creates: inventory ledger. Lash box usage: technician Emma (uses box 0.18mm thickness). System logs: box opened (timestamp recorded). Emma completes: 4 fills from box 0.18mm-001. System deducts: 4 units from box 0.18mm-001 (remaining: 96 units). Glue bottle management: manager opens: bottle A (timestamp 10 June, 10 am). System logs: bottle A active (3-day countdown starts). Technician Sarah: uses bottle A daily (fills: logged). Expiry: Monday 13 June (system alerts manager Friday 12 June: "Bottle A expires Monday, 2 fills remaining, use or discard by 1 pm Sunday."). Manager: discards Sunday (zero use of expired product). Expired batch prevention: system auto-flags (bottle A not used by 1 pm Monday, auto-marked expired, system prevents Sarah from selecting it next appointment). Sarah: tries to select bottle A (system blocks: "This bottle expired 13 June, please use bottle B [active, opened Monday]."). Sarah uses: bottle B (no product liability). Brow dye stock: system tracks (30 units, tinting appointments deplete inventory). Low stock alert: system detects (brow dye at 3 units, <10% threshold). Manager receives: alert (Sunday, "Brow dye low stock, 3 units remaining, reorder by Wednesday."). Manager: places order (supplier delivers Wednesday, stock replenished). Zero stock-out (all appointments fulfilled). Waste tracking: system generates (monthly waste report: 15 lash boxes expired unused [boxes unused past shelf-life], 2 glue bottles expired [not used], $180 month waste). Manager identifies: "Brow dye boxes ordered but only used 8/30, planning overstocked 3 weeks ahead." Manager adjusts: next order (15 units instead of 30, reduces waste). Waste reduction: month 2 ($45 waste, down 75% from $180). Annual waste savings: $2,600 × 75% = $1,950 saved. Supplier reorder automation: system tracks: lash box A [0.18mm thickness] (usage rate: 5 boxes/week). Current stock: 8 boxes. At usage rate (1.6 weeks of stock remaining). System alerts: Wednesday (reorder needed Friday for Monday delivery). Manager: approves reorder (10 boxes, $120). System sends: automated order to supplier (system integrates with supplier API). Lash boxes: arrive Friday (stock received Monday). Zero stock-out disruption. **Value: product liability prevention (no expired product use), waste reduction ($1,950/year savings), stock-out prevention (all appointments fulfilled), supplier automation (reorder friction eliminated). Payback: 4 weeks.**

5. Instructor Commission Automation — Teaching Hours Tracking (Rose: 50 hours/month @ $50/hour = $2,500), Mentee Success Tracking (Rose trained 3 new technicians, each gets $10 bonus = $30), Automated Weekly Pay (Transparent Breakdown), Mentorship Quality Scores, Dispute Prevention

Current: manual commission tracking (manager 80 hours/year = $12,000 labor value, instructor disputes, turnover cost $8k per replacement). Instructor Rose: teaches 50 hours/month @ $50/hour = $2,500. Mentees trained: 3 new technicians (no bonus tracking). Manager's process: spreadsheet (teaching hours only, no mentee outcomes). Rose: doesn't know if she gets mentee bonuses. Rose: frustrated (underpaid, no transparency). Commission dispute: Rose "Why don't I get paid for training?" Manager: "It's not documented." Rose: leaves (joins competitor, replacement cost $8k onboarding + 4-week productivity loss). New system: instructor commission. Rose: logs teaching hours (system tracks real-time). Monday 10 am: Rose teaches mentee Jess (1-hour foundation training). System logs: Rose 1 hour @ $50/hour = $50 logged. Mentee success: system tracks (Jess's first solo appointment Thursday). Appointment outcome: client review (5-star "Jess did amazing!"). System links: Jess's success → Rose's mentee record. System auto-adds: Rose's bonus $10 (mentee success bonus, Jess trained by Rose = $10 to Rose for quality outcome). Rose's app transparency: weekly summary (50 hours × $50 = $2,500, mentee bonuses: 3 mentees × $10 = $30, total $2,530). Breakdown visible: itemized (each mentee name, bonus logged). Rose: sees exactly why she got $2,530 (no mystery). Payout: automatic (system sends bank transfer Friday, $2,530 with itemized receipt). Rose: receives money + receipt (understands completely, no disputes). Mentorship quality: system tracks (mentee Jess: 5-star client reviews after Rose's training). System scores: Rose's mentorship quality (Jess trained by Rose → 4.9 avg client satisfaction score). Rose's quality score: 4.9/5 (top instructor). Bonus acceleration: month 2, Rose trains 5 new techs (instead of 3). System auto-calculates: 5 mentees × $10 = $50 bonus (vs $30 month 1). Rose's monthly bonus: accelerates with output (incentivizes training). Dispute prevention: Rose (reviews pay stub Friday: $2,530 itemized). Rose: sees mentee Jess's name + bonus ($10). Jess: 5-star review date visible (Rose confirms: "Yes, I trained Jess, she got 5 stars, $10 bonus correct."). Zero disputes (transparent, verifiable). Salary advancement: Rose (quality score 4.9/5, trained 15 mentees YTD). Manager reviews: Rose's instructor tier (top performer, qualifies for senior instructor rate: $60/hour [up from $50] + $15 per mentee bonus [up from $10]). Manager: offers Rose promotion (senior instructor, $2,800/month base + mentee bonuses $45/month [assuming 3 mentees/month] = $2,845 total). Rose: accepts (feels valued, no poaching risk). Retention: Rose stays (salary increase prevents competitor poaching). **Value: commission automation (zero manual tracking), transparency (mentee outcomes visible), bonus acceleration (quality incentive), dispute prevention (zero instructor conflicts), retention (promotion pathway). Payback: 6 weeks.**

6. Rebook Reminders + Churn Prevention Dashboard — 7-Day + 24-Hour SMS/Email Pre-Appointment Reminders, Low-Activity Client Alerts (No Booking in 8 Weeks), Re-Engagement Offers (SMS: "Miss you! 20% off your next fill"), Lifetime Value Tracking, Churn Risk Scoring

Current: no reminder system (clients forget to book next appointment, appointment gap grows, churn risk). Mia: books lash fill (today). No reminder sent. Mia: forgets to book next appointment. Gap grows: 7 weeks (misses 2 fills). Mia: "I'm tired of chasing bookings, finding new salon." Churn (revenue lost). New system: smart reminders. Mia: books lash fill (appointment 20 June). System calculates: optimal rebook window (Russian volume lash fills: every 3 weeks optimal). System sends: reminder 7 days before (13 June: SMS + email "Mia, your lash fill is next Wednesday 20 June at 10 am with Emma. Ready to book your next fill? Slots available: 4 July (Emma), 5 July (Kate), 7 July (Sarah) [links]."). Mia receives: reminder (clicks 4 July, books with Emma [instant]). Gap: 20 June → 4 July = 14 days (perfect, Mia happy). 24-hour reminder: SMS "Mia, your lash fill tomorrow 10 am with Emma, pod 2. See you then!" Mia: confirms (doesn't cancel). Low-activity alerts: system tracks (Olivia: last appointment 8 weeks ago). System flags: Olivia low-activity (baseline: fill every 3 weeks = 10–12 appointments/year; Olivia: 1 appointment in 8 weeks). Manager receives: alert (Olivia at risk, churn probability 75%). Manager sends: personal SMS (Olivia: "Hi Olivia, miss your beautiful lashes! It's been 8 weeks—let's get you back. 20% off your next fill, expires Friday. Book now [link]."). Olivia: reads offer (motivated, books $96 lash fill [20% off $120]). Olivia returns: lashes back in rotation (future revenue $120 × 8 fills/year = $960 recovered). Churn prevented. Lifetime value dashboard: Mia's profile (total spend $4,800 [40 appointments], average $120/appointment, frequency: every 3 weeks [14 appointments/year baseline], spend trend: up +12% YTD [added brow tinting $20/visit]). Retention status: loyal (green ✓, VIP). Manager's attention: Mia high-value (prioritize for quality, consistency). Churn risk scoring: James (member, activity low: 2 fills in past 90 days [baseline 9]). System flags: James churn risk score 82/100 (high risk). Manager receives: alert. Manager sends: SMS (James: "Hi James, haven't seen you in ages! Lashes need a refresh? New technician Kate is amazing. Book 30-min fill, 20% off this week [link]."). James: books (motivated by offer + new technician suggestion). James returns (churn prevented). Annual churn prevention: system prevents 8 churn events/month × 12 months = 96 client saves/year × $960 lifetime value = $92,160 annual churn-prevention value. **Value: rebook automation (zero gap friction), low-activity alerts (early churn detection), re-engagement offers (SMS-driven recovery), lifetime value visibility (VIP identification), churn scoring (predictive intervention). Payback: 5 weeks.**

Australian Beauty Industry Compliance: FairWork Award + GST

**FairWork Beauty and Hairdressing Award (all states)** — technicians classified: Level 1 (trainee, $23.47/hour as of 2026), Level 2 (qualified lash/brow, $28.38/hour), Level 3 (senior educator, $31.92/hour). Salon must: track hours (full-time vs part-time vs casual), ensure pay meets award minimums, provide break entitlements (10-min unpaid per 2-hour block). Commission structure: technician hourly rate + retail commission must not reduce total pay below award minimum. Example: Level 2 technician ($28.38/hour, 40-hour week = $1,135.20). Commission retail ($100 weekly) is separate (total must ≥ $1,135.20 minimum). Custom platform: tracks award rates (technician classification, system enforces minimum pay per hour + commission to meet FairWork). **GST on Beauty Services (all states)** — lash extensions, brow design, brow tinting, beauty services: GST-taxable (10% tax collected on revenue). Retail products: GST-taxable (10% on aftercare kits, lash primers, glues). GST reporting: quarterly Business Activity Statement (BAS) to ATO. Example: $120k monthly salon revenue. GST-taxable (90% lash services $108k + 10% retail $12k = $120k). GST owing: $120k × 10% = $12k per quarter = $48k annual GST owing. System tracks: all transactions GST-tagged (services vs retail), generates: quarterly GST report (auto-calculates $12k owing, itemized by category). Salon accountant: uploads report to BAS (system pre-calculated, reduces accounting hours). Commission GST: technician commission on retail (10% of $12k retail = $1,200 annual commission). GST treatment: technician commission is business income (technician must declare on tax return). System tracks: commission separately (reported as technician income to ATO if required). Custom platform: GST integration (auto-calculates per transaction, generates: quarterly report, reduces accounting complexity).

Three-Salon ROI: Fresha vs Custom Platform

**Current state (Fresha + manual processes):** $120k/month revenue. Fresha fees: $31,536/year. Rebook gap: 18 clients × 2 missed fills/year × $120 avg = $4,320/year. Style reference loss: inconsistency complaints + chargebacks $2,000/year. Inventory waste: $2,600/year. Gift voucher loss: $3,328/year. Intro package loss: $456/year. Instructor commission labor: $12,000/year. Instructor turnover: $8,000/year. **Total friction: $64,240/year.** Custom platform build: $60k (one-time, 3-salon deployment). Annual ops: $2,400 (hosting, support, updates). Year 1 net cost: $62,400. **Year 1 value delivered:** Fresha fee savings: $9,900 (own processor at 1.5%). Rebook automation: $4,320 (100% of gap recovered). Style consistency: $2,000 (zero churn from style mismatch). Inventory waste prevention: $1,950 (75% reduction). Gift voucher system: $3,328 (zero loss). Intro package automation: $456 (100% redemption). Commission automation: $12,000 (zero labor). Instructor commission transparency: $4,000 (zero turnover risk, turnover rate drops 2→0/year). Churn prevention (rebook + re-engagement): $92,160 (96 clients saved × $960 LTV). **Total Year 1 value: $129,794.** Net Year 1 ROI: $129,794 – $62,400 = $67,394 profit. Payback period: 42 weeks. Year 2+ (ongoing value): $129,794/year value – $2,400 ops = $127,394 annual profit (no build cost). 3-year total value: $67.4k (Yr 1) + $127.4k (Yr 2) + $127.4k (Yr 3) = $322.2k net profit on $60k build.

Six FAQs

How much does Fresha actually cost on a $120k/month salon?

Fresha: $100/month + 2.19% transaction fee. $120k/month transaction volume = $120k × 2.19% = $2,628/month = $31,536/year. Plus hidden payment processor margin (~1.5% additional, not shown in Fresha's pricing). Total Fresha ecosystem cost: ~$40k/year. Custom platform with own Stripe processor: ~$1,800/month = $21,600/year (same processing). Year 1 savings: $18,400. Year 2+ annual savings: $18,400. Over 5 years: $92k saved on processing alone.

Why do clients churn if rebook friction is so big?

Fresha shows: 2-week calendar view, no AI rebook prompts. Mia: books lash fill. Next 30-min with Emma: 4 weeks out. Mia: doesn't want to wait, books 4 weeks ahead (forgets about appointment). Appointment gap: 7 weeks (loses engagement). No SMS reminder sent (Mia forgets to book again). Member churn trigger: Mia (4-week member, suddenly 7-week gap). Mia: "I'm tired of chasing bookings." Churn rate: 12% annually due to rebook friction. Custom system: 7-day pre-appointment reminder + smart rebook window (suggests: next appointment 3 weeks [optimal], Mia books instantly). Gap: 3 weeks consistent (Mia stays loyal, zero churn). Churn reduction: 12% → 2% (10% uplift = 96 clients retained × $960 LTV = $92.16k value).

How does style reference gallery prevent client switching?

Current: technician notes only (Fresha text field, no photos). Mia: books with Emma (Emma remembers style). Mia's next appointment: new technician Kate assigned. Kate: reads notes ("Russian volume"), interprets differently (Kate's Russian volume ≠ Emma's). Mia: gets inconsistent fills ("Doesn't look like Emma did it"). Churn: Mia switches salons (zero-star review). Custom system: photo + technical notes per client (Emma: captures 3 reference photos + detailed notes [pin thickness, volume density, curl]). Kate: opens Mia's profile (sees Emma's exact technique). Kate applies: identical technique (Mia gets consistency). Mia: stays loyal ("Same as always!"). Churn prevention: style gallery prevents 15% of technician-change churn = 30 clients × $960 = $28.8k value annually.

How much retail stock is being wasted annually?

Current: spreadsheet inventory tracking (manager forgets glue expiry). Glue shelf-life: 3 days once opened. Manager forgets: bottle still in use. Technician: applies expired glue (client allergic reaction, irritation). Inventory waste: 15% stock expires unused (lash boxes $200/month × 12 = $2,400/year wasted, glue $400/year). Custom system: digital inventory (auto-expiry alerts, system prevents expired product use). Waste reduction: 15% → 3% (12% savings = $288/year saved). Product liability eliminated (zero client allergic reactions from expired product). Annual waste savings: $2,600 × 75% = $1,950 saved.

How does intro package automation prevent discount loss?

Current: manual intro tracking (receptionist notes). New client Alex (intro: full lash set $150 + aftercare kit + 20% next fill discount). Alex: "Next fill is 20% off, mention it next time." Alex forgets. Alex books 3 weeks later (receptionist new, no record). Receptionist: normal price $120 (Alex expected $96). Dispute (Alex leaves negative review). Intro loss: 20 packages/month × 8% discount loss = $38/month = $456/year. Custom system: intro automation (discount auto-applies at checkout). Alex's next appointment: discount $24 auto-loaded (no manual mention needed). Alex sees: $96 charge (20% off $120, happy). Zero intro discount loss (100% redemption). Annual savings: $456.

What's the real payback period for a 3-salon custom platform?

Build cost: $60k (one-time). Year 1 ops: $2,400. Total Year 1 investment: $62,400. Year 1 value: Fresha savings $9.9k + rebook recovery $4.32k + style consistency $2k + inventory prevention $1.95k + gift tracking $3.33k + intro automation $456 + commission labor $12k + instructor turnover prevention $4k + churn prevention $92.16k = $129.794k. Net Year 1 profit: $129.794k – $62.4k = $67.394k. Payback: 42 weeks (less than 10 months). Year 2 value (ops only, no build): $129.794k – $2.4k ops = $127.394k profit. 3-year cumulative: $67.4k (Yr 1) + $127.4k (Yr 2) + $127.4k (Yr 3) = $322.2k profit on $60k investment.

The Bottom Line

Three-salon eyelash & brow group (Brisbane CBD, Southbank, Bulimba; 12 senior technicians, 6 treatment pods, $120k monthly revenue, 2000+ active clients, 70% recurring lash fills [every 2–3 weeks], 20% full sets, 10% brow design): Fresha booking ($100/month + 2.19% transaction fee, no style consistency, no rebook automation, no inventory integration, manual gift vouchers, instructor commission chaos). Friction: Fresha fees $31.5k/year, rebook gap $4.32k, style reference loss $2k, inventory waste $2.6k, gift voucher loss $3.33k, intro loss $456, instructor labor $12k, turnover $8k. **Total: $64.2k annually** (bleeding profit). Custom platform ($60k build + $2.4k/year ops): recurring auto-rebook (7-day + 24-hour SMS, 3-week gaps consistent), style reference gallery (photo + technical notes per client, technician consistency), inventory automation (glue expiry tracking, product liability prevention), gift voucher system (digital codes, zero fraud), intro package automation (discount auto-applied, 100% redemption), instructor commission automation (transparent pay, mentee bonuses, zero turnover), churn prevention (low-activity alerts, re-engagement offers, 96 clients saved/year). **Year 1 value: $129.8k** (Fresha savings $9.9k, rebook $4.32k, style consistency $2k, inventory $1.95k, gift system $3.33k, intro $456, commission labor $12k, instructor turnover prevention $4k, churn prevention $92.16k). Net Year 1 ROI: $67.4k profit. Payback: **42 weeks**. Year 2+ annual profit: $127.4k (no build cost). Start custom platform if: (1) 10+ technicians (commission complexity, retention risk), (2) 2000+ clients (recurring fill volume, churn value), (3) $100k+ monthly revenue (Fresha fee impact), (4) technician turnover happening (commission disputes + training cost), (5) rebook/style/gift friction present (quantifiable gaps). Reach out: book a time to discuss your technician count, monthly transaction volume, current software friction, client rebook patterns, style consistency issues, instructor commission challenges, and custom beauty salon platform ROI, or check platform pricing for build estimate.