Q1 2026 revenue growth in the CorralData aesthetics customer base.
Aesthetics is growing faster than the headlines suggest. Across 100+ brands running on CorralData, the growth is concentrated among operators with stronger systems, team-wide adoption of data, and tight execution discipline.
- Aesthetics is growing faster than headlines suggest. The CorralData same-basis cohort grew +33% year-over-year in Q1 2026, roughly 5.5x the ~6% AmSpa industry benchmark. The top-performing cohort grew +41%, roughly 7x the industry rate.
- The outperformers share a specific stack profile. They run a modern aesthetics practice management system (PMS) and pair it with at least one specialist execution tool at the lead conversion or patient CRM layer.
- Team-wide AI adoption is associated with materially higher growth. Operators whose teams broadly adopted AI-powered analytics (3+ active users per operator) delivered +17.8% revenue-weighted YoY growth, while operators with fewer than three active users delivered -15.6%. The differentiator we observe is breadth of team adoption, not per-user intensity.
- Wellness is rebalancing, not collapsing. Cohort-wide GLP-1 share dropped from 3.9% to 3.1% while hormone and peptide share expanded by roughly the same magnitude. Operators with concentrated GLP-1 exposure are facing pressure; operators with diversified wellness mix, positioned as longevity and metabolic health rather than weight loss, are capturing the substitution.
- Core aesthetics is accelerating on its own merits. Neurotoxin, filler, laser, and modern device-based body treatments are all growing across the top cohort, independent of the GLP-1 story. Growth is volume-led, with new patient counts growing faster than revenue across the top cohort, and new-patient cohort quality improving at the same time.
- Speed-to-lead tracks with the top performers. Top-cohort operators respond to inbound leads in roughly 2 hours versus the 8-24 hour industry range, and convert leads to booked consults at roughly 42% versus the ~20% industry benchmark.
The industry is growing meaningfully faster than the headlines say.
Three ways of cutting the Q1 2026 cohort data, one consistent signal, and ~5-6x the AmSpa benchmark.
The medical aesthetics industry is growing faster than the headlines suggest.
Across our customers, representing 100+ aesthetics brands, in the analyzable same-basis cohort, Q1 2026 revenue was up 33% year-over-year, roughly 5-6x the AmSpa industry benchmark of ~6%. Nearly 80% of operators grew. Nearly half grew by 20% or more. Our CorralData customers added roughly 22% footprint expansion over the period, through a mix of greenfield builds and rollup acquisitions.
Some of that delta is composition. The CorralData customer base skews toward multi-location, tech-enabled operators that are disproportionately driving industry growth. But even after removing the top decile of growth operators, the median operator's Q1 year-over-year growth was 22%. This is not a story of a few outliers pulling up the average.
The shape of the growth distribution
Nearly half of CorralData customers grew by 20% or more Q1 year-over-year. The top of this distribution includes operators growing 40-150% year-over-year.
A third of operators grew at 5-20%. This is the "steady aesthetics" segment, mature multi-location brands running on their core injectable and laser businesses.
One in five operators were flat or declining.
Four findings shape the rest of this report
Cohort-wide GLP-1 revenue share dropped from 3.9% to 3.1% from Q1 2025 to Q1 2026. Hormone and peptide revenue grew 4.1 percentage points of share in the same period. The substitution is happening in real time.
Neurotoxin, filler, laser, and modern device-based body treatments are accelerating independent of the GLP-1 story. Core neurotoxin transactions showed meaningful acceleration across the top cohort in Q1 2026. Core injectables continue to drive the majority of aesthetics revenue.
Operators in the specialist stack sub-cohort we identified grew Q1 revenue at roughly 7x the industry benchmark, a pattern strong enough to be the dominant observable predictor of growth in this dataset.
Booked-but-not-yet-serviced appointments across the cohort total roughly 391,000, and the implied Q2 2026 run-rate continues the cohort growth trajectory at +15-20% year-over-year, with no early-churn signal at the cohort level even at operators whose Q1 revenue was down year-over-year.
Growth is not evenly distributed.
Wellness is rebalancing. Injectables are accelerating. A 15x productivity gap separates top operators from the cohort floor. Multi-location operators are capturing most of the growth. Allergan owns most of the supplier spend.
Wellness is rebalancing, not collapsing, and the operators getting the mix right are capturing the growth.
Cohort wellness-revenue mix shift, Q1 2025 vs Q1 2026. Each bar shows the change in category share of total revenue, in percentage points. The substitution pattern is consistent across operators.
Percentage-point change in category share of total cohort revenue
The most widely-reported industry narrative right now is that GLP-1 retail at medspas is collapsing as compounded semaglutide and tirzepatide exit pharmacies and brand-name drugs become widely accessible through telehealth. That's directionally accurate, but it understates what's actually happening.
Across our customers, representing 100+ aesthetics brands, GLP-1 revenue share dropped from 3.9% of total revenue in Q1 2025 to 3.1% in Q1 2026, a 0.8-point drop. Meaningful, but not catastrophic at the industry level.
However, the compression is concentrated in operators whose revenue was heavily GLP-1-dependent. Wellness-led operators (defined as those with 30%+ of revenue in wellness categories) show the widest variance of any segment. Operators with concentrated GLP-1 exposure are facing meaningful pressure as the retail GLP-1 market compresses. At the same time, wellness-led operators with a more diversified wellness mix, especially those positioned as longevity and metabolic health, are among the stronger-growing operators in the cohort. The variance within the wellness-led segment is much larger than within pure aesthetics.
What explains the variance?
The winning wellness-led operators substituted hormone and peptide revenue for declining GLP-1 retail. Hormone and peptide services grew to fill the gap. This is the substitution dynamic playing out in real time: GLP-1 as a retail line item is compressing; hormone, peptide, longevity, and diagnostic services are expanding. Operators framing their wellness line as longevity, not weight loss, appear to be capturing the new demand more effectively.
At the cohort level, hormone and peptide revenue share grew 4.1 percentage points in Q1 2026. Vitamin therapy and IV contributed another 1.2 percentage points. Total "medical wellness" revenue (GLP-1 + hormone/peptide + IV/vitamin) is 8.4% of cohort Q1 2026 revenue.
A natural follow-up question is whether wellness-led operators are also expanding into aesthetics services to capture more wallet share per patient. The Q1 2026 cohort data does not yet support that story. Wellness-led operators that grew in Q1 did so by deepening their wellness mix (hormones, peptides, longevity services), not by adding meaningful injectable, laser, or body contouring revenue. In some cases aesthetics revenue contracted year-over-year while wellness mix deepened. Aesthetics expansion may emerge later in the cycle as wellness operators mature their patient base, but it is not a Q1 2026 dynamic.
Wellness is not collapsing. It is rebalancing. Concentration matters more than the category itself, and operators with a diversified wellness mix are capturing the substitution.
Three operator archetypes are pulling apart.
Pure aesthetics is accelerating, integrated is stable, and wellness-led is showing the widest variance of any segment. This framework matters for PE investors, operators, and suppliers. The businesses may look similar on a marketing-materials level, but they behave very differently.
Traditional medspa: neurotoxin-led, filler-heavy, laser and modern body treatments significant, minimal wellness exposure. Wellness accounts for under 5% of revenue. Represents the majority of cohort accounts. Stable and growing. Q1 year-over-year growth ranged from low double-digits to well over 100% at the top end. Centers are expanding. Core neurotoxin transactions are accelerating across the segment. Core injectables remain the most profitable category with the most stable demand dynamics.
Operators where wellness is 10-30% of revenue, integrated into an aesthetics-led business. Hormone/peptide, IV therapy, and weight management alongside injectables and lasers. The most interesting segment strategically. Grew at or above cohort average with considerably more stability than the wellness-led segment. Absorbed the GLP-1 compression by substituting into hormone and peptide revenue. Membership models are common here and appear to provide revenue stability through product-mix shifts.
Operators where wellness (often GLP-1-heavy) is 30%+ of revenue. Some are nearly pure-play wellness, operating as longevity or metabolic health clinics that also offer aesthetics services. Widest variance of any archetype. Operators with concentrated GLP-1 exposure are facing meaningful pressure as the retail GLP-1 market compresses. Operators with more diversified wellness mix, especially those positioned as longevity and metabolic health, are among the stronger growers in the cohort.
Concentration matters more than the category. Concentrated GLP-1 exposure as a single revenue line carries more risk than a diversified wellness mix or wellness integrated into a broader aesthetics portfolio.
Core injectables are still the engine.
Nearly a third of CorralData customer revenue comes from neurotoxin and filler alone. Share of cohort Q1 2026 revenue by service category, blended across the analyzable same-basis cohort.
"Other" is large because modern PMS taxonomies don't cleanly bucket emerging service lines like GLP-1, hormone/peptide, or combo membership services.
The "other" bucket is large because modern medspa PMS category taxonomies don't cleanly bucket emerging service lines. GLP-1s, hormone and peptide services, regenerative services (exosomes, PRP, peptide mesoneedling), newer laser modalities, and membership-linked combo services often land in an "other" or uncategorized bucket. A significant portion of "other" represents the wellness and longevity services discussed above.
Core injectables are still accelerating
Narrative wisdom suggests injectables are a mature category. The data says otherwise. Neurotoxin remains the single largest revenue category at 22.9% of cohort Q1 2026 revenue, and neurotoxin transaction volume is accelerating across the pure-aesthetics archetype. Across the cohort, operators are still adding new neurotoxin patients faster than they're losing existing ones.
Filler sits at 9.6% of cohort Q1 2026 revenue and continues to post healthy growth, though at a slower rate than neurotoxin. Retail skincare holds 5.2% of cohort Q1 2026 revenue, roughly consistent with prior-period share across the same-basis cohort.
A note on the body treatments category
The 2.1% body treatments share reflects a specific category evolution. The traditional cryolipolysis wave (Coolsculpting and similar fat-reduction modalities from 5-10 years ago) has largely matured. What's actually driving growth in this bucket today is a newer generation of devices: muscle-stimulation platforms such as Emsculpt NEO and EmFace, and skin-tightening and resurfacing modalities including Morpheus8 and Sofwave. Operators treating this as a growth category are investing in the modern device portfolio, not the previous generation.
Core injectables are still the engine. Neurotoxin remains the largest single revenue category and is still adding patients faster than it loses them.
The hidden gap: revenue per service hour separates the best medspas from the rest.
Two medspas can post the same monthly revenue and run radically different businesses underneath. The cleanest way to see the difference is revenue per service hour. It captures treatment planning, enhancement upsell, retail attach, room turn time, and pricing power in one number. Across the cohort, it ranges from under $100 to over $1,500 per hour.
Q1 2026 revenue per service hour, medspa cohort
Why this matters in practical terms: a $5M medspa running at $700 per service hour deploys roughly 7,000 service hours to hit that number. The same $5M at $300 per hour requires more than 16,000 hours, more than 2x the staff cost and room turn count. Operators at the top end have meaningfully more cash to reinvest, more flexibility on pricing, and more room to absorb a bad month.
What the top operators have in common
Higher injectable mix. Botox and filler appointments are short, high-margin, and easy to upsell. Operators with neurotoxin and filler at 35%+ of revenue tend to land in the top half of the distribution. Operators leaning heavily on long-format laser or body-contouring services land lower, even when their topline looks healthy.
Treatment planning at the chair. The top operators don't run one-off appointments. They use the visit to plan the next two or three treatments, add an enhancement (filler at the same visit as Botox, a chemical peel add-on, a retinol script), and book the rebook before the patient leaves. The result is more revenue per visit and more visits per patient.
Pricing discipline. Operators competing on rate land at the bottom. Operators positioned as the premium choice in their market and pricing accordingly land near the top. Discounting and intro-pricing campaigns drag the average down quickly.
Tight time turns. A 30-minute Botox visit that takes 50 minutes (waiting, slow checkout, casual room turn) cuts revenue per hour by a third. Operators with disciplined patient flow generate meaningfully more revenue from the same provider hours.
The bottom of the distribution: who lands here and why
The lowest revenue-per-hour brands in the cohort tend to share one of three patterns: heavy laser or longer-format service mix where the appointment is long and the per-minute revenue is modest, aggressive new-patient promotional pricing that pulls the average down, or under-utilized rooms where providers are scheduled but not consistently booked through the day. None of these are death sentences, but they all eat productivity in a way that compounds.
Operating culture, not scale
The top revenue-per-hour brand in the cohort is part of a multi-location group. The bottom brand is also part of a multi-location group. Productivity discipline shows up as an operating-culture variable, not a scale variable. Single-location operators appear in both the top and bottom quartiles. The lever is how the team runs the day, not how big the business is.
The productivity gap is operating-culture, not scale. Single-location and multi-location operators appear at both the top and bottom of the distribution.
The top of the growth distribution is multi-location operators growing same-store and adding footprint simultaneously.
Center expansion explains a meaningful share of top-line growth, but not all of it. Several top operators added centers, but their growth exceeds what center additions alone would explain, showing same-store growth.
The correlation between growth and operator type is messy. Pure aesthetics, integrated, and wellness-led operators all appear in the top tier. The determinant of growth at this level appears to be operator execution, not segment.
The highest-growth operators in dollar terms are multi-location. This reinforces the PE thesis around multi-site aesthetics: operators with a functioning multi-location playbook outperform in absolute dollar terms, even against operators running excellent single-site economics.
Multi-location operators expanded footprint roughly 22% in a single year.
Mostly through greenfield and rollup, not acquisitions of troubled operators.
Starting point for the year-over-year footprint comparison.
+22% YoY through a mix of greenfield builds and rollup acquisitions.
The cohort includes a mix of regional multi-location and multi-state aesthetics groups of varying sizes. Center additions across individual operators ranged widely in the period, with some operators adding substantial footprint through acquisition and others through targeted greenfield expansion.
These additions come through both greenfield builds and acquisition. PE-backed operators in the cohort are more likely to grow through acquisition; founder-led operators lean more toward greenfield. Both are contributing to industry consolidation.
Initial directional read: larger multi-location operators appear to be growing same-store in the 8-15% range, with incremental centers adding 10-15 percentage points to total growth. A more precise same-store decomposition requires center-level revenue segmentation, which is a future research extension.
Supplier spend is highly concentrated, with Allergan holding the dominant position.
Directional cohort wallet share by aesthetic supplier brand. Relative ordering is consistent across the multi-location operators in the cohort. Individual operator mix varies based on geography, patient base, and formulary decisions.
Prescription aesthetics is a highly concentrated supplier market, and the cohort confirms this at scale.
Allergan holds the dominant share of cohort supplier COGS, driven by the Botox and Juvéderm portfolios. Individual operator share varies based on injector preference and corporate volume agreements, but the dominant position is consistent across the multi-location operators in the cohort.
Galderma is the clear #2 supplier in the cohort. Dysport, Sculptra, and the Restylane family (including Kysse, Lyft, and Eyelight) make up Galderma's footprint.
Revance is the strongest challenger in the data, with meaningful footholds at several accounts. Daxxify and the RHA filler line are visible challenger positions, and at some operators Revance accounts for a notably larger share than the cohort average.
Merz holds an established niche position with Xeomin, Radiesse, and Belotero.
The three largest injectable suppliers (Allergan, Galderma, Revance) together hold the substantial majority of cohort supplier spend. Regenerative medicine suppliers such as Benev and exosome brands are still a small share of cohort injectable spend at this point, though the category is evolving quickly and worth watching.
A deeper cohort supplier analysis, including per-category neurotoxin and filler brand breakdowns, is the subject of a forthcoming companion report on aesthetics supplier economics.
Supplier spend is highly concentrated. Injectable portfolios continue to drive a significant share of cohort economics, and challenger brands are gaining visibility in specific accounts.
The operators capturing outsized growth share a specific operating pattern.
Tech stack, AI adoption, and marketing speed all point the same way. Six recognizable operating habits separate the operators pulling ahead from the rest of the field.
A specific combination of CorralData plus specialist execution software cleanly separated the outperformers.
When our CorralData customers are segmented by software stack composition, one pattern stands out in the data. Within a sub-cohort of operators running a modern aesthetics PMS and paired with at least one specialist execution tool at the lead conversion or patient CRM layer, blended Q1 growth came in at +41% YoY, nearly 7x the industry benchmark.
Across the broader analyzable same-basis cohort, blended growth was +33%, and the directional signal holds even under the broadest framing across all CorralData aesthetics customers, where blended Q1 growth still ran at roughly 2.5x the industry rate. The spread widens as the cohort definition tightens.
Q1 2026 YoY revenue growth by cohort
Four structural indicators underneath the headline number
A blended growth number on its own is a weak signal. It can be driven by a couple of outliers. To test whether the pattern was structural or coincidental, we examined four additional structural indicators across the cohorts. All four point in the same direction as the +41% headline.
Standard deviation of Q1 growth rates inside the specialist stack cohort was meaningfully lower than in the comparison cohort. Tighter variance suggests the pattern is reproducible rather than driven by one or two outliers.
Top-cohort operators grew unique patient counts meaningfully faster than revenue in Q1 2026. That ratio is consistent with the +41% coming from new patient acquisition rather than pricing inflation or existing-patient spend expansion.
Top-performing operators in the cohort converted inbound leads at roughly 2x published industry benchmarks, with faster time-to-contact as the most observable driver.
Booked-but-not-yet-serviced appointments imply Q2 2026 cohort revenue continuing at +15-20% YoY, with healthy forward bookings even at operators whose Q1 revenue declined. The +41% isn't a one-quarter anomaly, the next quarter's revenue is already on the books.
Taken together, the specialist stack cohort grew faster, grew with tighter variance, acquired more new patients, converted inbound at higher rates, and shows no churn signal heading into Q2. Four independent structural indicators pointing the same direction as the headline number is what makes the +41% a finding rather than a coincidence.
These operators aren't running on legacy BI
The operators in the +41% cohort aren't moving this fast because they have better dashboards. They're moving this fast because they pivoted to leveraging their data for action. Legacy BI platforms and traditional analytics stacks were built for reporting: an analyst builds a dashboard, shares a link, and hopes someone looks at it next Tuesday. When the operator wants a different cut of the data, they file a ticket with the data team and wait. By the time the report comes back, the decision window has closed.
What's different about the outperformers is that they've restructured how their teams work with data. Instead of waiting for a report, the whole team can ask a question, pivot the data, and act on the answer in the same hour. That shift, from analytics as a reporting function to analytics as an operating surface, is what the data suggests separates this cohort from the rest.
Paired with specialist execution software at one or more specific layers
On top of that operating shift, every operator in the +41% cohort pairs CorralData with at least one specialist execution tool at one of two specific operational layers: lead conversion, or patient CRM and lifecycle. These are the two surfaces where economic leakage in a typical aesthetics business tends to concentrate: revenue leakage at the lead conversion layer, and patient lifetime value compression at the CRM layer.
CorralData gives the operator the visibility to see leakage across both layers in real time. Specialist execution tools at each layer give the team the surface to fix what CorralData surfaces. Purpose-built patient CRM platforms in particular show up at a disproportionate share of the top performers. Operators running one post materially stronger retention curves and lifetime patient value than operators running general-purpose CRM tooling.
The pattern is consistent across the specialist stack sub-cohort: the +41% group has restructured how their teams work with data and is paired with a specialist execution tool at the lead conversion or patient CRM layer. The more of those specialist layers are in place, the more reliably the pattern holds.
Five layers appear consistently in the outperforming cohort
The top-performing cohort does not share a single vendor stack. Practice management systems and finance systems vary by vertical and scale. What they do share is a functional decomposition. Each of the five operational layers below is handled by a tool purpose-built for that layer, rather than by an all-in-one platform attempting to cover multiple layers. Vendors called out below are the platforms that appear most consistently in the outperformer cohort; other platforms serve each layer as well.
The system running daily operations: scheduling, charting, checkout. The outperforming cohort runs a modern, aesthetics-oriented practice management system.
Inbound leads (phone calls, web forms, text messages) are where revenue is won or lost before a patient ever walks in the door. A specialist platform at this layer captures, scores, and routes every inbound lead, and measures which ones convert to booked appointments. This is the single largest source of observable lead-to-booking conversion lift in the cohort. Liine appears most consistently in the outperformer cohort at this layer. Across the top-performer subset, inbound lead response times run closer to ~2 hours than the 8-24 hour industry range.
Once a patient is in the door, a purpose-built aesthetics CRM owns treatment planning, follow-up cadence, retention workflows, and long-term patient value. Aesthetix CRM appears most consistently across the top-performing operators in the dataset. Operators with a purpose-built CRM see roughly 1.5x to 2x the visit frequency of operators using general-purpose CRM tooling.
Faster-growing multi-location and PE-backed operators in the dataset run purpose-built general ledgers, including Sage Intacct and NetSuite. QuickBooks remains appropriate for smaller single-entity operators; the inflection point typically arrives when the business crosses into multi-entity or multi-location consolidation.
Ties the four layers above into one operating picture. CorralData is the unified intelligence layer across the cohort in this analysis.
What sets the outperformers apart is not what they bought. It is how their teams use it. Specialist execution tools at the lead conversion and patient CRM layers, paired with a unified intelligence layer the team actually uses, is the pattern.
When the team uses the AI, the business grows. When they don't, it doesn't.
Every customer in this analysis has access to CorralData's AI-powered analytics. They are paying for it. The question is whether their team uses it. The answer is decisive: when the team uses it, the business grows. When they don't, it doesn't.
The headline
Across the cohort, operators with three or more active AI-platform users in Q1 2026 delivered +17.8% revenue-weighted year-over-year growth. Operators with fewer than three active users delivered -15.6%.
The differentiator we observe is breadth of team adoption, not per-user intensity. The teams that won this quarter were teams where multiple people sat with the data, not teams where one person occasionally checked it.
Revenue-weighted Q1 2026 YoY growth. Top of the cohort. Team-wide adoption is the operating signal.
Revenue-weighted Q1 2026 YoY growth. Roughly the same access, materially different outcome.
What "team-wide adoption" actually looks like
Team-wide adoption isn't an analyst writing a query and circulating a chart. It's a finance lead, an operations lead, and a marketing lead each pulling the data they need at the moment they need it, often inside the same week. It's a clinic manager pulling provider productivity at the start of every shift. It's a marketing lead checking lead-source ROI before approving the next campaign. It's the GM checking same-store revenue against last quarter on Monday morning.
The 3-user threshold matters because it's the point at which one team member's absence stops being the bottleneck. With one user, the data work stops when that person goes on vacation. With three or more, data-led decisions become a routine part of how the team operates rather than a project owned by an individual.
Speed-to-lead and conversion discipline are the most observable differentiators.
The top-cohort operators we examined respond to inbound leads in roughly 2 hours versus the 8-24 hour industry range, and convert those leads to booked consults at roughly 42% versus the ~20% industry benchmark.
Top-cohort lead funnel, illustrative
Paid media efficiency, top cohort vs cohort median
The cost-per-booked-consult gap is consistent with the conversion-rate gap: when more leads convert, the same ad spend produces more booked consults, so the cost per booked consult drops. The compounding effect is that top-cohort operators can profitably bid higher in paid channels, which earns more impression share, which feeds the cycle.
Where the speed-to-lead advantage comes from
It is operational, not technological. Top-cohort operators staff lead response as a dedicated function, not an afterthought handled by whichever front-desk staff is free. They route inbound leads to a specific person or platform within minutes, follow up via the patient's preferred channel rather than defaulting to phone, and measure response time as a daily KPI rather than a quarterly review item.
The marketing efficiency gap is structural. Top-cohort operators have built lead response into their operating routine, and the funnel math compounds from there.
Six recognizable habits separate the operators pulling ahead.
Across the top-cohort operators we examined, six operating habits show up consistently. None of them are exotic. All of them are operational discipline rather than buying decisions, and they compound when stacked together.
Three or more team members across finance, operations, and marketing routinely interact with the analytics platform. Decisions are made with the data on screen, not with the data summarized after the fact.
Inbound leads are routed within minutes, contacted within a couple of hours, and response time is measured as a daily KPI, not a quarterly review item.
The visit isn't a one-off. The provider plans the next two or three treatments, books the rebook before the patient leaves, and adds the right enhancement at the right moment.
Discounting and intro-pricing campaigns drag the average down quickly. The top operators position as the premium choice in their market and price accordingly. They give up volume at the bottom of the price ladder to protect contribution at the top.
Wellness-led operators that grew in Q1 did so by deepening the wellness portfolio, hormones, peptides, longevity services, IV therapy, rather than concentrating on one retail GLP-1 line item.
A modern PMS for the system of record, a specialist tool for lead conversion, a purpose-built CRM for patient lifecycle, a real GL for finance, and a unified intelligence layer the team actually uses. The combination compounds.
The forward book is healthy, even where Q1 wasn't.
Booked-but-not-yet-serviced appointments imply Q2 2026 cohort revenue continuing at +15-20% YoY, and the consult pipeline at the top cohort is full enough to keep them ahead of the rest of the field.
The forward book points to continued growth, with no early-churn signal.
Cohort-wide booked-but-not-yet-serviced appointments total roughly 391,000. The implied Q2 2026 revenue run-rate continues the cohort growth trajectory at +15-20% year-over-year.
Cohort-wide appointments scheduled but not yet serviced as of period close. Continues into Q2 with no break in cadence.
Forward-book run-rate continues the cohort growth trajectory. The next quarter's revenue is already on the books.
Even at operators whose Q1 revenue was down year-over-year, the forward book at period close did not show early signs of patient drop-off. The down-quarter operators are still booking patients into Q2 at a healthy rate.
The top-performing operators are entering Q2 with consult pipelines, lead-to-booking conversion rates, and provider utilization that match or exceed Q1 levels. The +41% cohort isn't slowing down.
Q1 2026 was not a one-quarter result. The forward book points to continued growth, with the top cohort entering Q2 ahead of the rest of the field and no observable churn signal at the cohort level.
Frequently asked questions
How does CorralData define the "top-cohort" in this benchmark?
The top-cohort is the sub-segment of CorralData customers running a modern aesthetics practice management system paired with at least one specialist execution tool at the lead conversion or patient CRM layer. This sub-cohort delivered +41% YoY revenue growth in Q1 2026, roughly 7x the AmSpa industry benchmark of ~6%.
Is the +33% same-basis cohort growth representative of the medspa industry?
It is representative of the analyzable cohort of CorralData customers, which skews toward multi-location, tech-enabled aesthetics operators. The cohort is not a randomly-sampled cross-section of all medspas. The relevant comparison is to the AmSpa industry benchmark of ~6% growth, against which the cohort grew at roughly 5-6x the industry rate.
How is GLP-1 revenue compression affecting the broader cohort?
Cohort-wide GLP-1 revenue share dropped from 3.9% to 3.1% from Q1 2025 to Q1 2026, a 0.8 percentage-point decline. The compression is concentrated in operators with high GLP-1 exposure. Operators with diversified wellness mix (hormone, peptide, IV, longevity services) substituted into the gap.
What's the difference between "wellness-led" and "wellness-integrated" operators?
Wellness-led operators have 30%+ of revenue in wellness categories (often GLP-1-heavy). Wellness-integrated operators have 10-30% wellness mix integrated into an aesthetics-led business. The wellness-integrated archetype showed the most stable Q1 2026 performance; the wellness-led archetype showed the widest variance, with the strongest performers positioned as longevity and metabolic health rather than weight loss.
Why is core injectable revenue accelerating in Q1 2026?
Neurotoxin and filler are not mature categories. Across the top cohort, neurotoxin transaction volume is accelerating, new patient counts are growing faster than revenue, and core injectables continue to drive the largest share of profitable revenue. The acceleration is patient-led rather than price-led.
What does "team-wide AI adoption" mean in this report?
Three or more active users on the analytics platform at an operator in Q1 2026, across roles like finance, operations, and marketing. Operators meeting that threshold delivered +17.8% revenue-weighted YoY growth in Q1 2026. Operators below that threshold delivered -15.6%. The differentiator is breadth of team adoption, not per-user intensity.
What's the speed-to-lead benchmark for top operators?
Top-cohort operators in the dataset respond to inbound leads in roughly 2 hours versus the 8-24 hour industry range, and convert leads to booked consults at roughly 42% versus the ~20% industry benchmark. Speed-to-lead is staffed as a dedicated function, not handled ad-hoc by available front-desk staff.
Are forward indicators showing any churn or slowdown signal?
No. Cohort-wide booked-but-not-yet-serviced appointments total roughly 391,000 at period close. The implied Q2 2026 run-rate continues at +15-20% YoY growth. Even operators whose Q1 revenue was down year-over-year are showing healthy forward books, with no early-churn signal at the cohort level.
How this benchmark was constructed.
Data source
This benchmark is constructed from anonymized Q1 2025 and Q1 2026 revenue, transaction, and operations data of 100+ medical aesthetics brands running on CorralData. All operator-level data is aggregated and de-identified before analysis.
Same-basis cohort definition
The "same-basis cohort" includes operators with continuous CorralData data coverage across both Q1 2025 and Q1 2026. Operators that joined CorralData mid-period or had material reporting gaps in either period are excluded from the same-basis comparison. Reported Q1 YoY growth rates use this same-basis definition unless otherwise noted.
Top-cohort definition
The "top-cohort" is the sub-segment of the same-basis cohort running a modern aesthetics practice management system paired with at least one specialist execution tool at the lead conversion or patient CRM layer. This sub-cohort definition is structural, based on tech-stack composition, not selected on outcome. The +41% YoY result is the blended growth of operators meeting that structural definition.
Revenue normalization
Reported revenue figures are normalized to a same-basis comparison: operators that opened or closed centers mid-period are aligned to comparable footprint, and one-time revenue events (asset sales, settlement payments, reclassifications) are excluded from the cohort comparison.
Service category taxonomy
Service categorization is based on the host PMS taxonomy. Where PMS taxonomies do not cleanly bucket emerging services (GLP-1, hormone/peptide, regenerative, modern device-based body treatments, membership-linked combo services), revenue lands in an "other or uncategorized" bucket. The 47.5% "other" share reflects this taxonomy limitation.
Supplier wallet-share methodology
Supplier wallet share is reported as directional rather than precise percentage share. Relative ordering across the largest suppliers (Allergan, Galderma, Revance, Merz) is consistent across the multi-location operators in the cohort. Individual operator wallet share varies based on geography, patient base, injector preference, and corporate volume agreements.
What this benchmark is not
This is not a randomly-sampled cross-section of the medical aesthetics industry. The CorralData customer base skews toward multi-location, tech-enabled operators. The relevant industry comparison is the AmSpa benchmark, against which the same-basis cohort grew at 5-6x the industry rate.
Causal claims
Where this report identifies associations between operating practices (team-wide AI adoption, specialist stack composition, speed-to-lead) and growth outcomes, those associations are reliable enough to act on but cannot be cleanly separated from other operating habits common to high-performing operators. We have flagged the multi-factor nature of these associations where relevant, especially in the AI-adoption section.