153 raw respondents, 8 excluded, 5 adjusted, multi-location revenue adjusted (per-location × locations). n=142 classified.
| Metric | Micro | Emerging | Scaling | Established |
|---|---|---|---|---|
| Count | 35 (24.6%) | 40 (28.2%) | 29 (20.4%) | 38 (26.8%) |
| Mean Revenue (adj) | $18K | $56K | $189K | $291K |
| Mean Providers | 1.7 | 2.7 | 4.1 | 8.0 |
| Mean Non-Rev Staff | 1.1 | 1.4 | 2.3 | 4.3 |
| Mean Owner Rev % | 80% | 51% | 51% | 22% |
| Mean Locations | 1.0 | 1.0 | 1.6 | 2.0 |
| Decision Score | 2.2/5 | 2.7/5 | 2.9/5 | 3.8/5 |
Monthly revenue (adjusted: per-location × locations for multi-site practices). Micro clusters under $50K; Emerging spans $20-100K; Scaling covers $20-250K+; Established is exclusively $100K+.
The primary discriminator. Note the dramatic shift from Micro (>75% dominant) to Established (<25% dominant).
As team size grows, the owner's share of revenue shrinks. This single variable explains most of the behavioral differences between segments.
Decision-making shifts from intuition to data as practices grow. Micro clinicians trust their gut; Established practices demand dashboards and team analysis.
Three levels: Gut + Glance (intuitive), Self-review (transitioning), Dashboards + Team (data-driven)
Micro is 69% gut+glance — nearly 7 in 10 run on intuition. Established flips to 61% dashboards+team. Scaling still has 45% on gut+glance despite running $189K/mo practices — they've outgrown their decision infrastructure.
What keeps practice owners up at night — full distribution adding to 100%. New patients dominates everywhere but dilutes as complexity grows.
Micro's pain is singular: 60% say new patients. Established pain is distributed across 7 categories. Provider turnover as a churn driver climbs: 6% (Micro) → 25% (Emerging) → 38% (Scaling) → 42% (Established). Turnover scales with practice size — larger practices have more providers to lose.
Growth ambition scales with practice size. Hiring intent climbs: 31% → 48% → 62% → 71%. Scaling has the highest expansion intent (48% planning new location).
Hiring intent climbs: 31% → 48% → 62% → 71%. Selling interest peaks at Established (18%) — once the owner has stepped back, exit becomes real. Scaling has the highest expansion intent (48% planning new location) but lowest selling interest (3%).
k-Means cluster analysis (n=142) independently validates the 4-segment model. All features standardized before clustering.
Mann-Whitney U test. Every segment boundary is statistically significant on core practice metrics.
| Feature | Micro → Emerging | Emerging → Scaling | Scaling → Established |
|---|---|---|---|
| Revenue (adj) | *** p<0.001 | *** p<0.001 | *** p<0.001 |
| Providers | *** p<0.001 | *** p<0.001 | *** p<0.001 |
| Owner Rev % | *** p<0.001 | ns | *** p<0.001 |
Unsupervised k-means clustering independently recovers the same 4-segment structure. Every segment boundary is statistically significant (p<0.001) on revenue and provider count. Clusters are perfectly stable across repeated runs (std=0.0019). The top two data axes — practice size and owner-dependency — explain 66% of all variation, confirming these are the right dimensions to segment on.