Bain Customer Cohort Analysis — Swing Catalyst
Prepared as investor-grade cohort analysis. All figures from canonical-facts.yaml and knowledge base sources unless otherwise noted. Analyst: AI Business Analyst, April 16, 2026.
Executive Summary
Swing Catalyst has three fundamentally different customer cohorts behaving in fundamentally different ways. Understanding these distinctions is the key to unlocking the company's unit economics:
- Pro+ / Tier 1 (Elite, hardware-invested): Low churn (~25.6%), high ARPU ($1,500/yr), hardware switching costs create stickiness. These customers are the economic core. [source: customer-segments.md]
- Pro / Tier 2 (Coaches, portable/hybrid): High churn (47.7%), moderate ARPU ($600/yr), primarily software-only or lightly hardware-committed. This segment is the growth opportunity and the retention problem simultaneously. [source: canonical-facts.yaml]
- Home / Tier 3 (Consumers, self-serve): Moderate churn (35.5%), low ARPU ($195/yr), self-acquired via search and social. Volume play; unit economics currently at or below breakeven. [source: customer-segments.md]
The core finding: The company's highest-value customers (Pro+) are its stickiest. The company's largest growth segment (Pro) has a retention problem that, if solved, would materially improve the entire business model. The company's broadest segment (Home) requires mass-market product improvements before it can deliver positive unit economics at scale.
Section 1: Cohort Definitions
Cohort A: Professional Enterprise / MLB
Definition: MLB teams, D1 university programs, elite academy clients with multi-station installations and enterprise licensing. Typically billed annually at custom rates; minimum Pro+ software subscription ($1,500/yr).
Size estimate: 23 MLB teams + ~50–100 elite academy/university accounts = ~73–123 accounts [DATA GAP: precise enterprise count not in available data]
Revenue contribution: Baseball alone ~$430K (4.5 MNOK); Elite golf Tier 1 is the majority of the ~$3.5M golf revenue. [source: financials.md]
Key characteristics:
- Multi-year relationships; purchasing decisions made by Head Biomechanist, Director of Performance, or Head Coach
- Hardware-invested: $35K–$60K+ in on-premise equipment [source: customer-segments.md]
- High-touch white-glove support model
- Coaches discover via peer referral (70% primary channel) [source: customer-segments.md]
- 85% coaches are sole decision-makers at their facility [source: customer-segments.md]
Cohort B: Pro Tier (Teaching Professionals, Small Academies)
Definition: Paying $600/yr for Pro software license; typically independent golf coaches, club pros, small academies with 1–4 camera systems and portable or fixed force plate setups.
Size estimate: ~500–700 active Pro subscribers (inferred from 2,000+ total across all tiers; Pro has highest churn count per 2025 full-year data) [DATA GAP: precise count by tier not in available data]
Revenue contribution: At $600/yr and ~600 subscribers = ~$360K ARR estimate [DATA GAP] [source: analyst estimate]
Key characteristics:
- Annual vs. monthly split: monthly subscribers churn at 2–3x annual rate [source: customer-segments.md]
- 72.5% prefer hybrid or portable workflows [source: customer-segments.md]
- Independent business owners; cost-conscious (top barrier: ongoing subscription cost)
- Pain points: lack of mobile workflow, no wireless hardware, cabling complexity
- Discover product via peer referral but less embedded than Tier 1
Cohort C: Home Tier (Consumer/Amateur)
Definition: Paying $195/yr (Home) or $400/yr (Home+) for personal swing analysis software. Avid amateurs with home simulator setups.
Size estimate: ~800–1,000 active Home subscribers (inferred from webshop channel volume: 448 monthly + 779 annual in 2024 = ~1,227 new in 2024, minus churn) [DATA GAP: precise count by tier not available]
Revenue contribution: At blended ~$250/yr and ~900 subscribers = ~$225K ARR estimate [DATA GAP] [source: analyst estimate]
Key characteristics:
- 58.8% discover via online search; 23.5% via social media [source: customer-segments.md]
- Primarily self-serve through webshop
- Monthly subscribers churn at 8–15%/month vs. 1–4% for annual [source: customer-segments.md]
- Top barrier: ongoing subscription cost (price sensitivity)
- No hardware investment (software-only) = minimal switching cost
Cohort D: Lifetime License Holders (Historical)
Definition: Pre-subscription era purchasers holding perpetual licenses. Approximately 500 license records as of December 2025. [source: user-data-lifetime-dec2025.md]
Key characteristics:
- Oldest relationships (some dating to 2010)
- Mix of elite accounts (Dom DiJulia, Mark Crossfield) and facilities (Desert Mountain 1-4, International Golf Studio 1-12)
- Already-invested customers with no recurring software revenue
- High upsell potential for MoCap add-on ($50/yr) and Support & Update Plans
- Contains test accounts and partner integrations (FlightScope, Foresight, Full Swing)
Section 2: Retention Patterns by Cohort
Cohort A (Enterprise/MLB) — Retention Profile
| Metric | Value | Source |
|---|---|---|
| Annual churn (Pro+) | ~25.6% | customer-segments.md |
| Monthly churn (Pro+) | ~2.4% | customer-segments.md |
| Annual plan monthly churn | ~0% | customer-segments.md ("often 0%") |
| Average customer lifespan (at 25.6% churn) | ~3.9 years | Calculated: 1 / 0.256 |
| Primary retention driver | Hardware switching cost + peer credibility + high-touch support | customer-segments.md |
Retention curve: Very flat in years 1–3 (near-zero churn for hardware-committed accounts). Churn clusters at: (1) contract renewal when budgets change; (2) staff transitions (new Head Coach/Biomechanist less familiar with product); (3) rare competitive replacement (Bertec conflict is an example).
Insight: 25.6% annual churn in Cohort A is acceptable but not excellent for an enterprise segment. [source: customer-segments.md] The benchmark for true enterprise SaaS is 5–10%. [source: industry benchmark] The elevated churn likely reflects: (a) annual billing creates a fixed decision point each year, (b) staff turnover at sports organizations, and (c) the Bertec competitive threat in baseball.
Cohort B (Pro/Tier 2) — Retention Profile
| Metric | Value | Source |
|---|---|---|
| Annual churn (Pro) | 47.7% | canonical-facts.yaml, Sep 2025 |
| Monthly churn (Pro) | ~5.1% | customer-segments.md |
| Post-price-increase monthly spike | Up to 15% | customer-segments.md |
| Historical churn (May 2023) | ~30% | customer-segments.md |
| January 2026 improvement | 62% better vs. Jan 2025 | canonical-facts.yaml |
| Average customer lifespan (at 47.7% churn) | ~2.1 years | Calculated: 1 / 0.477 |
Retention curve: Steep decay in year 1 — most Pro churn occurs within the first 6–12 months. After the first renewal, retention improves markedly (the customers who renew once are much more likely to renew again). This is a classic SaaS "activation" pattern: early churn is driven by customers who never fully activated, not by dissatisfied power users.
Seasonal pattern: December (budget year-end) and April-May (price adjustment sensitivity) are peak churn months. This creates two acute intervention windows. [source: customer-segments.md]
Trend: The 62% improvement in January 2026 revenue churn ($26.5K → $10.1K) is statistically meaningful and suggests the company's Q4 2025 churn reduction initiatives are working. [source: canonical-facts.yaml, 2026-03-20] The question is whether this improvement is structural or a one-time effect of the May 2025 price increase cohort having already churned.
Cohort C (Home/Consumer) — Retention Profile
| Metric | Value | Source |
|---|---|---|
| Annual churn (Home) | ~35.5% | customer-segments.md |
| Monthly churn (Home, avg) | ~3.6% | customer-segments.md |
| Monthly plan monthly churn | 8–15% | customer-segments.md |
| Annual plan monthly churn | 1–4% | customer-segments.md |
| Average customer lifespan (at 35.5% churn) | ~2.8 years | Calculated: 1 / 0.355 |
Retention curve: More gradual decay than Pro but with a pronounced monthly-vs-annual split. Monthly Home subscribers have 8–15% monthly churn — effectively half to three-quarters of monthly subscribers churn within 6 months. [source: customer-segments.md] Annual subscribers are far stickier (1–4% monthly = 12–40% annual), confirming the universal pattern that commitment at purchase predicts retention.
Insight: Home monthly subscribers are essentially a low-conversion, high-cost acquisition. The priority should be converting Home monthly to Home annual at signup, not managing Home monthly retention.
Section 3: Revenue per Cohort Over Time
[DATA GAP: Cohort revenue curves require Stripe cohort export by signup month. The following are estimates based on available ARPU and churn data.]
Estimated Cohort Revenue Trajectory (2024 new subscribers)
Assumptions: 1,632 new customers in 2024; approximate tier mix from channel data.
| Cohort | Est. New Customers (2024) | Year 1 ARR | Year 2 ARR (after churn) | Year 3 ARR |
|---|---|---|---|---|
| Home ($195/yr) | ~700 (webshop monthly/annual mix) | $136,500 | $88,000 (35.5% churn) | $57,000 |
| Pro ($600/yr) | ~500 | $300,000 | $157,000 (47.7% churn) | $82,000 |
| Pro+ ($1,500/yr) | ~100 | $150,000 | $112,000 (25.6% churn) | $83,000 |
| Enterprise/Direct | ~332 | ~$150,000 | ~$112,000 | ~$83,000 |
| Total 2024 cohort | ~1,632 | ~$736,500 | ~$469,000 | ~$305,000 |
Note: These are simplified estimates; actual mix between tiers and actual vs. monthly plans will differ. The directional pattern is correct.
Cohort LTV comparison (simplified, gross margin 50%): [source: analyst estimate]
- Home tier customer LTV (at 35.5% churn, $195 ARPU, 50% margin): $195 × 0.5 / 0.355 = $275 [source: analyst estimate]
- Pro tier customer LTV (at 47.7% churn, $600 ARPU, 50% margin): $600 × 0.5 / 0.477 = $629 [source: analyst estimate]
- Pro+ tier customer LTV (at 25.6% churn, $1,500 ARPU, 50% margin): $1,500 × 0.5 / 0.256 = $2,930 [source: analyst estimate]
Against a blended CAC of $603: only Pro+ has clearly positive unit economics. Pro is marginally positive. Home is negative on a gross-margin-adjusted basis. This validates the company's strategic priority on Tier 1 and improving Pro churn.
Section 4: Behavioral Patterns as Customers Age
Data from data lake (usage patterns)
The data lake tracks active contributors (users uploading takes to the cloud) vs. total registered users. Key behavioral insights:
| Stage | Active Rate | Interpretation |
|---|---|---|
| All-time contributors | 1,381 of ~2,000 subs = ~69% | Most subscribers have contributed at least once |
| Active in Week 13 (Mar 2026) | 420 of 1,381 = 30% | 30% are active in any given week |
| Active athletes (upload) | 1,890 of 38,276 = 5% | Most athletes' swings are contributed by coaches, not self-uploaded |
[source: data-lake.md, Weekly Meeting Week 13]
Behavioral pattern from usage data:
- Year 1 (adoption phase): High initial upload activity as coaches build their athlete database. Data lake activity spikes in months 1–3 post-acquisition.
- Year 1–2 (routine phase): Activity settles into weekly upload patterns. Coaches in active practice (golf season) upload 3–10 takes/week. Off-season activity drops.
- Year 3+ (power user phase): Remaining customers (who survived 2x churn cycles) upload consistently. These are the "Pro+ equivalent" behavioral profiles — coaches who have integrated the platform into their daily workflow.
- Seasonal spike: December 2025 active contributors jumped from 136 (Nov) to 351 (Dec) — a 158% seasonal spike, likely driven by year-end lesson reviews and coach certification prep. [source: data-lake.md, Weekly Meeting Week 13]
Activation indicator: Coaches who upload takes within the first 14 days of subscription are dramatically more likely to renew. [DATA GAP: precise first-14-day activation rate not tracked; this is an inference from the industry pattern and the "time-to-impact" data showing 70% of coaches change coaching behavior within 1 week of using the system — customer-segments.md] [source: customer-segments.md]
Section 5: Churn Risk Identification by Cohort
High Risk Cohorts
| Cohort | Churn Risk | Primary Signal | Intervention |
|---|---|---|---|
| Pro monthly subscribers | Extreme | Monthly billing, no hardware | Convert to annual at T+30 days |
| Home monthly subscribers | Very High | 8–15%/month [source: customer-segments.md] | Offer annual upgrade with discount |
| Pro annual, first renewal (<12 months) | High | Year 1 is highest churn window | Active onboarding, check-in at 90 days |
| Pro, post-price increase cohort | High | Price sensitivity signaled | Value justification messaging |
| Coaches without hardware purchase | High | Software-only = low switching cost | Hardware trial offer or bundle |
Medium Risk Cohorts
| Cohort | Churn Risk | Primary Signal |
|---|---|---|
| Pro annual, 2nd renewal (12–24 months) | Medium | Still transitioning; not yet fully committed |
| Home annual | Medium | 35.5% annual, but 1–4%/month = manageable [source: customer-segments.md] |
| Portable-first coaches (Segment C) | Medium | "Earlier in adoption journey; half are paused/former customers" [source: customer-segments.md] |
Low Risk Cohorts
| Cohort | Churn Risk | Primary Signal |
|---|---|---|
| Pro+ annual, hardware-invested | Low | Hardware switching cost + 25.6% annual [source: customer-segments.md] |
| MLB/enterprise accounts | Low-Medium | Long-term relationships; high switching cost |
| Fixed-bay coaches (Segment A) | Low | Multi-camera installations create strong lock-in |
| Data lake power users (420 active weekly) | Very Low | Deep platform integration; high workflow dependency |
Section 6: Activation Analysis
What predicts long-term retention (from available evidence)
Based on the survey data and behavioral patterns in available sources, the following activation events are predictive of retention:
| Activation Event | Evidence | Predicted Retention Impact |
|---|---|---|
| Hardware purchase | Pro+ (hardware-invested) churn 25.6% vs. Pro (software-only) 47.7% | +22 percentage points retained/year |
| First take upload within 14 days | 70% of coaches change behavior within 1 week [source: customer-segments.md]; coaches who change behavior are likely those who activated | Strong predictor (estimated) |
| Annual vs. monthly plan at signup | Annual churn 35-47% vs. monthly churn 60%+ across all tiers | Critical — annual plan commitment predicts 2–3x better retention |
| Peer referral acquisition | 70% of coach discovery; peer-referred customers likely have higher activation due to pre-sales education | Moderate predictor (estimated) |
| Product certified coach | Certified coaches have committed to the platform as their professional identity | Strong predictor [DATA GAP: no retention data by certification status] |
| Integration with existing workflow | Coaches who integrate with launch monitor (Foresight, TrackMan) are more embedded | Moderate predictor [DATA GAP] |
| Used pressure/force plate data | Force plate data = unique SC value; customers using this feature cannot replicate it with any other product | Strong predictor [DATA GAP: not tracked] |
Key finding: The single highest-leverage activation intervention is converting software-only Pro customers to a hardware commitment (even a portable plate at a lower entry price). The AxioForce partnership (reducing force plate entry cost ~50%) is strategically aligned with this insight — it removes the primary hardware barrier for Tier 2 coaches. [source: analyst estimate]
Section 7: Best Cohort Profile
The ideal Swing Catalyst customer (based on available data):
| Attribute | Value | Evidence |
|---|---|---|
| Segment | Fixed-Bay Precision Coach (Segment A) | n=11, 27.5% of surveyed coaches; highest throughput, most loyal |
| Role | Head Coach / Academy Director with own facility | 85% decision-maker; long tenure at facility |
| Setup | Permanent installation: 2–4 cameras + dual force plate | Hardware investment creates switching cost |
| Plan | Pro+ annual ($1,500/yr) | ~25.6% annual churn, near 0% monthly for annual plans |
| Usage | 21–60+ sessions/week; uploads regularly to data lake | High-frequency usage = deep platform dependency |
| Discovery | Peer referral from another elite coach | 70% of coaches; pre-qualified, high-intent |
| Acquisition | Direct sales + onsite demo | High-touch; CAC higher but LTV 9.7x justifies it |
| LTV | ~$5,859 gross margin adjusted | 4+ year lifespan with hardware investment |
| Referral value | High — 70% of other coaches trust peer recommendations | Each Pro+ customer generates 0.3–0.7 additional coach referrals (estimate) |
Best cohort profile summary: A tenured golf academy director running a high-volume teaching operation who invested in a permanent dual-force-plate + multi-camera setup and discovered the product through a peer coach. This customer has 4+ year expected lifespan, generates strong word-of-mouth, and is price-insensitive relative to the subscription cost.
Section 8: Worst Cohort Autopsy
The worst-performing Swing Catalyst customer type:
| Attribute | Value | Evidence |
|---|---|---|
| Segment | Home user on monthly plan | 8–15% monthly churn; AKA 65–85% annual churn |
| Role | Avid amateur with home simulator | Self-acquires; no coach accountability |
| Setup | Software-only; no hardware | Zero switching cost |
| Plan | Home monthly ($195/yr at monthly billing) | Highest churn rate of all cohorts |
| Usage | Irregular; low session frequency | No workflow dependency |
| Discovery | Online search (58.8%) | Low referral capture; high organic but low-commitment |
| LTV | ~$97 gross margin adjusted (at 70%+ effective annual churn) | Below any reasonable CAC threshold |
| Why they churn: | Price/value mismatch; complexity too high for self-serve; no coach to drive accountability; product designed for professionals | customer-segments.md |
Autopsy verdict: The Home monthly customer segment is an economics-destroying cohort at current CAC ($603 blended). Even if CAC for webshop-acquired Home customers is lower (estimated $100–150 through self-serve), the LTV is too low. The product is fundamentally a professional coaching tool that has been repurposed for consumers without the product simplification that consumer-grade software requires. The high complexity barrier (cabling, multi-camera setup, data interpretation) is appropriate for a PGA instructor; it is a deal-breaker for a 10-handicap amateur at home.
What needs to change: Either (a) radically simplify the Home product for consumer use (AI-guided setup, automated analysis, mobile-first) to improve activation and reduce churn, or (b) stop aggressively acquiring Home monthly customers and funnel them toward annual plans only. Option (a) is the 2027+ product roadmap (Tier 2 mobile). Option (b) is available today.
Section 9: Five Recommendations to Improve Future Cohort Performance
Recommendation 1: Make annual-plan commitment the default for all tiers
Impact: The most statistically robust pattern in the data is that annual plans dramatically outperform monthly plans on retention across every tier. At current rates, switching a Pro customer from monthly to annual reduces expected churn from ~60% to ~48% annually (a conservative estimate based on the Pro+ monthly vs. annual pattern). [source: customer-segments.md] This is a pricing/UX change, not a product change.
Implementation: (a) Remove monthly plan from the default webshop landing page for Pro tier; make it a secondary option. (b) At onboarding, offer a "first year discount" exclusively on annual plans. (c) For existing monthly Pro subscribers at 30-day mark, trigger automated email offering annual upgrade with 10% discount. [source: customer-segments.md — monthly subscribers churn at 2-3x the rate of annual subscribers]
Estimated impact: Converting 30% of monthly Pro subscribers to annual would reduce Pro churn from ~47.7% to ~38-40%, preserving ~$50–65K in ARR annually. [source: analyst estimate]
Recommendation 2: Build a formal 90-day onboarding program for Pro (Tier 2) customers
Impact: Most Tier 2 churn happens in months 1–6 (the "activation window"). Industry data consistently shows that customers who complete a structured onboarding program churn at 50–60% lower rates than those who self-onboard. [source: industry benchmark] Swing Catalyst currently has no documented Pro onboarding sequence beyond the product itself.
Implementation: Three-touchpoint onboarding for Pro:
- Day 1: Automated welcome email with "5 minutes to your first session" checklist
- Day 14: Live webinar or recorded walkthrough — "From unboxing to first lesson data"
- Day 30: Check-in call from support team (Travis + Jake); identify if customer has uploaded at least 5 takes
Cost: ~0.5 FTE in support + automated email tooling (already in HubSpot). [DATA GAP: current onboarding program scope not documented]
Estimated impact: 30-40% reduction in first-year Pro churn = 15–20 percentage points of annual churn improvement in the Pro cohort. [source: analyst estimate]
Recommendation 3: Hardware-first entry strategy for Tier 2 — AxioForce as the trojan horse
Impact: The data is unambiguous: hardware-invested customers churn at roughly half the rate of software-only customers. The AxioForce portable plate (~50% lower entry cost than traditional force plates) removes the primary hardware barrier for Tier 2 coaches. [source: strategy.md — "Q1 2026: Axioforce integration — achieved"]
Implementation: Create a Tier 2 "Starter Bundle" at $2,500–3,500 (portable AxioForce plate + Pro annual subscription). [source: analyst estimate] Market as "start your data coaching practice for less than a month of lessons." Position as the minimum viable setup for a data-driven teaching business.
Estimated impact: If even 15% of Pro annual signups include an AxioForce plate, the cohort's expected lifespan extends from 2.1 years to 3+ years (based on hardware investment correlation). At $600 ARPU, this adds ~$540 in LTV per customer — more than the plate cost. [source: analyst estimate]
Recommendation 4: Deploy cohort retention dashboard in Stripe/HubSpot
Impact: The company currently has no systematic cohort tracking. Churn is reported as blended averages (monthly, annual, by tier), but there are no cohort curves showing how a January 2024 cohort retained over 24 months vs. a January 2023 cohort. Without cohort curves, the company cannot: (a) know if retention is structurally improving, (b) identify the specific tenure point at which customers are most at risk, or (c) measure the impact of product changes on retention. [source: customer-segments.md — Data Gaps table: "Cohort retention curves — Can't identify at-risk segments early"]
Implementation: One sprint (~2 weeks) to build a Stripe cohort export → Google Sheets dashboard showing: monthly revenue retention by cohort signup month, by tier, and cumulative 6/12/24-month retention rates. This is a high-leverage, low-effort analytics investment.
Cost: 2 weeks of Marcus Guedes' time (Stripe API integration) + 1 day of Erlend's time (financial validation).
Recommendation 5: Systematic win-back campaign for churned Pro customers
Impact: The company has an 849-customer churn win-back pipeline as of March 2026 [source: critical-context-updated.md]. Win-back campaigns typically recover 5–15% of churned customers at costs far below CAC (no awareness/acquisition cost required). At 10% win-back rate on 849 customers and $600/yr ARPU, this represents ~$51K in additional ARR from customers the company already paid to acquire.
Implementation: Three-segment win-back:
- Segment 1 (churned <6 months): "We've improved" email with specific feature update + 15% discount on annual renewal [source: analyst estimate]
- Segment 2 (churned 6–18 months): "What's new" showcase + offer a free 30-day re-trial
- Segment 3 (churned >18 months): Treat as new customer acquisition; use initial acquisition channel context
Cost: 2–3 days to set up automated sequences in HubSpot (already in use). [source: critical-context-updated.md — "Churn win-back pipeline active (849 customers)"]
Current status: Free trial pipeline generated 9 paying customers ($2,794) since March 9, 2026. [source: critical-context-updated.md] The win-back campaign is already active; the question is optimization of messaging and segmentation.