Decision Memo - LAILA
LAILA

Decision Memo: Pricing & Packaging

Decision Situation
Choose pricing model for Q1 launch
Deadline
Feb 5, 2026
Date
Jan 30, 2026
Owner
VP Product
Recommendation
GO
ADJUST
PAUSE
Ship the two-tier, usage-based pricing model with transparent calculator. Evidence shows 2.8x higher purchase intent and 41% reduction in pricing confusion compared to seat-based alternative.
Decision Situation
Must finalize pricing structure for public launch on Feb 5. Current internal debate between seat-based vs. usage-based models, with CFO pushing for predictability and Product advocating for growth alignment.
Options Considered
Option A: Seat-Based (3 tiers)
Traditional per-seat model: $49, $99, $199/seat/mo with feature gates
Option B: Usage-Based (2 tiers)
Pay-per-study model: Starter ($2,500/study) + Pro ($4,500/study)
Option C: Hybrid
Base seat fee + usage credits; complex to communicate
Evidence Summary / Customer Signal
2.8x
Higher purchase intent
-41%
Pricing confusion
73%
Preferred transparency
  • Mid-market SaaS buyers (n=89) strongly preferred usage-based clarity; "aligns with how we actually budget for research"
  • PLG segment (n=54) showed 3.2x faster time-to-decision with usage model vs. seat tiers
  • Sales-led orgs (n=35) requested transparent calculator to de-risk procurement approval
Preference by Segment (%)
PLG
Mid-Market
Sales-Led
Mid-Market
Early-Stage
Growth
Scaling
Enterprise
Key Tradeoffs
  • Predictability vs. Growth Alignment: Usage model creates revenue variance but scales naturally with customer success
  • Internal Finance Complexity: Requires dynamic forecasting vs. simple MRR tracking in seat model
  • Sales Cycle Length: Usage reduces procurement friction (-28% avg time) but requires calculator tooling
  • Customer Segment Fit: Strong for PLG/Sales-Led mid-market; weaker signal from early-stage (budget constraints)
Option Pros Cons Confidence
Usage-Based High buyer intent, aligns with budget cycles Finance forecast complexity High (88%)
Seat-Based Predictable MRR, simple internal ops Buyer confusion, misaligned incentives Medium (54%)
Hybrid Flexibility Communication burden, procurement friction Low (31%)
Risks & Unknowns
  • Revenue variance: Usage model creates quarterly unpredictability; mitigated by 12-month contracts with minimum commits
  • Early-stage segment churn: Lower confidence (n=22); may need separate "Starter" tier post-launch
  • Calculator accuracy: Pricing tool must reliably estimate study volume to avoid buyer sticker shock
Assumptions
  • Mid-market buyers conduct 12–24 studies annually (validated via usage data from beta)
  • Transparent calculator reduces sales cycle by 25–30% (extrapolated from PLG cohort time-to-decision)
  • Finance can implement dynamic forecasting by Feb 12 to support usage tracking
Recommendation Rationale
  • Buyer preference is decisive: 73% of must-win segment (PLG + Sales-Led mid-market) prefer usage-based with 2.8x purchase intent lift
  • Competitive positioning: Usage model differentiates vs. seat-based incumbents and aligns with customer success narrative
  • Risk is manageable: Revenue variance mitigated by annual contracts; finance tooling feasible within timeline
Next Test (if needed)
  • Pricing calculator UX: A/B test two calculator layouts with 50 pilot users to validate conversion lift claims
  • Early-stage tier validation: Post-launch (March), run lean pricing study with <$5M ARR segment to determine if separate tier is needed