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finance-based-pricing-advisor · product-manager-skills · Flowy
Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship.
One skill from product-manager-skills .
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Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship. </> SKILL.md
finance-based-pricing-advisor.SKILL.md
---
name : finance-based-pricing-advisor
argument-hint: "[pricing change to evaluate]"
description : Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship.
intent : >-
Evaluate the **financial impact** of pricing changes (price increases, new tiers, add-ons, discounts) using ARPU/ARPA analysis, conversion impact, churn risk, NRR effects, and CAC payback implications. Use this to make data-driven go/no-go decisions on proposed pricing changes with supporting math and risk assessment.
type : interactive
best_for:
- "Evaluating price increases, discounts, or new packaging"
- "Estimating churn and conversion risk before a pricing change"
- "Making a go/no-go call on monetization changes"
scenarios:
- "Should we raise prices 15% for new customers next quarter?"
- "Evaluate a new premium tier for our SaaS product"
- "Help me assess whether an annual discount will improve revenue"
---
## Purpose
Evaluate the **financial impact** of pricing changes (price increases, new tiers, add-ons, discounts) using ARPU/ARPA analysis, conversion impact, churn risk, NRR effects, and CAC payback implications. Use this to make data-driven go/no-go decisions on proposed pricing changes with supporting math and risk assessment.
**What this is:** Financial impact evaluation for pricing decisions you're already considering.
Flowy AI Flows that just work. Hand-picked Claude Code plugins that fire the right skill as you prompt.
**What this is NOT:** Comprehensive pricing strategy design, value-based pricing frameworks, willingness-to-pay research, competitive positioning, psychological pricing, packaging architecture, or monetization model selection. For those topics, see the future `pricing-strategy-suite` skills.
This skill assumes you have a specific pricing change in mind and need to evaluate its financial viability.
## Input
**Works best with:** The pricing change on the table — increase, new tier, add-on, or discount — and current pricing.
**Also useful:** Current ARPU/ARPA, conversion and churn baselines, NRR, and who's pushing for the change.
Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended `ARGUMENTS:` line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.
**Arriving empty-handed? That works too.** The advisor opens by asking what change is proposed and what today's pricing looks like.
**Example invocation:** `Evaluate raising our Pro plan from $49 to $59/seat; ARPU $52, monthly logo churn 1.8%, NRR 108%.`
## Key Concepts
### The Pricing Impact Framework
A systematic approach to evaluate pricing changes financially:
1. **Revenue Impact** — How does this change ARPU/ARPA?
- Direct revenue lift from price increase
- Revenue loss from reduced conversion or increased churn
- Net revenue impact
2. **Conversion Impact** — How does this affect trial-to-paid or sales conversion?
- Higher prices may reduce conversion rate
- Better packaging may improve conversion
- Test assumptions
3. **Churn Risk** — Will existing customers leave due to price change?
- Grandfathering strategy (protect existing customers)
- Churn risk by segment (SMB vs. enterprise)
- Churn elasticity (how sensitive are customers to price?)
4. **Expansion Impact** — Does this create or block expansion opportunities?
- New premium tier = upsell path
- Usage-based pricing = expansion as customers grow
- Add-ons = cross-sell opportunities
5. **CAC Payback Impact** — Does pricing change affect unit economics?
- Higher ARPU = faster payback
- Lower conversion = higher effective CAC
- Net effect on LTV:CAC ratio
### Pricing Change Types
**Direct monetization changes:**
- Price increase (raise prices for all customers or new customers only)
- New premium tier (create upsell path)
- Paid add-on (monetize previously free feature)
- Usage-based pricing (charge for consumption)
**Discount strategies:**
- Annual prepay discount (improve cash flow)
- Volume discounts (larger deals)
- Promotional pricing (temporary price reduction)
**Packaging changes:**
- Feature bundling (combine features into tiers)
- Unbundling (separate features into add-ons)
- Pricing metric change (seats → usage, or vice versa)
### Anti-Patterns (What This Is NOT)
- **Not value-based pricing:** This evaluates a proposed change, not "what should we charge?"
- **Not WTP research:** This analyzes impact, not "what will customers pay?"
- **Not competitive positioning:** This is financial analysis, not market positioning
- **Not packaging architecture:** This evaluates one change, not redesigning all tiers
### When to Use This Framework
**Use this when:**
- You have a specific pricing change to evaluate (e.g., "Should we raise prices 20%?")
- You need to quantify revenue, churn, and conversion trade-offs
- You're deciding between pricing change options (test A vs. B)
- You need to present pricing change impact to leadership or board
**Don't use this when:**
- You're designing pricing strategy from scratch (use value-based pricing frameworks)
- You haven't validated willingness-to-pay (do customer research first)
- You don't have baseline metrics (ARPU, churn, conversion rates)
- Change is too small to matter (<5% price change, <10% of customers affected)
---
### Facilitation Source of Truth
Use [`workshop-facilitation`](../workshop-facilitation/SKILL.md) as the default interaction protocol for this skill.
It defines:
- session heads-up + entry mode (Guided, Context dump, Best guess)
- one-question turns with plain-language prompts
- progress labels (for example, Context Qx/8 and Scoring Qx/5)
- interruption handling and pause/resume behavior
- numbered recommendations at decision points
- quick-select numbered response options for regular questions (include `Other (specify)` when useful)
This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
## Application
This interactive skill asks **up to 4 adaptive questions**, offering **3-5 enumerated options** at decision points.
---
### Step 0: Gather Context
**Agent asks:**
"Let's evaluate the financial impact of your pricing change. Please provide:
**Current pricing:**
- Current ARPU or ARPA
- Current pricing tiers (if applicable)
- Current monthly churn rate
- Current trial-to-paid conversion rate (if relevant)
**Proposed pricing change:**
- What change are you considering? (price increase, new tier, add-on, etc.)
- New pricing (if known)
- Affected customer segment (all, new only, specific tier)
**Business context:**
- Total customers (or MRR/ARR)
- CAC (to assess payback impact)
- NRR (to assess expansion context)
You can provide estimates if you don't have exact numbers."
---
### Step 1: Identify Pricing Change Type
**Agent asks:**
"What type of pricing change are you considering?
1. **Price increase** — Raise prices for new customers, existing customers, or both
2. **New premium tier** — Add higher-priced tier with additional features
3. **Paid add-on** — Monetize a new or existing feature separately
4. **Usage-based pricing** — Charge for consumption (seats, API calls, storage, etc.)
5. **Discount strategy** — Annual prepay discount, volume pricing, or promotional pricing
6. **Packaging change** — Rebundle features, change pricing metric, or tier restructure
Choose a number, or describe your specific pricing change."
**Based on selection, agent adapts questions:**
---
#### If Option 1 (Price Increase):
**Agent asks:**
"**Price increase details:**
- Current price: $___
- New price: $___
- Increase: ___%
**Who is affected?**
1. New customers only (grandfather existing)
2. All customers (existing + new)
3. Specific segment (e.g., SMB only, new plan only)
**When would this take effect?**
- Immediately
- Next billing cycle
- Gradual rollout (test first)"
---
#### If Option 2 (New Premium Tier):
**Agent asks:**
"**Premium tier details:**
- Current top tier price: $___
- New premium tier price: $___
- Key features in premium tier: [list]
**Expected adoption:**
- What % of current customers might upgrade? ___%
- What % of new customers might choose premium? ___%
**Cannibalization risk:**
- Will premium tier cannibalize current top tier?"
---
#### If Option 3 (Paid Add-On):
**Agent asks:**
"**Add-on details:**
- Add-on name: ___
- Price: $___ /month or /user
- Currently free or new feature?
**Expected adoption:**
- What % of customers would pay for this? ___%
- Is this feature currently used (if free)?
- Will making it paid hurt retention?"
---
#### If Option 4 (Usage-Based Pricing):
**Agent asks:**
"**Usage pricing details:**
- Usage metric: (seats, API calls, storage, transactions, etc.)
- Pricing: $___ per [unit]
- Free tier or minimum? (e.g., first 1,000 API calls free)
**Expected impact:**
- Average customer usage: ___ units/month
- Expected ARPU change: $current → $new
**Expansion potential:**
- As customers grow usage, will ARPU increase?"
---
#### If Option 5 (Discount Strategy):
**Agent asks:**
"**Discount details:**
- Discount type: (annual prepay, volume, promotional)
- Discount amount: ___% off
- Duration: (ongoing, limited time)
**Trade-off:**
- Lower price vs. improved cash flow (annual prepay)
- Lower price vs. larger deal size (volume)
- Lower price vs. urgency (promotional)"
---
#### If Option 6 (Packaging Change):
**Agent asks:**
"**Packaging change details:**
- What are you changing? (bundling, unbundling, pricing metric)
- Current packaging: [describe]
- New packaging: [describe]
**Expected impact:**
- ARPU change: $current → $new
- Conversion change: ___% → ___%
- Churn risk: (low, medium, high)"
---
### Step 2: Assess Expected Impact
**Agent asks:**
"Now let's quantify the impact. Based on your pricing change, estimate:
**Revenue impact:**
- Current ARPU: $___
- Expected new ARPU: $___
- ARPU lift: ___%
**Conversion impact:**
- Current conversion rate: ___%
- Expected new conversion rate: ___%
- Conversion change: [increase / decrease / no change]
**Churn risk:**
- Current monthly churn: ___%
- Expected churn after change: ___%
- Churn risk: [low / medium / high]
**Expansion impact:**
- Does this create expansion opportunities? (new tier to upgrade to, usage growth)
- Expected NRR change: ___% → ___%
You can provide estimates. We'll model scenarios (conservative, base, optimistic)."
---
### Step 3: Evaluate Current State
**Agent asks:**
"To assess whether this pricing change makes sense, I need your current baseline:
**Current metrics:**
- MRR or ARR: $___
- Number of customers: ___
- ARPU/ARPA: $___
- Monthly churn rate: ___%
- NRR: ___%
- CAC: $___
- LTV: $___
**Growth context:**
- Current growth rate: ___% MoM or YoY
- Target growth rate: ___%
**Competitive context:**
- Are you priced below, at, or above market?
- Competitive pressure: (low, medium, high)"
---
### Step 4: Deliver Recommendations
**Agent synthesizes:**
- Revenue impact (ARPU lift × customer base)
- Conversion impact (new customers affected)
- Churn impact (existing customers affected)
- Net revenue impact
- CAC payback impact
- Risk assessment
**Agent offers 3-4 recommendations:**
---
#### Recommendation Pattern 1: Implement Broadly
**When:**
- Net revenue impact clearly positive (>10% ARPU lift, <5% churn risk)
- Minimal conversion impact
- Strong value justification
**Recommendation:**
"**Implement this pricing change** — Strong financial case
**Revenue Impact:**
- Current MRR: $___
- ARPU lift: ___% ($current → $new)
- Expected MRR increase: +$___/month (+___%)
**Churn Risk: Low**
- Expected churn increase: ___% → ___% (+___% points)
- Churn-driven MRR loss: -$___/month
- **Net MRR impact: +$___/month** ✅
**Conversion Impact:**
- Current conversion: ___%
- Expected conversion: ___% (___% change)
- Impact on new customer acquisition: [minimal / manageable]
**CAC Payback Impact:**
- Current payback: ___ months
- New payback: ___ months (faster due to higher ARPU)
**Why this works:**
[Specific reasoning based on numbers]
**How to implement:**
1. **Grandfather existing customers** (if raising prices)
- Protect current base from churn
- New pricing for new customers only
2. **Communicate value**
- Emphasize features, outcomes, ROI
- Justify price with value delivered
3. **Monitor metrics (first 30-60 days)**
- Conversion rate (should stay within ___%)
- Churn rate (should stay <___%)
- Customer feedback
**Expected timeline:**
- Month 1: +$___ MRR from new customers
- Month 3: +$___ MRR (cumulative)
- Month 6: +$___ MRR
- Year 1: +$___ ARR
**Success criteria:**
- Conversion rate stays >___%
- Churn rate stays <___%
- NRR improves to >___%"
---
#### Recommendation Pattern 2: Test First (A/B Test)
**When:**
- Uncertain impact (wide range between conservative and optimistic)
- Moderate churn or conversion risk
- Large customer base (can test with subset)
**Recommendation:**
"**Test with a segment before broad rollout** — Impact is uncertain
**Why test:**
- ARPU lift estimate: ___% (wide confidence interval)
- Churn risk: Medium (___% → ___%)
- Conversion impact: Uncertain (___% → ___% estimated)
**Test design:**
**Cohort A (Control):**
- Current pricing: $___
- Size: ___% of new customers (or ___ customers)
**Cohort B (Test):**
- New pricing: $___
- Size: ___% of new customers (or ___ customers)
**Duration:** 60-90 days (need statistical significance)
**Metrics to track:**
- Conversion rate (A vs. B)
- ARPU (A vs. B)
- 30-day retention (A vs. B)
- 90-day churn (A vs. B)
- NRR (A vs. B)
**Decision criteria:**
**Roll out broadly if:**
- Conversion rate (B) >___% of control (A)
- Churn rate (B) <___% higher than control
- Net revenue (B) >___% higher than control
**Don't roll out if:**
- Conversion drops >___%
- Churn increases >___%
- Net revenue impact negative
**Expected timeline:**
- Week 1-2: Launch test
- Week 8-12: Enough data for statistical significance
- Month 3: Decision to roll out or kill
**Risk:** Medium. Test mitigates risk before broad rollout."
---
#### Recommendation Pattern 3: Modify Approach
**When:**
- Original proposal has significant risk
- Better alternative exists
- Need to adjust pricing change to improve outcomes
**Recommendation:**
"**Modify your approach** — Original proposal has risks
**Original Proposal:**
- [Price increase / New tier / Add-on / etc.]
- Expected ARPU lift: ___%
- Churn risk: High (___% → ___%)
- Net revenue impact: Uncertain or negative
**Problem:**
[Specific issue: e.g., "20% price increase will likely cause 10% churn, wiping out revenue gains"]
**Alternative Approach:**
**Option 1: Smaller price increase**
- Instead of ___% increase, try ___%
- Lower churn risk (___% vs. ___%)
- Still positive net revenue: +$___/month
**Option 2: Grandfather existing, raise for new only**
- Protect current base (zero churn risk)
- Higher prices for new customers only
- Gradual ARPU improvement over time
**Option 3: Value-based pricing (charge more for high-value segments)**
- Keep SMB pricing flat
- Raise enterprise pricing ___%
- Lower churn risk (enterprise is stickier)
**Recommended:**
[Specific option with reasoning]
**Why this is better:**
- Lower churn risk
- Comparable revenue upside
- Easier to communicate
**How to implement:**
[Specific steps for alternative approach]"
---
#### Recommendation Pattern 4: Don't Change Pricing
**When:**
- Net revenue impact negative or marginal
- High churn risk without offsetting gains
- Competitive or strategic reasons to hold pricing
**Recommendation:**
"**Don't change pricing** — Risks outweigh benefits
**Why:**
- Expected revenue lift: +$___/month (___%)
- Expected churn impact: -$___/month (___%)
- **Net revenue impact: -$___/month** 🚨 or marginal
**Problem:**
[Specific issue: e.g., "Churn-driven revenue loss exceeds price increase gains"]
**What would need to change:**
**For price increase to work:**
- Churn rate must stay below ___% (currently ___%)
- OR conversion rate must stay above ___% (currently ___%)
- OR you need to reduce CAC to offset lower conversion
**Alternative strategies:**
**Instead of raising prices:**
1. **Improve retention** — Reduce churn from ___% to ___% (same revenue impact as price increase, lower risk)
2. **Expand within base** — Increase NRR from ___% to ___% via upsells
3. **Reduce CAC** — More efficient acquisition (better than pricing)
**When to revisit pricing:**
- After improving retention (churn <___%)
- After validating willingness-to-pay (WTP research)
- After competitive landscape changes
**Decision:** Hold pricing for now, focus on [retention / expansion / acquisition efficiency]."
---
### Step 5: Sensitivity Analysis (Optional)
**Agent offers:**
"Want to see what-if scenarios?
1. **Optimistic case** — Higher ARPU lift, lower churn
2. **Pessimistic case** — Lower ARPU lift, higher churn
3. **Breakeven analysis** — What churn rate makes this neutral?
Or ask any follow-up questions."
**Agent can provide:**
- Scenario modeling (optimistic/pessimistic/breakeven)
- Sensitivity tables (if churn is X%, revenue impact is Y)
- Comparison to alternative pricing strategies
---
## Examples
See `examples/` folder for sample conversation flows. Mini examples below:
### Example 1: Price Increase (Good Case)
**Scenario:** 20% price increase for new customers only
**Current state:**
- ARPU: $100/month
- Customers: 1,000
- MRR: $100K
- Churn: 3%/month
- New customers/month: 50
**Proposed change:**
- New customer pricing: $120/month (+20%)
- Existing customers: Grandfathered at $100
**Impact:**
- New customer ARPU: $120 (+20%)
- Churn risk: Low (existing protected)
- Conversion impact: Minimal (<5% drop estimated)
**Recommendation:** Implement. Net revenue impact +$12K/year with low risk.
---
### Example 2: Price Increase (Risky)
**Scenario:** 30% price increase for all customers
**Current state:**
- ARPU: $50/month
- Customers: 5,000
- MRR: $250K
- Churn: 5%/month (already high)
**Proposed change:**
- All customers: $65/month (+30%)
**Impact:**
- ARPU lift: +30% = +$75K MRR
- Churn risk: High (5% → 8% estimated)
- Churn-driven loss: 3% × 5,000 × $65 = -$9.75K MRR/month
**Net impact:** +$75K - $9.75K = +$65K MRR (but accelerating churn problem)
**Recommendation:** Don't change. Fix retention first (reduce 5% churn), then raise prices.
---
### Example 3: New Premium Tier
**Scenario:** Add $500/month premium tier
**Current state:**
- Top tier: $200/month (500 customers)
- ARPA: $200
**Proposed change:**
- New tier: $500/month with advanced features
- Expected adoption: 10% of current top tier (50 customers)
**Impact:**
- Upsell revenue: 50 × ($500 - $200) = +$15K MRR
- Cannibalization risk: Low (features justify premium)
- NRR impact: Increases from 105% to 110%
**Recommendation:** Implement. Creates expansion path, minimal cannibalization risk.
---
## Common Pitfalls
### Pitfall 1: Ignoring Churn Impact
**Symptom:** "We'll raise prices 30% and make $X more!" (no churn modeling)
**Consequence:** Churn wipes out revenue gains. Net impact negative.
**Fix:** Model churn scenarios (conservative, base, optimistic). Factor churn-driven revenue loss into net impact.
---
### Pitfall 2: Not Grandfathering Existing Customers
**Symptom:** "We're raising prices for everyone effective immediately"
**Consequence:** Massive churn spike from existing customers who feel betrayed.
**Fix:** Grandfather existing customers. Raise prices for new customers only.
---
### Pitfall 3: Testing Without Statistical Power
**Symptom:** "We tested on 10 customers and it worked!"
**Consequence:** 10 customers isn't statistically significant. Results are noise.
**Fix:** Test with large enough sample (100+ customers per cohort) for 60-90 days.
---
### Pitfall 4: Pricing Changes Without Value Justification
**Symptom:** "We're raising prices because we need more revenue"
**Consequence:** Customers see price increase without corresponding value increase. Churn.
**Fix:** Tie price increases to value improvements (new features, better support, outcomes delivered).
---
### Pitfall 5: Ignoring CAC Payback Impact
**Symptom:** "Higher ARPU is always better!"
**Consequence:** If conversion drops 30%, effective CAC increases dramatically. Payback period explodes.
**Fix:** Calculate CAC payback impact. Higher ARPU with lower conversion might make payback worse, not better.
---
### Pitfall 6: Annual Discounts That Hurt Margin
**Symptom:** "30% discount for annual prepay!" (improves cash but destroys LTV)
**Consequence:** Customers lock in low prices for a year. Revenue per customer decreases.
**Fix:** Limit annual discounts to 10-15%. Balance cash flow improvement with LTV protection.
---
### Pitfall 7: Copycat Pricing (Competitor-Based)
**Symptom:** "Competitor raised prices, so should we"
**Consequence:** Your customers, value prop, and cost structure are different. What works for them may not work for you.
**Fix:** Use competitors as data points, not decisions. Make pricing decisions based on your unit economics.
---
### Pitfall 8: Premature Optimization
**Symptom:** "Let's A/B test 47 different price points!"
**Consequence:** Analysis paralysis. Spending months on 5% pricing optimizations while missing 50% growth opportunities elsewhere.
**Fix:** Big pricing changes (tiers, packaging, add-ons) matter more than micro-optimizations. Start there.
---
### Pitfall 9: Forgetting Expansion Revenue
**Symptom:** "We're maximizing ARPU at acquisition"
**Consequence:** High upfront pricing prevents landing customers. Miss expansion opportunities.
**Fix:** Consider "land and expand" strategy. Lower entry price, higher expansion revenue via upsells.
---
### Pitfall 10: No Pricing Change Communication Plan
**Symptom:** "We're raising prices next month" (no customer communication)
**Consequence:** Surprised customers churn. Poor reviews. Reputation damage.
**Fix:** Communicate pricing changes 30-60 days in advance. Emphasize value, not just price.
---
## References
### Related Skills
- `saas-revenue-growth-metrics` — ARPU, ARPA, churn, NRR metrics used in pricing analysis
- `saas-economics-efficiency-metrics` — CAC payback impact of pricing changes
- `finance-metrics-quickref` — Quick lookup for pricing-related formulas
- `feature-investment-advisor` — Evaluates whether to build features that enable pricing changes
- `business-health-diagnostic` — Broader business context for pricing decisions
### External Frameworks (Comprehensive Pricing Strategy)
These are OUTSIDE the scope of this skill but relevant for broader pricing work:
- **Value-Based Pricing** — Price based on value delivered, not cost
- **Van Westendorp Price Sensitivity** — WTP research methodology
- **Conjoint Analysis** — Feature-to-price trade-off research
- **Good-Better-Best Packaging** — Tier architecture design
- **Price Anchoring & Decoy Pricing** — Psychological pricing tactics
- **Patrick Campbell (ProfitWell):** Pricing research and benchmarks
### Future Skills (Comprehensive Pricing)
For topics NOT covered here, see future `pricing-strategy-suite`:
- `value-based-pricing-framework` — How to price based on value
- `willingness-to-pay-research` — WTP research methods
- `packaging-architecture-advisor` — Tier and bundle design
- `pricing-psychology-guide` — Anchoring, decoys, framing
- `monetization-model-advisor` — Seat-based vs. usage vs. outcome pricing
### Provenance
- Adapted from `research/finance/Finance_For_PMs.Putting_It_Together_Synthesis.md` (Decision Framework #3)
- Pricing scenarios from `research/finance/Finance for Product Managers.md`
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