Pricing And Wtp

Skill: pricing-and-wtp

Purpose

Determine what users would actually pay, not what the developer hopes to charge. Anchor WTP to pain intensity, desire strength, competitive pricing, and real monetization signals from market_insights — never to the cost of building. Pricing is the single decision with the highest leverage on unit economics: a $1/mo difference at 1,000 users is $12K/year.

Input

• Idea slug
• memory/ideas/<slug>/idea.md (app concept, key features, business_model, price_point_hypothesis)
• memory/ideas/<slug>/competitors.json (competitive pricing, pricing models in use, anchors for the B2B lane)
• memory/ideas/<slug>/desire_scores.json (desire strength, primary/secondary drivers)
• memory/market_insights/<niche>-*-<YYYY>-<MM>.md (trend data — use all available platform files)

Using Market Insights

Trend analysis files provide monetization reality-checks that desk research alone cannot:

Lane selection

business_model = b2c or prosumer uses the B2C lane: the category WTP table in Step 4, freemium conversion in Step 5, and wtp_range + recommended_price in the output. b2b-smb and b2b2c use the B2B lane: the benchmark table in Step 4b, trial-to-paid in Step 5b, tiers in Step 7, and target_wtp_range + recommended_tiers in the output. Van Westendorp (Step 2) and the desire multiplier (Step 3) apply to both lanes; in B2B, anchor the thresholds on the closest product that sells to the same buyer rather than on the category as a whole.

Pricing Models

Model selection criteria

Process

Step 1 — Establish competitive pricing range

From competitors.json, extract pricing data for all direct competitors:

1. List each competitor's pricing model and price point.
2. Compute the range: competitive_min (cheapest) and competitive_max (most expensive).
3. Identify the modal price — the price point most competitors converge on. This is the market's revealed equilibrium.
4. Note any competitor using a different model (e.g., all use subscription but one uses one-time purchase) — this is a potential positioning gap.

If competitors.json has limited pricing data, supplement with market_insights monetization_evidence and App Store narrative pricing mentions.

Step 2 — Van Westendorp Price Sensitivity Analysis

The Van Westendorp model uses four price perception thresholds to identify the acceptable price range. Since we can't survey users directly, we estimate each threshold from available data:

The four thresholds

Acceptable price range

The optimal price point sits between "cheap but acceptable" and "getting expensive" — this is the target WTP.

wtp_low = cheap_but_acceptable
wtp_target = getting_expensive (adjusted by desire multiplier)
wtp_aspirational = midpoint between getting_expensive and too_expensive

Step 3 — Desire-Premium Multiplier

Desire strength from desire_scores.json directly affects pricing power. Apps that tap into primal desires command premium pricing; apps that solve mild inconveniences face price resistance.

Apply the multiplier to the competitive modal price:

desire_adjusted_target = competitive_modal_price × desire_multiplier

If desire_strength_label = "weak", do not apply any multiplier — the app lacks the emotional pull to justify premium pricing.

Secondary desire bonus

If the secondary desire driver is different from the primary and scores ≥ 3, add a +10% bonus. Apps that tap two distinct desires (e.g., survival + control in a health tracker) have stronger pricing power than single-desire apps.

Step 4 — WTP Benchmarks by App Category

Use these ranges as a sanity check against the Van Westendorp and desire-adjusted estimates:

If the estimated WTP is more than 2× above the category range, it's likely too optimistic. If it's below the category minimum, the app may struggle to sustain development.

Step 4b — B2B lane benchmarks (SMB and agency buyers, self-serve or light sales; heuristic ranges)

Sanity anchors: routine SMB tooling sits at $20–100/mo per company (heuristic: Zapier, Make, Notion team plans); agency white-label tooling at $59–349/mo with per-client overage (AgencyAnalytics pricing page); compliance and security platforms at $10k–80k/yr (Vanta, Drata, Nudge published or quoted pricing). If the idea sits between two clusters with nothing in the gap, the revealed price is a gap, not a validation; say so and set monetization_risk no lower than "medium".

Rules for the B2B lane:

• Copy the billing unit the buyer already accepts from the closest comparable product; do not invent a unit.
• Do not price per seat unless the per-user value is real.
• Recommend a free trial (time-boxed or one-unit) rather than a free tier unless a free incumbent must be defended against.
• Publish prices unless every comparable hides them; transparency is a free differentiator in categories full of "contact sales".

Step 5 — Freemium Conversion Estimation

If the recommended model includes a free tier, estimate what percentage of free users will convert to paid:

Category benchmarks for freemium conversion:

Use the typical rate as the base estimate. Adjust toward top-quartile if:

• The desire_strength_label is "strong"
• The free tier design has strong value gating
• Category benchmarks from market_insights show successful freemium competitors

Step 5b — B2B trial-to-paid estimation

In the B2B lane set freemium_conversion_estimate to null unless a free tier is genuinely recommended, and estimate trial_to_paid_estimate instead (heuristic ranges for self-serve SMB SaaS):

Choose the row matching the recommended trial and state why. A trial that lets the buyer produce something they can show a client or boss during the trial period sits at the top of its band.

Step 6 — Annual vs. Monthly Strategy

Most indie apps benefit from offering both monthly and annual plans. The annual plan serves as the anchor.

Annual discount psychology

Recommended annual price = monthly price × 12 × (1 - discount). Present the annual plan as the default/highlighted option.

Step 7 — Pricing lane by business model

B2B lane (b2b-smb, b2b2c): recommended tiers. Build 3 tiers (plus a trial) from the Van Westendorp range: entry at cheap_but_acceptable, the primary revenue tier at getting_expensive, and a top tier near the midpoint to too_expensive with the features only larger buyers need. Name the target for each tier. For b2b2c add a rebilling_strategy: how the buyer marks the product up to its own customers, with evidence that comparable buyers do this. Rebilling moves the subscription from the buyer's cost line to its revenue line and is the strongest churn lever available; say whether it is critical, useful, or absent.

B2C lane with a business path (B2B2C expansion). Some consumer ideas have a viable path to both consumer and business revenue. Evaluate if the app concept could serve both:

If B2B2C path exists:

• B2C price: Use the standard WTP methodology above (this is the consumer price).
• B2B2C price: 3–5× the consumer price per seat. Businesses have larger budgets and lower price sensitivity.
• Recommendation: Launch B2C first (faster validation, faster feedback). Flag B2B2C as a future monetization expansion in the output.
• Do NOT recommend B2B2C as the primary model for an indie developer — enterprise sales cycles and support needs don't fit the indie model.

Output

Write to memory/ideas/<slug>/pricing.json:

{
  "idea_slug": "",
  "modeled_at": "YYYY-MM-DD",
  "lane": "b2c | b2b",
  "wtp_range": {
    "low": 0,
    "target": 0,
    "aspirational": 0,
    "currency": "USD",
    "period": "monthly | yearly | one-time"
  },
  "target_wtp_range": {
    "low": 0,
    "target": 0,
    "high": 0,
    "unit": "USD per month per <company | seat | client>"
  },
  "van_westendorp": {
    "too_cheap": 0,
    "cheap_but_acceptable": 0,
    "getting_expensive": 0,
    "too_expensive": 0,
    "methodology_note": ""
  },
  "anchors": [
    { "product": "", "price": "", "relevance": "" }
  ],
  "desire_premium_multiplier": null,
  "desire_premium_rationale": "",
  "recommended_pricing_model": "",
  "pricing_model_rationale": "",
  "pricing_models_considered": [
    { "model": "", "fit_rationale": "", "risk": "" }
  ],
  "recommended_price": {
    "monthly": 0,
    "annual": 0,
    "annual_discount_pct": 0,
    "one_time": 0
  },
  "recommended_tiers": [
    { "name": "", "price": 0, "billing": "per month | per year | one-time", "scope": "", "target": "" }
  ],
  "freemium_conversion_estimate": null,
  "freemium_conversion_rationale": "",
  "trial_to_paid_estimate": null,
  "rebilling_strategy": { "importance": "critical | useful | none", "detail": "", "evidence": "" },
  "competitive_pricing_range": {
    "min": 0,
    "max": 0,
    "modal": null
  },
  "category_benchmark_range": {
    "min": 0,
    "max": 0
  },
  "b2b2c_potential": {
    "exists": false,
    "b2b_price_estimate": 0,
    "rationale": ""
  },
  "monetization_risk": "low | medium | high",
  "monetization_risk_explanation": "",
  "market_insights_pricing_signals": [],
  "market_insights_sources_used": [],
  "pricing_rationale": "",
  "sources": [
    { "url": "https://", "title": "", "accessed": "YYYY-MM-DD", "used_for": "" }
  ]
}

Fill wtp_range + recommended_price in the B2C lane and target_wtp_range + recommended_tiers in the B2B lane; the other pair may be omitted. modal is null when no competitor occupies the idea's price position. sources lists every pricing page and anchor consulted.

Notes

• The target WTP is the price used by downstream skills (cac-modeler for LTV, tam-sam-som-builder for revenue projections). Getting this wrong cascades errors through the entire scoring system.
• If monetization_evidence from market_insights is empty across all platform files, flag pricing as "unvalidated" in the rationale. This is a key risk — the market may not support paid apps.
• For apps competing with strong free alternatives (Google Keep, Apple Notes, default apps), the effective WTP ceiling may be $0 for most users. In this case, the pricing model must create value that the free alternative structurally cannot (social features, AI, specialized workflows).
• Lifetime deal pricing should only appear as a launch tactic, never as the recommended primary model. LTD price = 3–5× annual price. Cap at $60 for consumer apps.
• If market_insights files are past their stale_after date, note that competitive pricing may have shifted and recommend refreshing.
• cac-modeler reads target (B2C) or the primary tier price (B2B) as ARPU, and trial_to_paid_estimate or freemium_conversion_estimate for funnel maths. Keep those fields numeric.