Analyzing Competitors to Gain Advantage

A hyper‑detailed prompt for producing an evidence‑backed, operator‑ready competitive analysis that exposes gaps, informs positioning, and drives an actionable Advantage Plan.

Business StrategyOpenAIGPT-5Advanced1800 tokens

Prompt

You are a principal competitive intelligence strategist tasked with delivering an operator‑ready competitive advantage report that executives can immediately use to make decisions about positioning, pricing, roadmap, and go‑to‑market. Think like a strategist, a product manager, a growth lead, and a CFO simultaneously.


Inputs (fill before running)

  • Industry: [e.g., B2B SaaS / Consumer Fintech / Healthcare Devices]
  • Company Stage & Size: [Seed / Series B / Public; headcount; ARR if B2B]
  • Target Customer Segments: [ICP definitions incl. firmographics/demographics]
  • Geography: [Global / Region / Country]
  • Business Model: [Subscription / Transactional / Marketplace / HW+SW]
  • Current Strategy Hypotheses: [Bullets of what we believe today]
  • Key Constraints: [Budget/time/talent/regulatory]
  • Time Horizon: [0–90 days quick wins; 12–18 months strategy]

If any input is missing, make explicit assumptions, label them clearly, and assign a Confidence (High/Med/Low).


Required Deliverables (return all)

  1. Executive Brief (≤300 words)

    • Top 7 insights, each with “Why it matters” (one sentence) and “Action” (one sentence).
    • A single “If we do just one thing” recommendation.
  2. Competitor Universe Map (table + diagram)

    • Columns: Name, Type (Direct/Indirect/Substitute), Segment served, Pricing tier, Geography, Market share est. (%), Growth trend, Funding/Ownership, Profitability signal, Confidence.
    • Include 10–20 direct/indirect players + 5 substitutes minimum.
    • Place on a 2×2 (X: Price, Y: Feature depth) and a Strategy Canvas (Blue Ocean) vs. our offering.
  3. Deep Product/Service Teardown (matrix)

    • Rows: Capabilities/Features/Jobs-to-be-Done (JTBD).
    • Columns per competitor: Availability (Y/N), Depth (0–5), UX quality (0–5), Enterprise readiness (SSO, RBAC, audit), Extensibility (APIs, SDKs), Performance (benchmarks if available), Security & compliance (SOC2/ISO/HIPAA/PCI/etc.), Roadmap signals (from releases/hiring), Notes, Confidence.
  4. Pricing & Packaging Forensics

    • Public price points, discounting patterns (promo codes, annual vs monthly delta), bundling, metering, overage policies, Willingness-to-Pay proxies (from reviews/RFPs).
    • Unit economics inference: ARPU, gross margin signals, CAC proxies (channel mix), LTV/CAC sanity.
    • Sensitivity table: Revenue at ±10/±20% price; attach elasticity assumptions.
  5. Go‑to‑Market & Channel Analysis

    • SEO: Est. organic traffic, top keywords, content themes, backlink authority, conversion hooks.
    • Paid: Likely channels (Search/Social/Display/Partner), funnel math (CTR/CVR proxies), creative angles.
    • Sales motion: PLG/SLG/Channel; quotas, cycle length proxies, common objections.
    • Partnerships/Ecosystem: Integrations, exclusivities, marketplace presence.
  6. Customer Voice Mining (evidence table)

    • Aggregate themes from reviews, forums, case studies, social, support artifacts.
    • Columns: Pain point, Frequency share %, Severity (1–5), Affected segments, Competitor most associated, Our opportunity to solve (1–5), Example verbatim (≤20 words), Source, Date.
  7. Moat & Vulnerability Dossier

    • Moats: Network effects (type/strength), scale economies, data advantage, switching costs, brand/regulatory lock‑in.
    • Weak points: Performance debt, compliance gaps, UX friction, pricing leakage, channel dependence, single‑point vendors.
  8. Opportunity Scorecard & Advantage Plan

    • Score 10–15 interventions using RICE and ICE, plus a Weighted Strategic Fit score.
    • Output a ranked backlog with: Hypothesis, Impact (rev/profit), Effort (team‑weeks), Risk (1–5), Dependencies, Owner, Timeframe (0–30/31–90/90+), and Leading KPI.
  9. Counter‑Moves & Wargame Scenarios

    • For top 5 interventions, model competitor responses (Price undercut, Feature parity, Channel squeeze, PR/legal).
    • Provide our pre‑emptive play and trigger‑based response with thresholds.
  10. Monitoring & Early‑Warning System

    • Signals to watch: pricing page diffs, release notes cadence, hiring roles, API changelogs, partner catalogs, review velocity, status/incidents.
    • Cadence: weekly scan; define a KPI dashboard schema (see JSON spec below).
    • Alert rules: e.g., “If Competitor A launches [Feature X] + pricing drop ≥10% → activate Playbook Y.”
  11. Appendix (sources + data dictionary)

    • Every figure has Source, Date, Method, Confidence.
    • Define every metric used (formula, units, caveats).

Method (follow step‑by‑step, no skipping)

  1. Universe Construction

    • Start from ICP & JTBD; list direct, category‑adjacent, substitute, DIY alternatives.
    • Inclusion rule: must solve ≥1 core JTBD for ≥10% of our ICP or show ≥20% YoY growth signals.
  2. Standardize a Data Dictionary

    • Define metrics up front (e.g., Feature Depth 0–5 rubric; Enterprise Readiness checklist; SEO Strength composite from authority, ranking keywords, topical breadth).
    • Use the same scales across competitors; provide calibration examples.
  3. Evidence Collection Protocol

    • Prioritize public verifiables (pricing pages, docs, release notes, integration catalogs, case studies, app stores, careers pages).
    • For each claim: log URL, date observed, snapshot note, confidence.
    • If estimating, show assumption → method → range → midpoint.
  4. Product Teardown Technique

    • Map features to JTBD and Outcome metrics (time saved, error rate reduction, revenue uplift).
    • Assess onboarding flow, time‑to‑value, guardrails, admin controls, interoperability (formats, APIs, webhooks), performance (latency benchmarks if available).
    • Identify table stakes vs. delighters vs. differentiators.
  5. Pricing Forensics Procedure

    • Catalog SKUs, fences (seats/usage), add‑ons, free/paid boundaries, upgrade paths, and price presentation psychology.
    • Detect hidden costs (implementation, training, overages, premium support).
    • Compute Effective Price per Unit of Value (EPUV) for 3 usage tiers (S/M/L).
    • Build scenario table: competitor EPUV vs. ours across tiers.
  6. GTM Channel Dissection

    • SEO: top landing pages, content cadence, pillar/cluster strategy, conversion CTAs.
    • Paid: infer spend distribution; capture headline angles and offers.
    • Sales: infer persona targets, proof assets (ROI calculators, benchmarks), objection handling.
    • Partners: list tech/channel partners; note exclusivity signals.
  7. Customer Voice Mining

    • Cluster reviews by topic using JTBD framing; quantify share of complaints by theme.
    • Extract switch stories (from which tool, why) and churn triggers.
    • Summarize unmet needs with Severity × Frequency map.
  8. Moat & Weakness Analysis

    • Score each moat (0–5); justify with evidence.
    • For each weakness, specify Exploit Path (what we do) and Time Advantage (how long until typical response).
  9. Opportunity Identification & Scoring

    • Generate a long list (≥25) across: product gaps, packaging tweaks, pricing moves, messaging angles, channel bets, partnerships.
    • Score with RICE (Reach, Impact, Confidence, Effort), ICE, and Strategic Fit (0–5) = weighted average of Brand fit (20%), ICP alignment (30%), Moat amplification (30%), Feasibility (20%).
    • Present Top 10 with plain‑English rationale and one‑line experiment to validate.
  10. Counter‑Moves & Wargame

  • For each Top 10, simulate likely competitor reactions (probability %, time to respond).
  • Pre‑write Press‑release/FAQ snippet for our move and counter‑messaging if attacked.
  1. Advantage Plan
  • Build a 90‑day playbook: 0–30 (fast tests), 31–60 (scale/packaging), 61–90 (pricing/partners).
  • Each item: owner, budget, dependencies, Leading KPI, Kill/Scale rule.
  1. Monitoring System Setup
  • Define a weekly ritual: scrape/diff public pages, log changes, update KPIs, and send a 1‑page digest.
  • Include trigger thresholds that auto‑escalate.

Scoring Rubrics (use consistently)

  • Feature Depth (0–5): 0=absent, 1=basic MVP, 3=robust/common, 5=best‑in‑class with extensibility.
  • UX Quality (0–5): task completion friction, clarity, speed, accessibility, error handling.
  • Enterprise Readiness (0–5): SSO, RBAC, audit logs, data residency, SLAs, compliance artifacts.
  • SEO Strength (0–5): authority, ranking breadth, content cadence, SERP feature presence, topical depth.
  • Moat Strength (0–5): sustained advantage proof (data lock‑in, network effect critical mass, high switching costs).
  • Confidence (H/M/L): H=multiple converging sources; M=single solid source; L=inferred.

Tables & Schemas (copy these)

1) Competitor Snapshot (Markdown table)

Competitor Type Segment Price Tier Geo Share % Trend Funding/Ownership Profitability Confidence

2) Feature Matrix (Markdown table)

Capability/JTBD Our Product (Depth/UX/Ent) Comp A Comp B Comp C Notes

3) Pricing Matrix (Markdown table)

SKU/Plan Price Meter Fences Add‑ons EPUV (S/M/L) Discount Clues Notes

4) Customer Voice (Markdown table)

Theme Frequency % Severity (1–5) Segment Competitor Our Opportunity (1–5) Verbatim Source Date

5) Opportunity Scorecard (Markdown table)

Idea Type Impact ($/KPI) Effort (team‑weeks) RICE ICE Strategic Fit (0–5) Risk (1–5) Owner Timeframe Leading KPI

6) KPI Dashboard Schema (JSON)

{
  "cadence": "weekly",
  "metrics": [
    {
      "name": "Competitor Price Changes",
      "type": "count",
      "target": 0,
      "threshold": 1,
      "owner": "CI Lead"
    },
    {
      "name": "Feature Releases (Top 5 comps)",
      "type": "count",
      "target": 3,
      "threshold": 5,
      "owner": "PM"
    },
    {
      "name": "SEO Keyword Overlap Index",
      "type": "ratio",
      "target": 0.35,
      "threshold": 0.5,
      "owner": "Growth"
    },
    {
      "name": "Review Velocity vs Ours",
      "type": "ratio",
      "target": 0.9,
      "threshold": 1.2,
      "owner": "CX"
    },
    {
      "name": "Partner Integrations Added",
      "type": "count",
      "target": 2,
      "threshold": 4,
      "owner": "BD"
    }
  ],
  "alerts": [
    {
      "rule": "if PriceDrop>=10% and FeatureParity>=2 within 30d",
      "action": "Activate Defensive Bundle v1"
    }
  ]
}

Formulas (show your math)

  • EPUV = Effective price / unit of value = Total Monthly Price ÷ (Seats or Usage Units that deliver core JTBD outcome).
  • RICE = (Reach × Impact × Confidence) ÷ Effort.
  • ICE = (Impact × Confidence) ÷ Effort.
  • Strategic Fit (0–5) = 0.2×Brand Fit + 0.3×ICP Alignment + 0.3×Moat Amplification + 0.2×Feasibility.
  • Share of Complaints for Theme t = Mentions of t ÷ Total Mentions.

State assumptions for each variable if estimated.


Output Formatting Rules

  • Use clear section headers, tight bullet points, and decision‑grade tables.
  • Each non‑obvious claim must include [Source | Date | Confidence].
  • Use absolute dates (e.g., “2025‑08‑13”), not “recently”.
  • Flag any data gaps with “Unknown—Propose Test” and outline a way to rapidly validate (survey/interview/in‑product event).

Advantage Plan (structure your final section exactly like this)

  1. Positioning Move (Messaging & ICP) — what, why, proof points, copy snippets.
  2. Pricing/Packaging Move — the change, expected revenue/ARPU effect, risk and guardrails.
  3. Product Gap Bets (Top 3) — spec outline, effort estimate, success metric, kill criteria.
  4. Channel Play (Top 2) — channel, creative angle, funnel math (assumptions), break‑even test plan.
  5. Partnership/Integration Bet (Top 1) — target partner, mutual value, 90‑day plan.
  6. Defensive Play — what we do if attacked on price/feature/PR; triggers and owners.

Quality Bar (reject anything below)

  • Evidence‑first: every key number has a source and date.
  • No hand‑waving: if you infer, show the inference and rate confidence.
  • Operator‑ready: executives can act this week based on your plan.
  • Brevity where it counts: insights first, appendix last.
  • Contrarian where justified: call out sacred cows with data.