Profiling Competitor Offerings
Given an offering/product to analyze (e.g., "CRM software for SMBs"), produce a competitor profile table:
| Competitor | Offering Overview | Target Buyer/Industry | Differentiation | Pricing |
|---|---|---|---|---|
| Acme CRM | Cloud CRM with sales + marketing automation | SMBs, B2B SaaS, sales teams | AI lead scoring, native WhatsApp integration | $29-$99/user/mo |
Always use a fixed-format template across all competitors — this is what makes profiles comparable.
Progress:
- [ ] Step 1: Define scope (the offering/category being analyzed)
- [ ] Step 2: Identify players (direct + adjacent competitors)
- [ ] Step 3: Gather source material per competitor (site pages, decks, pricing pages)
- [ ] Step 4: Extract into fixed-format fields
- [ ] Step 5: Summarize and flag patterns/gaps across competitors
Step 1: Define Scope
- Clarify the offering category, geography, and buyer segment being analyzed.
- State this scope explicitly at the top of the output — it anchors which players are "in" vs "out."
Step 2: Identify Players
- Search for direct competitors (same offering, same buyer).
- Include 1-2 adjacent/aspirational players (different tier, but relevant for differentiation context).
- List them before deep-diving — confirm the list covers the market before spending time on extraction.
Step 3: Gather Source Material
For each competitor, pull from (in priority order):
- Product/offerings pages (primary source)
- Pricing page
- Public decks, one-pagers, case studies
- About/customers page (for target buyer/industry signals)
If a field isn't publicly available (common for pricing), mark as Not disclosed — [inference if any] rather than leaving blank or guessing silently.
Step 4: Extract into Fixed Fields
Use this exact schema for every competitor, no exceptions:
- Offering Overview: 1-2 sentence summary of what they sell
- Target Buyer/Industry: Who buys it (role, company size, vertical)
- Market Differentiation: What they claim makes them different (features, positioning angle, not just a feature list)
- Pricing: Model (per-seat, flat, usage-based) + range if available
Step 5: Summarize Patterns
After individual profiles, add a short synthesis:
- Common positioning themes across players
- Pricing model clusters (e.g., "most are per-seat $20-50/mo")
- Whitespace — buyer segments or differentiators nobody is claiming
Example 1: Input: "Profile competitors in the project management software space for creative agencies." Output:
- Scope stated: PM tools targeting creative/agency teams
- Players identified: Monday.com, Asana, Function Point, Wrike
- Each profiled in the 4-field table
- Synthesis: "3 of 4 target 'creative teams' explicitly; pricing clusters at $10-24/user/mo; only Function Point offers agency-specific billing/profitability tracking — a differentiation gap others could target."
Example 2: Input: A sales deck for "Offering X" is shared with no further instructions. Output: Summarize the deck → identify named/implied competitors mentioned or inferable from category → build profiles for each using the fixed format → note any competitor claims in the deck that should be independently verified.
- Keep the profile format identical across every competitor — side-by-side comparability is the whole point.
- Distinguish stated differentiation (what they claim) from actual differentiation (what's verifiably different) when evidence allows.
- Capture pricing as ranges/models, not single data points that go stale fast.
- Date-stamp profiles — competitor pricing and offerings change quickly.
- Note source for each major claim (e.g., "per pricing page, Oct 2025") so profiles are auditable later.
- Don't let format vary by competitor based on what's easiest to find — force every field, even if it's "Not disclosed."
- Don't copy marketing copy verbatim as "differentiation" — translate into what it actually means for the buyer.
- Don't skip the player-identification step — an incomplete competitor list invalidates the whole analysis.
- Don't ignore adjacent/indirect competitors — they often reveal pricing or positioning whitespace.
- Don't present raw data without the synthesis step — profiles without pattern-spotting are just a data dump.