Analog

What it is: A reference case where something similar to what you're building worked — in your market, an adjacent vertical, or a completely different industry. The point is not "they're a competitor" but "they proved something true about the world that is relevant to your bet."

Typical lenses to find analogs:

• Product analog - a solution that solved a structurally similar problem (even in a different industry). Example: Notion's block-based flexibility as an analog for any tool trying to replace rigid enterprise software.
• Go-to-market analog - a company that cracked a similar buyer, sales motion, or adoption curve. Example: Veeva as an analog for any vertical SaaS targeting a regulated, relationship-driven industry.
• Customer story analog - a specific customer win that demonstrates the value pattern you're betting on. Example: a manufacturer that reduced scrap rate by 30% by centralizing process data — even if the tool they used is nothing like yours, the value story validates the problem is real and worth paying for.

What you're extracting from an analog:

"This proves that [type of buyer] will [change behavior / pay / switch] when [condition is met]."

Antilog

What it is: A reference case where something similar failed, or is failing, in a way that is instructive. Not just "they lost market share" but why, and what that means for your choices.

Typical lenses to find antilogs:

• Product antilog - a solution that addressed the same problem but made structural mistakes (over-engineered, wrong UX paradigm, wrong pricing model). Example: early AI scheduling tools that automated too much and lost user trust.
• Go-to-market antilog - a company that targeted the right space but with the wrong motion. Example: a bottom-up PLG play in a market that turned out to be top-down procurement only.
• Customer story antilog - a specific failed deployment or abandoned project that reveals a structural constraint in the market. Example: a factory that piloted three analytics tools in two years and abandoned all of them — not because the tools were bad, but because there was no internal owner to act on the insights. This tells you something critical about where value actually lives and what capability you need to exist in the customer's organization for your product to work.

What you're extracting from an antilog:

"This proves that [type of buyer / market condition / product approach] will fail because [structural reason] — and here's what we'll do differently."

Why the customer story lens matters most in early discovery

Customer stories - especially strong fails - cut through faster because they surface the real constraint: perceived value, budget cycles, internal politics, missing capabilities, wrong champion. A customer who tried your category, succeed or abandoned it is more valuable research than a competitor's post-mortem, because it reveals what the world actually looked like from the inside.