Sales loses winnable deals to competitors they can't crisply argue against. This playbook researches each competitor across public sources and compresses the findings into a one-page battlecard — positioning, pricing signals, landmines to plant, objection counters — with every claim sourced and dated, because an outdated battlecard loses deals faster than no battlecard.
Workflow area: Marketing · Tier: Advanced · Hands-on time: ~45 minutes
The failure mode of AI-written battlecards is confident staleness: models "know" competitors from training data that may be two years old, and they fill gaps with plausible fiction. The discipline this playbook enforces is simple — the model may only synthesize evidence you collected, every claim carries a source and a date, and anything unverifiable is marked as such. A battlecard sales trusts is a curated evidence file wearing a usable format.
Collect the evidence pack — you, not the model's memory. Per competitor, 20–30 minutes across: their pricing page, two or three product/feature pages, their positioning homepage headline, recent release notes or changelog, a G2/Capterra review skim (sort by recent), any recent funding or launch coverage, and your own CRM's last five win/loss notes against them. Save text snippets with URLs and access dates into one doc. If you use a browsing-enabled model or deep-research mode for collection, treat its output as leads to verify, not evidence — click through before anything enters the pack.
Run the synthesis pass on your evidence only.
Build a competitor battlecard from the evidence below. Use ONLY
this evidence — no background knowledge about this company. Every
claim must cite its source number and date. Where evidence is
missing or older than 6 months, write [UNVERIFIED] or [STALE —
date] rather than filling the gap.
Us: [YOUR PRODUCT, ICP, ONE-LINE POSITIONING]
Competitor: [NAME]
Evidence pack:
[1] Pricing page, accessed 2026-08-05: "..."
[2] G2 reviews (last 90 days), accessed 2026-08-05: "..."
[3] Closed-lost note, deal #482, 2026-07: "..."
[continue numbering]
Produce these sections:
1. SNAPSHOT: who they are, who they sell to, their positioning
claim in their own words [cite]
2. PRICING SIGNALS: model, published tiers, what's NOT public
3. WHERE THEY WIN: 3 honest strengths, with evidence — sales
only trusts a card that admits these
4. WHERE WE WIN: 3-4 differentiators, each tied to evidence of
their gap AND our capability
5. LANDMINES: questions our rep should get the prospect asking
early, phrased neutrally (e.g. "ask how implementation is
staffed"), each tied to the weakness it exposes [cite]
6. OBJECTION COUNTERS: for the 3 objections in our loss notes,
a 2-3 sentence factual response — acknowledge, reframe,
evidence
7. DISQUALIFIERS: deal shapes where they genuinely fit better
and we should qualify out
8. SOURCES: numbered list with URLs and access dates
Audit the card against the pack. The model will occasionally launder training-data "knowledge" into a cited section. Check every claim in sections 2, 4, and 5 against its cited source — the load-bearing sections. A trustworthy landmine entry looks like:
LANDMINE 3: "Ask them what's included in the base tier versus
paid add-ons for reporting." — Their advanced reporting moved to
a paid add-on in the March repackaging [1]; four recent G2
reviews cite surprise add-on costs [2]. [Checked 2026-08-05]
If a claim's source doesn't actually support it, cut it. A battlecard with seven bulletproof claims beats one with fifteen shaky ones — reps find out which claims are shaky in front of prospects.
Pressure-test with a red-team pass. In the same chat: "Now argue the competitor's side: how would their best rep counter each of our WHERE WE WIN points and neutralize each landmine?" Fold the strongest counters back into the card as "if they say X, respond Y" lines. A card that has already survived the counter-argument is what makes a rep confident live.
Publish in Notion with freshness machinery. One page per competitor from a shared template: the card, an evidence appendix, last_verified date on the page and per-claim, an owner, and a "field intel" comment thread where reps drop what they hear in deals (marked unverified until sourced). Set a quarterly review reminder; the refresh is fast — re-collect the pricing page and recent reviews, ask the model to diff old evidence against new: "What changed, and which claims on the card does each change affect?"
last_verified dates mean a stale card looks stale instead of confidently wrong.Use only public sources and your own deal notes. Never include material from NDA'd documents, a competitor's private roadmap a prospect shared, or anything a reasonable person would consider misappropriated — it's a legal exposure and, the day it's repeated in a deal, a reputation one. Anonymize your own customers in loss notes before pasting.
The battlecard's authority comes from the evidence pack, not the model. Collect real sources, let AI compress them into a fighting format, audit the citations, and date everything — because in competitive deals, a wrong claim delivered confidently is the most expensive sentence a rep can say.