See who your prospects compare you to, why they’re tempted, where you win and lose, and what changed since last month
A competitive landscape brief shows who prospects actually compare you to, where you win and lose by capability, which non-competitor alternatives are hardest to beat, and what changed since last month — built from sales call transcripts and CRM data with evidence counts and buyer quotes.
| Question | What you'll see |
|---|---|
| Who are we competing against? | Every alternative showing up in deals — named competitors, DIY workarounds, internal tools, spreadsheet workflows, and “do nothing” decisions |
| How often does each come up? | How many calls each alternative appeared in, whether that’s trending up or down, and who’s gaining ground vs. last period |
| Where do we win and lose? | What buyers say we’re better at, where they think we fall short, and the actual quotes organized by competitor |
| What are we losing to besides other vendors? | The spreadsheets, internal tools, and “it works fine” workflows that prospects default to instead of buying anything |
| What’s different from last month? | New competitors showing up, existing ones gaining or fading, new objections, and any win/loss shifts |
| What do we need to update or change? | Which battlecards to refresh, talk track gaps to close, product gaps to flag, and where to adjust positioning |
You are a competitive intelligence analyst preparing a monthly competitive landscape brief for a GTM leadership team.
Using the OnePerfectSlice data available to you, pull the most recent Competitive Intelligence and Alternatives Evaluated analyses and synthesize them into a structured brief covering:
1. LANDSCAPE SUMMARY
- How many distinct alternatives came up across calls this period?
- Breakdown by type: Named Competitor vs DIY vs Status Quo vs Do Nothing
- Which alternatives are increasing in frequency vs last period?
2. TOP COMPETITORS (by evidence count)
For each named competitor that appeared in 3+ deals:
- Who: Competitor name
- How often: Evidence count and frequency trend
- Where we win: Top win factors with a representative quote
- Where we lose: Top loss factors with a representative quote
- The wedge: The argument that beats them
- The threat: Why prospects are tempted
3. NON-COMPETITOR THREATS
For DIY, Status Quo, and Do Nothing alternatives with frequency of "Often" or "Always":
- What it is: Name and type
- Why it's sticky: The threat (why buyers default to it)
- How to beat it: The wedge
- Quote: What a prospect actually said
4. CAPABILITY BATTLEGROUND
Which specific capabilities are being compared most often? Rank by evidence count. For the top 5:
- Capability
- Our position (Win Factor / Loss Factor / Parity)
- Who we're compared against on this capability
- Representative quote
5. CHANGES SINCE LAST PERIOD
What's new or different vs the previous analysis:
- New competitors or alternatives that weren't there before
- Win/Loss factor flips
- Frequency changes
- New capabilities entering the battleground
6. RECOMMENDED ACTIONS
Based on the data:
- Battlecard updates needed
- Talk track gaps to close
- Product gaps to flag
- Positioning adjustments to consider
Format with clear headers and tables where appropriate. Include direct prospect quotes throughout. Every claim should cite the evidence count. Flag anything with fewer than 3 data points as "early signal."
Run these two OnePerfectSlice analyses first:
Recommended filters:
Skill version: v1 — May 2026
Period: [Last 30 days] ([X] calls analyzed)
Comparison baseline: [Previous 30 days] ([Y] calls)
Frequency trends vs. previous period:
[Competitor A] — Primary named threat
“[Competitor A] seemed fine at first, but when we dug into [specific need], it wasn’t there unless we upgraded twice.”
[Competitor B] — Declining
“[Competitor B] was too expensive and felt like more than we need right now.”
Spreadsheets + Email (Status Quo) — [28] evidence, ~40% of all mentions
“Honestly, [name] just handles it all manually right now. It works fine.”
Battlecard updates:
Talk track gaps:
Product gaps to flag:
Positioning adjustments:
Data: Competitive Intelligence ([X] calls) + Alternatives Evaluated ([Y] calls), [date range]. Claims with <3 data points flagged as “early signal.” Prompt v1 — May 2026.
What this is: A data-driven snapshot of what buyers are comparing you against, built from your real sales calls. Every claim is backed by evidence counts — the number of distinct calls where something came up. This isn’t opinion; it’s what prospects actually said.
These come directly from the AI synthesis and reflect how often an alternative comes up relative to the full call set — “Very Often” means it appeared in the majority of calls, “Occasionally” means a handful.
| What to do | How |
|---|---|
| Update your battlecards | Review the brief’s “Changes Since Last Period” and “Recommended Actions” sections. For each competitor with changes, update the relevant battlecard — positioning, objection handling, talk tracks, proof points. Push updates to wherever your team accesses them (Gamma, Google Slides, Confluence, Klue, Highspot, Seismic). Learn more about keeping battlecards current → |
| Share a competitive digest | Copy the “Changes Since Last Period” and “Top Competitors” sections into your competitive Slack channel or email. Strip the detail, keep the headlines — what’s new, what shifted, what to watch. |
| Explore the data | The brief is the starting point. With OnePerfectSlice connected to Claude, drill into the underlying data — “how does Competitor A come up differently in enterprise vs. mid-market?”, “what’s our biggest loss factor this quarter?”, “show me the pricing objections from renewal calls.” |
Parent concept
Job that produces this output
Sibling outputs (same program, different deliverable)
What to do with this output
You’ll start seeing patterns at around 30 calls per analysis window. Below that, you’re looking at anecdotes, not trends. The sweet spot is 50–200 calls. If you have fewer than 30 calls per month, run quarterly instead of monthly. The brief flags anything with fewer than 3 data points as “early signal” so you know what’s a pattern and what’s a one-off.
Yes. Both analyses support filters for call types, deal stages, company domains, account owner, and CRM fields. Run a brief for just enterprise deals, just renewals, or just one territory. This allows teams to generate enterprise-only competitive briefs, renewal-risk analysis, SMB vs enterprise comparisons, territory-specific competitor patterns, segment-level capability battlegrounds. A common operating model is: one company-wide monthly brief plus filtered briefs for strategic segments or regions.
Not completely. Win/loss interviews still provide depth and strategic nuance that this analysis alone may miss. Most companies only conduct a small number of win/loss interviews each quarter. Competitive landscape briefs complement that process by continuously analyzing conversations and crm data at larger volumes. The result is broader market visibility between formal win/loss cycles.
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