Positioning prompts

AI competitor social positioning prompt

Analyze competitor social posts by repeated topics, claims, proof, audience, and category narrative.

This is a working analyst brief. Sources go in. Patterns, risks, and decisions come out.

Use this prompt

You are a social positioning analyst.

Find how the competitor is using social content to shape buyer beliefs and category language.

My company:
{{my_company}}

Competitor:
{{competitor}}

Market:
{{market}}

Sources:
{{sources}}

Return:
1. Repeated themes and claims.
2. Audience cues and buyer language.
3. Proof used in posts.
4. Topics that create category authority.
5. Topics that are noise.
6. Social angles we can test with our own proof.

Rules:
- Use only the sources I provide.
- Do not invent metrics, spend, conversion rates, private pricing, customers, or intent.
- Mark unsupported claims as [UNVERIFIED].
- Separate observation, interpretation, and recommendation.

Advanced AI technique settings:
- Source-grounded context pack: Build a source table first with source, date checked, claim, confidence, and business meaning. Use only that table for the final recommendations.
- Pattern clustering: Cluster repeated signals before interpreting them. Label one-off examples as one-offs and do not treat them as strategy.
- Counterfactual options: Give at least one alternative interpretation and one reason the main recommendation could be wrong.
- Evidence rubric: Score each important finding by evidence strength, relevance, business impact, and reversibility before recommending an action.
- Verification loop: After the first draft, run a verification pass that lists unsupported claims, stale details, missing sources, and recommendations to downgrade or remove.

Copy the prompt. Fill the variables. Then check the output for real.

Advanced AI techniques

Use these techniques for this prompt

These are selected for this specific competitor research job. Use the prompt-ready instruction when it helps, and skip it when the condition does not fit.

Source grounding

Source-grounded context pack

Use when: Use when the answer depends on competitor pages, screenshots, ads, pricing, SEO exports, or reviews.

Prompt move: Build a source table first with source, date checked, claim, confidence, and business meaning. Use only that table for the final recommendations.

Skip when: Skip only for brainstorming with no factual claims.

Pattern analysis

Pattern clustering

Use when: Use for batches of ads, emails, social posts, reviews, SEO pages, or competitor claims.

Prompt move: Cluster repeated signals before interpreting them. Label one-off examples as one-offs and do not treat them as strategy.

Skip when: Skip for a single landing page or one pricing table.

Strategy critique

Counterfactual options

Use when: Use when the output recommends positioning, offer, creative, content, or product moves.

Prompt move: Give at least one alternative interpretation and one reason the main recommendation could be wrong.

Skip when: Skip for factual extraction or source verification.

Decision-quality scoring

Evidence rubric

Use when: Use when recommendations could change strategy, positioning, pricing, ads, or product priorities.

Prompt move: Score each important finding by evidence strength, relevance, business impact, and reversibility before recommending an action.

Skip when: Skip for prompts that only organize notes without recommending action.

Verification workflow

Verification loop

Use when: Use before sharing research with a client, team, sales deck, ad brief, or website backlog.

Prompt move: After the first draft, run a verification pass that lists unsupported claims, stale details, missing sources, and recommendations to downgrade or remove.

Skip when: Skip only for private rough notes.

Replace placeholders

Replace these variables before running the prompt

Variable	Meaning	Type	Example
`{{my_company}}`	Your company, product, or brand	string	Northstar CRM
`{{competitor}}`	The competitor you want to analyze	string	Acme CRM
`{{market}}`	The category or market context	string	B2B CRM for agencies
`{{sources}}`	URLs, screenshots, notes, exports, or pasted copy	list	Homepage URL, pricing URL, ad screenshots

Expected shape

Compare a filled input with a realistic output shape

The output below is fictional. It shows the shape you are looking for, not a real competitor result.

Example input

my_company = DevBrief
competitor = BuildNote
market = developer documentation tools
sources = 30 LinkedIn posts, X posts, profile copy, dates

Fictional example output

Fictional example output:

Repeated theme: docs as revenue infrastructure.
Proof pattern: customer quotes, but few product screenshots.
Test: publish one teardown of broken docs handoff with real workflow screenshots.

Prompt logic

Why this prompt works

It reads social as positioning, not just content volume.
It separates category ideas from noise.
It produces angles tied to proof.

Mistakes to avoid

Asking the AI to analyze a competitor with no sources.

Paste the page copy, ad screenshots, pricing table, SEO notes, or transcript first.

Treating the output as research truth.

Use it as a source-backed brief: keep strong evidence, downgrade weak evidence, and decide what deserves action.

Asking for generic strategy advice.

Ask for observations, risks, and next actions tied to the evidence.

Verification checklist

Every factual claim has a source or is marked as unverified.
Pricing, dates, and product claims were checked on the original source.
The output separates observation from interpretation.
The output gives actions you can reject, edit, or test.
Nothing is treated as final just because an AI tool wrote it.

Use the output safely

What you should do next

Collect posts over a date range.
Group themes before judging them.
Turn one verified theme into a content test.