What are the 5 ways to ground AI in trusted sources?
Grounding is the solution to cold starts, generic output, and hallucinations. The more context
you give AI, the better it performs.
- Attachments & files — upload PDFs, spreadsheets, documents, or images as direct context
- Web pages — point AI to specific URLs for reference material
- Deep research — send AI to scour the internet and return structured findings
- Instructions & system prompts — give AI rules, brand voice guidelines, and step-by-step procedures to follow
- Knowledge bases & external data — connect AI to databases, CRMs, and other live data sources (increasingly powerful as of February 2026)
How do I structure a competitive mapping prompt?
This prompt sends AI to research competitor marketing hooks and messaging angles across ads, landing pages, and social posts — and returns everything in a structured table.
| Section |
What to include |
Example |
| Objective |
Tell AI why it exists — what you want it to build |
"Build an evidence-backed dataset of competitor marketing hooks and messaging angles" |
| Inputs (Competitors) |
List the businesses to research (1–10+) |
"WebFX, Ignite Visibility, SmartSites" |
| Scope |
Where to look and what to find |
"Paid ads, landing pages, social posts — look at Meta Ad Library, TikTok Creative Center, LinkedIn" |
| Output format |
Define the table columns you want |
"Competitor, Source, Platform, Hook Category, Hook/Angle, Primary Promise, Pain Point, CTA" |
| Example row |
Show AI what a completed row looks like |
A filled-in example row with real data so AI knows the quality bar |
Pro tip: You can adjust every part of this prompt. Change the competitors, change what you're looking for (positioning statements, pricing models, CTAs), and change the output columns.
How do I structure a voice of customer research prompt?
This prompt sends AI to collect verbatim customer quotes from review sites, forums, and social media — then transforms them into usable messaging angles.
The prompt returns two tables:
| Table |
Purpose |
Columns |
| Table 1: Raw Quotes |
Verbatim voice of customer — exactly what people said |
Quote, Source, Platform, Sentiment (positive/negative), Pain Point or Desire, Emotional Intensity |
| Table 2: Messaging Angles |
Structured marketing hooks derived from the research |
Core Pain/Desire, Messaging Angle, Headline, Support Bullets, Content Hook, CTA Direction |
Example result: For bereavement gifts, VoC research surfaced hooks like "The gift that doesn't wilt in a week" and "Be the one who still remembers — grief doesn't end after the funeral." These came directly from real customer language.
What is the research-to-content workflow?
This is the step-by-step process for turning deep research into published marketing content.
- Run deep research — use a competitive mapping or VoC prompt to gather structured data from across the internet
- Surface the best hooks — ask AI to find the top 10 most contrarian, out-of-the-ordinary, or pattern-breaking hooks from the research
- Pick one hook to develop — choose the hook that best fits your brand, audience, or campaign
- Create outlines — ask AI to outline 2–3 LinkedIn posts, emails, or ads based on the selected hook
- Draft in Canvas — move the best outline into ChatGPT Canvas (or Claude Cowork) for editing and refinement
- Polish and publish — use AI to add subheadings, tighten copy, adjust tone, and finalize for publishing
Key insight: The real power isn't in the research itself — it's in grounding your content creation in real data. Every piece of content you create after deep research will be sharper because it's based on actual market language, not guesswork.
FAQ
What is deep research in AI?
Deep research is an AI agent mode available in ChatGPT, Claude Cowork, Gemini, and Perplexity. It sends AI to scour the internet for 10–20+ minutes, searching dozens of sources and synthesizing findings into structured tables, reports, or datasets you can use immediately.
Do I need ChatGPT Plus for deep research?
Yes, ChatGPT deep research requires a Plus subscription ($20/month) or higher. Claude Cowork also offers deep research capabilities starting at $20/month. Gemini and Perplexity have their own research modes with varying plan requirements.
How long does a deep research task take?
Expect 10–20 minutes depending on scope and tool. ChatGPT took about 20 minutes for competitive mapping in the training demo. Claude Cowork completed the same task in roughly 10 minutes because it processes searches in parallel.
Can I use deep research for my own brand instead of competitors?
Absolutely. Swap competitor names for your own brand, client brands, or product categories. The voice of customer prompt works especially well for discovering how real customers talk about your products or industry, which you can turn into marketing copy.
What is meta prompting and why should I use it?
Meta prompting means using AI to write your research prompts. Brain-dump everything you want — competitors, goals, format — and ask AI to build the prompt. This produces more thorough, better-structured prompts than most people write manually.
What's the difference between competitive mapping and voice of customer research?
Competitive mapping analyzes competitor marketing — hooks, angles, CTAs, and positioning across ads and landing pages. Voice of customer research collects what real customers say in reviews, forums, and social media, then transforms those quotes into usable messaging angles.
Can deep research access sites that require a login or payment?
No. Deep research can only access publicly available content on the open internet. It cannot log into accounts, access paywalled articles, or run surveys. For gated data, upload files or screenshots as attachments to ground your AI manually.
Why is grounding AI important for marketing?
Without grounding, AI produces generic output (the boiled chicken problem). When you ground AI in real competitor data, customer language, or brand files, output becomes specific, relevant, and usable. Grounding is the single biggest factor in AI output quality for marketers.
Should I use ChatGPT or Claude Cowork for deep research?
Use ChatGPT for quick one-off research tasks — it's simpler to start with. Use Claude Cowork for ongoing workflows where you need persistent files, brand voice consistency, and self-healing skills. Both produce strong research; the difference is what happens after.
How do I turn deep research results into actual marketing content?
Follow the research-to-content workflow: run deep research, ask AI to surface the top hooks, pick one to develop, outline posts or emails based on it, draft in Canvas, then polish and publish. The key is taking the next step beyond the research itself.
