Market Research & Business Case Generator
Send a market topic via chat to generate a structured business case study with live research, saved directly to Google Docs.
What it does
Define your market research topic in chat to instantly generate a structured business case study with live industry data and trends. This process synthesizes the findings into a detailed report that saves directly to your Google Docs for immediate use.
Step by step
- The workflow begins with a chat trigger that captures the initial user prompt and passes it to the first LLM for structuring.
- Perplexity API calls are made using structured queries generated by the scope definition step to retrieve live industry data.
- The final synthesized document is written to Google Docs via the official API, creating or updating a specific file ID.
Where the LLM does the work
- OpenAI must interpret vague user inputs into precise search parameters and research angles for Perplexity.
- Anthropic needs to synthesize disparate web results into a coherent narrative with professional business tone.
- The system should dynamically adjust the depth of research based on the complexity of the initial market topic.
Watch out for
Google Docs API permissions may fail if the service account lacks write access, verify OAuth scopes before deployment.
Context window overflow from large research dumps can degrade writing quality, chunk the Perplexity results before sending to Anthropic.
Tools that fit
Anthropic Chat Model LLM Synthesizing findings into case study
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Market Research & Business Case Generator: Send a market topic via chat to generate a structured business case study with live research, saved directly to Google Docs. ## Specification - What it does: Define your market research topic in chat to instantly generate a structured business case study with live industry data and trends. This process synthesizes the findings into a detailed report that saves directly to your Google Docs for immediate use. - Trigger: Run manually (Manual · on chat prompt) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - OpenAI: Research scope definition - Perplexity: Live web research and data retrieval - Anthropic Chat Model: Synthesizing findings into case study - Google Docs: Saving final output ## Known pitfalls, handle each one explicitly in your implementation 1. Google Docs API permissions may fail if the service account lacks write access, verify OAuth scopes before deployment. 2. Context window overflow from large research dumps can degrade writing quality, chunk the Perplexity results before sending to Anthropic. ## Reference implementation https://n8n.io/workflows/5430 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/market-research-business-case-generator/ via usecasesforagents.com
Frequently asked questions
Can I use a different LLM than OpenAI?
Yes. OpenAI is only the example LLM in this recipe. The same flow works with Anthropic, Cohere, DeepSeek and Google Gemini. Swap the LLM connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need research handled without hiring for it.
Freelancers and consultants can run this per-client with no changes beyond the source data.
Analysts get a ready-made pattern for turning raw numbers into a report someone will actually read.