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AI for Competitive Intelligence Webinar March 26th

•57:06
AI Tool Guide

This webinar shows you how to track competitors and market trends with AI: deep research reports in Claude or Perplexity, LinkedIn post scraping with Apify, and a Claude Code dashboard that refreshes every day.

Pour qui: Business owners and operators who want a steady, low-effort read on what their competitors and their market are doing, without paying for a dedicated intelligence tool.

Téléchargement gratuitCompetitor Intelligence Prompt KitThe prompts from the webinar for market research, competitor research and LinkedIn tracking with Claude Code and Apify, plus the three privacy levels.
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À retenir

  1. Start with deep research you already pay for

    Claude, ChatGPT, Gemini and Perplexity all have a deep research mode. Write a plain prompt with the right keywords (your market, customer size, region, what you want to know), switch on Research, and pick the biggest model for tasks that need reasoning. A run takes around five to ten minutes. My point: this costs about twenty dollars a month and not enough people use it.

  2. Research each competitor company, then repeat on a schedule

    Paste a competitor's website or LinkedIn page and ask for the people who work there, recent hires, product launches and anything that could widen your own services. The report I got covered founding date, employees, website claims, day rates and weak spots, pulled from sources like LinkedIn, Glassdoor and the French company site Papers. If you do not know your competitors yet, first ask AI to list them, then research each one.

  3. Social media shows what reports miss

    Any public profile on LinkedIn, YouTube, Instagram or TikTok can be tracked. Look at both the people and the company page, since many companies post little on their own page. Apify, a library of scrapers, pulls a post's content and everyone who engaged with it. From that raw data you can spot a new client, a new hire or a new offer. Use many posts over time, not one.

  4. Build a 'parasite system' with Claude Code and Apify

    With Apify connected, I ask Claude Code in plain language to fetch the last ten posts from a competitor's profile, then the posts from their company page. The next steps are a dashboard, then deploying it so it runs every 24 hours, or every seven days if your industry moves slowly. As I put it: connect Claude Code to a service and tell it to redo everything every 24 hours.

  5. Track keywords, not only people

    When competitors or prospects are spread across platforms and languages, monitor a topic instead. My system pulls LinkedIn posts containing the keyword Claude every morning and sorts them: power user, someone migrating from ChatGPT, or noise. The same data serves competition tracking and prospecting, depending on how you treat it. Spotting a theme before it goes mainstream helps you stay ahead.

  6. Check sources before you use a claim

    Deep research reports list their sources, so you can verify them yourself or have a second AI check them. You can also favor or block sources. I recommend Perplexity for this: under connectors and sources you choose academic, social or web, and the Pro plan lets you narrow down to specific websites.

  7. Three levels of privacy

    Level one: in your AI tool's settings, turn off data sharing (in Claude, Privacy, then turn off Help Improve Claude). Level two: contact the provider's sales team about a zero data retention agreement. Level three: local models. Claude Code's 'brain' runs on the provider's servers even when it reads your local files. Swap in a local brain (I point to Ollama) for full privacy, with less power and a stronger computer.

Outils présentés

Questions du public

Can you trust the numbers a deep research report gives you, like what competitors charge?

Every deep research report comes with its sources, so the data is verifiable. You can verify it yourself or have another AI go through the sources and check them. You can also list preferred sources or blacklist ones you do not trust. Even with checking, gathering the data this way is much faster than fetching it all yourself. For tighter control over sources, I point to Perplexity, where you choose academic, social or web sources and, on Pro, specific websites.

Do I need to build my own RAG to compare dashboards with private company data?

In my opinion it is not worth it. Start with privacy settings: turn off data sharing in your AI tool (in Claude, the Help Improve Claude option under Privacy). Next, contact sales for zero data retention. For full privacy, use a local model. Claude Code already does the work of a RAG, so you keep Claude Code as the 'body' and replace the remote 'brain' with a local one such as Ollama. It is less powerful and needs a stronger computer.

Should I use Gemini CLI or Antigravity instead of Claude Code?

I tested Gemini as a budget version of Claude Code because it was very good for students. Lately, in my experience, Google gives less usage than it advertises, and results from Antigravity have not been very good either. I find it hard to recommend Google tools right now and still recommend Claude Code as the main tool.

Claude Code keeps wandering into the wrong connected tools or says my documents are too big. What should I do?

The 'document too big' message is not the real limit, since the models now have very large memory. The fix is to organize your workspace well. I keep my knowledge siloed: each skill points to one precise data point or one folder. I do not write the skills myself. I run one workflow end to end with Claude Code, then asks it to turn that workflow into a skill.

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