Market Research and Competitive Intelligence

Research That Used to Take Weeks

Traditional market research goes something like this: hire a research firm, wait three weeks, get a 60-page report, realize half of it is filler, extract the five insights that actually matter.

Or the scrappy version: spend a week reading competitor websites, scrolling through Reddit threads, and skimming industry reports. Write up your findings in a Google Doc that nobody reads.

AI compresses both of these into hours. Not by making things up—by processing and synthesizing real data faster than any human could. You still need the data. You still need judgment about what matters. But the analysis? That’s where AI becomes your unfair advantage.

Step 1: Competitive Landscape Analysis

Start with your competitors. Here’s the prompt framework:

I'm analyzing the competitive landscape for [your product/service].
Here are our top 5 competitors and their positioning:

1. [Competitor A] - [their website URL and key messaging]
2. [Competitor B] - [their website URL and key messaging]
3. [Competitor C] - [their website URL and key messaging]
4. [Competitor D] - [their website URL and key messaging]
5. [Competitor E] - [their website URL and key messaging]

For each competitor, analyze:
- Core value proposition (what they promise)
- Target audience (who they're speaking to)
- Pricing model and positioning (premium, value, freemium)
- Key messaging themes (what words/phrases they use repeatedly)
- Apparent strengths and weaknesses

Then identify:
- Common themes across all competitors (what everyone says)
- Messaging gaps (customer needs nobody is addressing)
- Opportunities for differentiation

The key here: feed AI real data. Copy actual text from competitor websites, their homepage hero sections, their pricing pages. Don’t just give names and let AI hallucinate their positioning.

Here’s what this looks like with real data. Say you’re launching an AI writing tool:

Competitor analysis data:

Jasper.ai homepage: "AI marketing platform that helps you
create high-quality content 10x faster. Trusted by 100,000+
teams. Enterprise-grade AI with brand voice control."

Copy.ai homepage: "Go-to-market faster. AI-powered content
creation for sales and marketing teams. From brainstorm to
publish in seconds."

Writer.com homepage: "Enterprise AI built on your data.
Not just content—full-stack AI for work. SOC 2 compliant."

AI identifies patterns: everyone’s targeting “teams” and emphasizing speed. Nobody’s talking to solo creators. Nobody’s emphasizing learning and skill improvement. Those are potential gaps.

Step 2: Customer Voice Mining

The richest market research data is hiding in plain sight: customer reviews, forum posts, support tickets, and social media comments.

Here are 20 customer reviews of [competitor product]
from G2/Capterra/Amazon. Analyze them for:

1. Most common praise (what do customers love?)
2. Most common complaints (what frustrates them?)
3. Unmet needs (what do customers wish it did?)
4. Emotional language (what feelings come up repeatedly?)
5. Use cases (how are customers actually using this?)

[paste 20 reviews]

This analysis reveals things surveys never capture. When you read that a customer wrote “I spend more time formatting the output than writing it myself,” that’s a product insight and a marketing message rolled into one.

The emotional language is gold. When customers say “I feel stupid using this” or “It’s like having a senior marketer on my team,” those exact phrases become your marketing copy. AI identifies these patterns across hundreds of reviews in seconds.

Step 3: Building Data-Driven Personas

Forget the fake personas with stock photos and made-up names. AI helps you build personas from actual data:

Based on the customer review analysis above, plus these
additional data points:

- Our website analytics show 60% of visitors are from
  companies with 1-50 employees
- Most popular pages: pricing, integrations, "How it works"
- Top search queries that bring people to competitors:
  "AI writing tool for small business", "content marketing
  on a budget", "write blog posts faster"

Create 2-3 customer personas. For each, include:
- Role and company size
- Primary goal (what they're trying to achieve)
- Key frustration (what's blocking them)
- Decision criteria (what matters when choosing a tool)
- Objections (why they might NOT buy)
- Where they spend time online
- Quotes from actual reviews that represent this persona

AI produces personas grounded in reality:

Persona: The Overwhelmed Content Manager

• Role: Solo content marketer at a 20-person SaaS company
• Goal: Produce 3x more content without hiring
• Frustration: “I spend 4 hours on every blog post and my boss wants weekly output”
• Decision criteria: Quality of output, ease of use, price
• Objection: “AI content is generic and doesn’t sound like our brand”
• Hangs out: LinkedIn, marketing Slack communities, HubSpot blog
• Representative quote: “I don’t need more templates. I need something that actually understands my industry.”

This persona isn’t imaginary. Every detail comes from real data. That last quote? Pulled directly from a customer review.

Quick Check: Data Quality

You’ve collected 50 competitor reviews. Before feeding them to AI, which of these would produce the most useful insights?

A) All 50 reviews, unfiltered B) Only the 5-star and 1-star reviews C) Reviews filtered to your target market segment, including 1-5 star ratings

The answer is C. You want the full range of opinions, but filtered to the segment you’re targeting. A solopreneur’s review of an enterprise tool isn’t relevant if you’re targeting mid-market companies.

Step 4: Market Sizing and Opportunity Assessment

AI can help you estimate market opportunity, though you should verify the numbers:

Help me estimate the market opportunity for an AI writing
tool targeting solo content marketers at companies with
10-100 employees.

Known data points:
- There are approximately 33 million small businesses in the US
- 64% of small businesses have a website
- Content marketing adoption among small businesses is ~60%
- Average content marketing budget: $5,000-15,000/year
- Our target price point: $49/month

Walk me through a TAM, SAM, SOM analysis.
Flag any assumptions I should verify.

The “flag assumptions” instruction is critical. AI will tell you which numbers it’s estimating versus which come from your provided data. Verify the estimates before putting them in a pitch deck.

Putting It All Together: The Research Brief

After completing your analysis, have AI compile everything into a structured brief:

Compile our market research into a one-page strategic brief.
Include:

1. Market Overview (2-3 sentences)
2. Target Customer (primary persona, one paragraph)
3. Competitive Landscape (key competitors and their positioning)
4. Market Gaps (opportunities nobody is addressing)
5. Customer Pain Points (top 3, with supporting evidence)
6. Strategic Implications (what this means for our positioning)

Source everything from the analysis we've done.
Keep it concise—this will be read by executives.

This brief becomes the foundation for everything else in the course. Your positioning, campaigns, messaging—all built on actual market data rather than assumptions.

Practical Exercise

Try this now with your own product or service:

1. Collect homepage messaging from your top 3 competitors
2. Find 10 customer reviews of your strongest competitor
3. Feed both into an AI assistant using the prompts from this lesson
4. Generate a competitive analysis and one customer persona

Even this abbreviated version will reveal insights you didn’t have before. And it’ll take less than an hour.

Key Takeaways

• AI-powered research requires real data—competitor content, customer reviews, analytics
• Customer voice mining from reviews reveals emotional language and unmet needs
• Data-driven personas are built from patterns in real customer behavior, not imagination
• Always verify AI’s market claims against actual sources
• The research brief becomes the foundation for all subsequent strategy work

Next up: positioning. You’ve mapped the competitive landscape and identified gaps. Now it’s time to stake your claim—defining exactly why customers should choose you.

Up next: In the next lesson, we’ll dive into Positioning, Messaging, and Brand Voice.