ClawDeployMarket Research Prompts for Every Stage
Structured prompts for market sizing, trend analysis, customer segmentation, and competitive intelligence — with example outputs.
These prompts help founders, product managers, and strategists conduct market research with AI. Each prompt is designed to produce structured, data-backed output — not generic summaries.
Market Sizing
Prompts for estimating TAM, SAM, and SOM with public data.
Estimate TAM, SAM, and SOM for an AI-powered code review tool targeting startups with 5-50 developers. Use funding data, developer population stats, and competitor revenue as proxy metrics.
TAM: $12B (global developer tools market) SAM: $2.1B (code review/quality segment) SOM: $80-200M (startups 5-50 devs, AI-native tools) Proxy: GitHub Copilot ($100M+ ARR), Snyk ($200M ARR). Developer tool spend ~$50/dev/mo average...
Estimate the market size for a SaaS tool that helps real estate agents write property listings using AI. Use a bottom-up approach: number of agents × potential adoption rate × price point.
Bottom-up estimate: - 1.5M active real estate agents in the US (NAR data) - ~30% tech-savvy enough to adopt AI tools (450K) - Realistic adoption: 5-10% in year 1 (22K-45K users) - Price: $19/mo average - Year 1 revenue potential: $5M-$10M - Mature market potential: $100M+ (if 15% adoption)
Estimate the growth rate of the AI customer support market for the next 3 years. Use current market data, funding trends, and adoption curves as evidence.
Estimated CAGR: 32-40% Evidence: - Current market: ~$2B (2025) - AI support funding: $1.2B in 2024 alone - Gartner: 40% of interactions AI-handled by 2027 (up from 15%) - Enterprise adoption: Early majority phase Projection: $2B → $3.5B (2026) → $5.8B (2027) → $8.2B (2028)
I'm building a Canva-like tool for presentation design. Use Canva's growth trajectory as a comparable to estimate my potential market. What were their key inflection points?
Canva trajectory: - 2013: Launch, 750K users year 1 - 2016: 10M users, first profitable year - 2020: 55M users, $500M ARR - 2024: 170M+ users, $2.3B ARR Key inflection points: Free tier viral loop, template marketplace, enterprise plan, education vertical. Presentation-specific TAM: ~$4B (presentation software). If you capture the "easy design" niche like Canva did for graphics, $200M-$500M is realistic at scale...
Trend Analysis
Prompts for identifying and analyzing market trends.
What are the top 5 emerging trends in the developer tools market for 2025-2026? Focus on trends with real traction signals, not hype.
1. AI-native code review (not just autocomplete) — Codium, CodeRabbit raising rounds. Developers want AI that understands context. 2. Internal developer platforms (IDP) — Backstage adoption growing 200% YoY. DevOps is shifting left. 3. Observability for AI systems — New category. LLM monitoring, token cost tracking...
Is "AI-powered recruiting" a real trend or just hype? Analyze funding data, product launches, search trends, and user sentiment in the last 12 months.
Verdict: Real trend with caveats. Funding: $1.8B into AI recruiting startups in 2024 (Findem, HireVue, Eightfold) Product launches: 12 new AI recruiting tools on Product Hunt in past 6 months Search trends: "AI recruiting tool" up 150% YoY Caveat: Strong backlash from candidates about AI screening. Companies are adopting but brand risk is real...
Where are AI agents on the technology adoption curve for SMBs? Early adopters? Early majority? Use real adoption data as evidence.
Current position: Late Early Adopter → Early Majority transition Evidence: - 12% of SMBs have deployed some form of AI agent (Salesforce 2024 survey) - "AI agent" search volume up 340% YoY - First mainstream tools emerging (ClawDeploy, Relevance AI) with sub-$50 pricing - Key signal: Non-technical users are starting to deploy agents (previously developer-only) Projection: Will enter Early Majority in 2026 as prices drop and deployment becomes zero-code...
Analyze the shift from "chatbots" to "AI agents" in the customer service market. What's changing, what's driving it, and what are the implications?
The chatbot → AI agent shift: What changed: Chatbots followed scripted flows. AI agents understand context, remember conversations, and take actions autonomously. Drivers: 1. LLM quality: GPT-4/Claude can actually resolve issues, not just deflect 2. Cost: Token costs dropped 90% in 2 years 3. Customer expectations: People expect instant, intelligent responses Implications: - Rule-based chatbot vendors (ManyChat, Chatfuel) are losing to AI-native players - "Resolution rate" replacing "deflection rate" as the key metric - Support team roles shifting from answering to supervising agents...
Customer Segmentation
Prompts for identifying and understanding target customer segments.
Identify the top 4 customer segments for an AI scheduling assistant. For each, describe: who they are, their primary pain point, willingness to pay, and best acquisition channel.
1. Solo consultants (freelancers doing 15+ meetings/week) - Pain: Scheduling back-and-forth wastes 3-5 hours/week - WTP: $10-20/mo (price-sensitive but high pain) - Channel: Twitter/X indie maker community, Product Hunt 2. Startup founders (seed to Series A) - Pain: Calendar is 80% meetings, 20% actual work - WTP: $20-40/mo (time is extremely valuable)...
Define the ideal customer profile for ClawDeploy. Include: company size, industry, role of buyer, budget, pain points, and current solution.
Ideal Customer Profile: Company: 1-50 employees, B2B SaaS or e-commerce Industry: Tech, e-commerce, digital services Buyer: Founder, Head of Operations, or Customer Support Lead Budget: $25-100/mo for automation tools Pain points: Overwhelmed by repetitive tasks, can't afford to hire, need 24/7 coverage Current solution: Manual processes, Zapier for basic automation, or nothing (just grinding) Best-fit signal: They're already using Telegram, Discord, or WhatsApp for business communication.
Create a detailed buyer persona for a content marketing AI tool. Include demographics, goals, frustrations, tools they use, and where they hang out online.
Persona: "Content-Stretched Sarah" Role: Solo content marketer at a Series A SaaS (20 employees) Age: 28-35, based in a major US city Goals: Publish 4 blog posts/month, grow organic traffic 30% QoQ Frustrations: Spends 60% of time on research and outlining, only 40% on writing. Always behind on the content calendar. Tools: Notion, Google Docs, Ahrefs, Canva, Buffer Online: r/contentmarketing, Twitter/X marketing community, Superpath Slack group Budget authority: Up to $50/mo without manager approval...
I have 4 potential customer segments for my product. Rank them by: market size, ease of acquisition, willingness to pay, and retention potential. Help me decide who to target first.
Segment ranking: | Segment | Market Size | Acquisition | WTP | Retention | Score | |---|---|---|---|---|---| | Solo founders | Large | Easy (communities) | Medium | Medium | 7.5/10 | | Agency teams | Medium | Medium (cold outreach) | High | High | 8/10 | | Enterprise | Large | Hard (sales cycle) | Very High | Very High | 6/10 | | Freelancers | Very Large | Easy | Low | Low | 5/10 | Recommendation: Start with Agency teams (best balance of WTP and retention), then expand to Solo founders (easier acquisition, lower revenue per user)...
Competitive Landscape
Prompts for mapping and analyzing competitors.
Map the competitive landscape for AI writing tools. Categorize by: target audience, pricing tier, and primary use case. Identify where the white space is.
Competitive map: Enterprise ($50+/mo): Jasper, Writer.com, Copy.ai Enterprise Prosumer ($15-49/mo): Copy.ai, Writesonic, Rytr Freemium: ChatGPT, Claude (via direct API) Developer-focused: GPT API, Anthropic API White space: 1. Niche-specific writers (real estate, legal, medical) at $20-30/mo 2. Team collaboration features (shared prompts, brand voice) at prosumer pricing 3. "Workflow" writers that integrate into existing tools (not another editor)...
Compare ClawDeploy's features against the top 3 competitors. Where do we win, where do we lose, and what features would close the biggest gaps?
Feature comparison vs. top 3: | Feature | ClawDeploy | Competitor A | Competitor B | Competitor C | |---|---|---|---|---| | Setup time | ✅ <2 min | ❌ 30 min | ❌ 1 hour | ⚠️ 10 min | | Messaging channels | ✅ 3 | ⚠️ 1 | ❌ 0 | ⚠️ 2 | | No-code | ✅ | ❌ | ❌ | ✅ | | Custom personas | ✅ | ✅ | ✅ | ⚠️ | | Team features | ❌ | ✅ | ✅ | ❌ | | API access | ❌ | ✅ | ✅ | ❌ | Biggest gap to close: Team features (shared agents, role-based access). This blocks us from team plan upsells...
Analyze how our top 5 competitors position themselves on their homepages. What messaging themes dominate? Where can we differentiate?
Homepage positioning analysis: Common themes (all 5 use): - "AI-powered" or "AI-first" (table stakes, not differentiating) - "Save time" / "automate" (everyone claims this) Differentiating themes: - Competitor A: "Enterprise-ready" (security, compliance focus) - Competitor B: "For developers" (API-first, code examples) - Competitor C: "No-code AI" (visual builder, templates) Our whitespace: Nobody leads with SPEED + SIMPLICITY + CHANNELS. "Deploy in 2 minutes to Telegram/Discord/WhatsApp" is unique. Lean into this harder...
Frequently Asked Questions
How accurate are AI-generated market size estimates?
They're directional, not precise. Use them for go/no-go decisions and order-of-magnitude estimates. Always verify critical numbers from primary sources before raising funding or making large bets.
Can I use these prompts for investor pitch research?
Yes. The market sizing and competitive landscape prompts are specifically useful for pitch decks. Just verify the key data points independently — investors will check.
Do these work with free AI models?
Yes, but paid models (Claude Pro, GPT-4) produce more detailed and accurate research. For market sizing, the quality difference is significant.
How often should I re-run market research prompts?
Quarterly for established markets, monthly for fast-moving spaces like AI. Markets shift quickly — stale research leads to stale strategy.