Research Prompts

You're an SEO strategist doing a content gap analysis. I've uploaded two Google Search Console exports from the last 3 months: - Queries.csv (search queries with clicks, impressions, CTR, position) - Pages.csv (my URLs with clicks, impressions, CTR, position) Note: these files aren't linked, so match queries to pages by comparing query topics to URL slugs and page themes. Tell me when a match is a guess. Find: 1. Missing content: queries with meaningful impressions where no page on my site clearly targets that topic. Group related queries into topic clusters. 2. Striking distance: queries ranking in positions 8–20 with solid impressions, where a better or more focused page could reach the top 5. 3. Underperforming visibility: queries or pages with high impressions but CTR well below what their position should get. Suggest why (title mismatch, wrong intent, weak snippet). 4. Question and comparison queries (how, what, best, vs, alternatives) that deserve a dedicated answer-style page. These are also the ones most likely to get cited in AI search. Ignore branded queries and anything with fewer than 10 impressions. Output: - A prioritized table: Topic/Query cluster | Total impressions | Avg position | Gap type | Recommended action (new page / update existing URL / rewrite title) | Priority (High/Med/Low) - Top 5 content pieces to create first, each with a suggested title, target queries, and one line on search intent - Top 5 quick wins on existing pages Use only numbers from my files. Don't invent search volumes or keywords that aren't in the data.

Conduct deep competitive intelligence on [COMPETITOR NAME]: COMPANY OVERVIEW: - Founding story and key milestones - Leadership team (backgrounds, previous companies) - Funding history (rounds, investors, valuations, burn rate estimates) - Employee count and growth trajectory (check LinkedIn headcount) - Office locations and expansion patterns PRODUCT DEEP-DIVE: - Complete product catalog with descriptions - Pricing tiers (current + historical changes) - Feature comparison vs top 3 alternatives - Technology stack (from job postings, tech blogs, BuiltWith) - Recent product launches (last 12 months) - Roadmap clues (from: job postings, conference talks, patent filings, customer surveys) MARKET POSITIONING: - Target customer (size, industry, characteristics, job titles) - Ideal Customer Profile (ICP) based on case studies - Messaging and positioning (analyze website, ads, content) - Brand voice and personality - Key differentiators they claim GO-TO-MARKET STRATEGY: - Marketing channels (paid, organic, partnerships) - Content strategy (blog topics, frequency, engagement) - Sales approach (inbound vs outbound, PLG vs sales-led) - Partnership ecosystem (integrations, resellers, tech partners) - Event presence (conferences, webinars, sponsorships) CUSTOMER INTELLIGENCE: - Review analysis (G2, Capterra, TrustPilot - what do users love/hate?) - Common complaints (from Reddit, Twitter, support forums) - Feature requests and gaps (from public roadmap, user forums) - Churn signals (Glassdoor reviews, customer testimonials that stopped) STRATEGIC VULNERABILITIES: - What are they bad at? (based on reviews, hiring patterns) - What markets are they ignoring? - Where are they overextended? - Technology debt or legacy issues - Pricing weaknesses or gaps THREAT ASSESSMENT: - How aggressive are they in OUR market? - What would it take to compete effectively? - What could they do that would hurt us most? - Early warning signals to monitor Use: Recent sources only (last 18 months). Prioritize primary sources (their blog, official announcements, verified reviews). Flag speculation vs confirmed facts. Include URLs for verification.

You are a local SEO strategist who specializes in Google Business Profile optimization through competitive intelligence. Your methodology is called "Chameleon" — you don't give generic GBP advice. Instead, you reverse-engineer what's actually working for the top-ranking competitors in a specific market, identify the patterns and signals driving their success, then build an adaptive strategy that absorbs those winning patterns while exploiting competitor vulnerabilities. I'm going to give you a client's Google Business Profile and 2-5 competitor GBPs from the same market. Here's what I need you to do: Step 1: Extract Data From Every Profile For the client AND each competitor, pull every available data point: Business name, primary category, all secondary categories Business type (service area business vs. storefront vs. hybrid) Service areas listed, services listed, products listed Total review count, average rating, review velocity (reviews per month over last 6-12 months), review recency, whether reviews contain keyword mentions of services/locations Owner response rate and quality (templated vs. personalized, keyword usage in responses) Photo count, photo velocity (uploads per month), photo types (team, jobs, equipment, etc.) GBP post frequency, post types (offers, updates, events, project showcases), last post date Business description (full text, keyword usage, CTA presence) Attributes filled out, Q&A section populated or empty Hours accuracy, appointment/booking links, website URL Whether the business operates multiple GBP listings across the metro area Step 2: Build the Competitive Benchmark Once you have data on all profiles, build a comparison matrix. For every metric, calculate the market minimum, median, and leader — then show exactly where the client sits and what the gap is. Don't just list numbers. Identify the PATTERNS: What category combinations do the top performers share? What review velocity sustains a map pack position in this market? What photo count and type is the competitive floor? Are leaders using GBP posts, and if so, what kind and how often? Are leaders using the Products or Q&A sections that others ignore? Are any competitors running multiple listings or DBA strategies? Step 3: Find the Attack Vectors Identify where competitors are weak or lazy — stale review velocity, no recent posts, generic owner responses, thin services lists, missing Q&A, no photos in months. These gaps are where the client can leapfrog without needing to match total volume. Prioritize the vulnerabilities that align with high-impact ranking signals. Step 4: Build the Chameleon Strategy Using the competitive consensus and vulnerability analysis, write a specific optimization plan for the client. Every single recommendation must reference actual competitor data — no generic advice. Structure it as: Immediate fixes (week 1) — what's broken or missing right now Category & service optimization — what to add based on competitor reverse-engineering Review acceleration plan — target velocity, generation tactics, owner response protocol with natural keyword integration Visual content strategy — photo targets, types, velocity, geotagging GBP post strategy — cadence, content mix, keyword integration, CTAs Q&A section — seed 10-15 keyword-rich questions and answers Business description rewrite — 750 chars max, keyword-optimized, clear CTA Multi-profile strategy — whether additional listings make sense based on what competitors are doing Step 5: Set the Priority Dials Assign a priority weight (1-10) to each optimization dimension based on where the biggest gaps and opportunities exist for THIS client in THIS market. The highest-weighted areas are where effort produces disproportionate results. Explain why each dial is set where it is. Step 6: 90-Day Execution Roadmap Break everything into Month 1 (foundation), Month 2 (momentum), Month 3 (dominance) with specific actions, targets, and benchmark checkpoints. Tone & Format Write this as a strategic intelligence briefing, not a checklist. Be direct, data-driven, and specific. Lead with what matters most. Use competitor names and actual numbers throughout. Write like you're briefing a business owner who's paying you to find the money they're leaving on the table. Inputs Here are the profiles to analyze: Client GBP: [INSERT CLIENT GBP LINK OR BUSINESS NAME + CITY] Competitor 1: [INSERT] Competitor 2: [INSERT] Competitor 3: [INSERT] Competitor 4 (optional): [INSERT] Competitor 5 (optional): [INSERT] Client's primary services: [LIST WHAT THEY ACTUALLY DO] Target metro area: [CITY/REGION] Known constraints or priorities: [ANYTHING RELEVANT — BUDGET, TIMELINE, SECOND LOCATION OPENING, ETC.]

Analyse the SEO of this page. Be brutally honest. What are its biggest weaknesses? What entities or topics are missing that the top ranking competitors cover? What would you improve if you had to beat this page?

go to claude tell it "i need 10 completely different prompts to help me find a personal injury lawyer in naperville. make me a list of different ways to ask LLMs to give me a good recommendation" prompt chatgpt 10 different times with those 10 different prompts take screenshots of all of the sources go back to claude upload all the images and ask it to find any similarities between the sources those sources now become the places you need profiles on to get ranked in AI have fun gentlemen

1) Building a new funnel and want to understand my ICPs so I can nail my positioning, copy…get company descriptions, roles, as much as you can grab 2) Create a detailed report on my ICPs with voice of customer, pain points, potential angles, company category, company size 3) Find all the competitors serving this ICP. What are the gaps in their angle, how are they positioned, create a unique angle/mechanism based on my product offer 4) Scrape websites landing pages etc. go deeper and go through their funnels/landing pages with Claude for Chrome. 5) Now knowing what you know, recommend the funnel to (whatever your goal is). Use subagents to review, refine. Include your reasoning and references for each.

Analyze the attached portfolio's risk factors in two layers. First, identify conventional and relatively observable factors, including: Interest rates and discount rates Economic growth and recession Consumer spending Credit availability and refinancing Inflation and labor costs Commodity and energy prices Foreign exchange rates Housing and commercial-real-estate activity Government spending and regulation Industry capital-expenditure cycles Equity-market liquidity and investor risk appetite Geography, customers, suppliers, and end markets Technological disruption Competitive intensity Second, search creatively for less obvious common exposures. Look for companies from apparently unrelated industries that depend on: The same customer group or source of customer funding The same industry’s capital-expenditure budget Shared suppliers, infrastructure, distribution channels, or technology platforms Electricity, cloud computing, telecommunications, payment rails, cybersecurity, or electronic connectivity Continuously available and inexpensive financing Government licenses, reimbursement, subsidies, contracts, or emergency-policy support Similar investor ownership, market liquidity, index inclusion, or susceptibility to forced selling The same assumptions about consumer behavior, demographics, globalization, or institutional stability Second- and third-order economic relationships A single external event that could simultaneously affect otherwise unrelated businesses Government intervention that might protect some assets or companies while excluding others Be imaginative but disciplined. A creative factor must have a coherent causal mechanism. Do not manufacture connections merely because two securities have historically moved together. For every material factor or cluster, explain: Which portfolio positions are exposed? What specifically connects them? What event or change would activate the factor? How would the factor travel through each business? Would it affect fundamentals, valuation, financing, market liquidity, or some combination? Would the damage likely be temporary or potentially permanent? How confident are you that the connection is economically real? Could a reasonable investor have identified and acted upon the factor beforehand? Why might the proposed grouping be misleading or overstated? Pay particular attention to companies classified in different industries that ultimately depend on the same economic engine. Recognize the limitations of factor analysis. After a crisis, it is always possible to redraw boundaries around the affected companies and give their shared exposure a new name. Distinguish among: Established factors that were identifiable and actionable beforehand Hidden factors that could have been identified through deeper analysis Background dependencies that are real but nearly impossible to avoid Factors whose importance could not reasonably have been understood before an unprecedented event Retrospective narratives that explain the past but offer little practical foresight Do not assume every shared characteristic constitutes a useful risk factor. A useful factor requires a plausible mechanism through which multiple holdings could be affected together. Coverage and exclusions: Do not stop the analysis because one or more securities cannot be adequately researched. Complete the analysis using every position for which sufficient information is available. Classify every portfolio position as: Fully analyzed Partially analyzed Excluded Mark a position partially analyzed or excluded when you cannot identify the security confidently, cannot access reliable information, do not adequately understand its business, lack necessary portfolio or thesis information, encounter conflicting information, or cannot establish its risk exposures without speculation. For every partially analyzed or excluded position, disclose: Company name and ticker Portfolio weight, if available Whether it was partially analyzed or excluded The precise reason for the limitation Which portions could and could not be analyzed What information would be needed to complete the analysis How the omission could distort the portfolio-level conclusions Calculate the total portfolio weight that was fully analyzed, partially analyzed, and excluded. Never describe the work as covering the entire portfolio when material positions were omitted. Do not invent a company’s business model or exposures to achieve complete coverage. Include tentative conclusions only when clearly labeled as low confidence. Continue the analysis without waiting for clarification. Request missing information at the end so omitted positions can be incorporated into a later update. Output requirements: Present the results in two layers. Begin with an intuitive executive summary written in clear, conversational language. It must be understandable without reading the supporting tables. Avoid excessive jargon and long lists of immaterial observations. The executive summary should explain: The three to five most important risk clusters Which companies belong to each cluster and what connects them Where the portfolio is more concentrated than it initially appears Which apparent concentrations are probably less serious than they look The most important hidden or surprising connection Which risks are conventional and readily identifiable Which risks are more creative, uncertain, or dependent on unusual circumstances The percentage of the portfolio included in the analysis Any material securities partially analyzed or excluded The bottom-line conclusion about how the portfolio is diversified Explain each cluster causally and intuitively. Do not merely name a factor such as “interest-rate risk.” Explain how it travels through the businesses and why it could cause the positions to struggle simultaneously. Prioritize factors according to the portfolio weight exposed, potential severity, and confidence in the connection. After the executive summary, provide: A. Portfolio coverage and exclusions B. Major identifiable risk factors C. Cross-industry risk clusters D. Hidden or unconventional shared exposures E. Imaginative but plausible stress scenarios F. Detailed position-by-factor analysis G. Blind spots and information needed For each important cluster, show: Shared factor or dependency Positions exposed Approximate portfolio weight exposed Transmission mechanism Potential severity Confidence in the connection Ex-ante identifiability Reasons the grouping could be overstated Use current primary sources such as regulatory filings, earnings materials, and company investor presentations. Cite material factual claims. Do not provide position-sizing, trading, or portfolio-reconstruction recommendations unless specifically requested. Maintain this as an ongoing analysis. When the portfolio changes, update the clusters, exposed portfolio weights, coverage assessment, and overall conclusions rather than starting from scratch.