Brand and Market Analytics AI Prompts

Analyze brand sentiment from customer reviews, social mentions, and survey data. Data sources: {{data_sources}} (reviews, social listening, NPS survey, support tickets) Time period: {{period}} Competitors to compare: {{competitors}} 1. Sentiment scoring: For each text data source: - Classify each item as: Positive, Neutral, Negative - Sentiment score: (Positive - Negative) / Total - Track sentiment score over time - Volume by sentiment category per period 2. Theme extraction: - Use topic modeling or keyword clustering to identify the main themes in reviews/mentions - For each theme: count of mentions, sentiment split, trend over time - Positive themes: what do customers love most? (Product quality, service, value, ease of use) - Negative themes: what are the biggest complaints? (Price, reliability, support, missing features) 3. NPS driver analysis: - Promoters (9-10): what do they consistently praise? - Passives (7-8): what would convert them to promoters? - Detractors (0-6): what are the primary complaint themes? - For each NPS segment: top 3 verbatim themes 4. Competitive sentiment comparison: - Overall sentiment score vs competitors - Which themes does our brand win on vs competitors? - Which themes do competitors win on? (Areas to improve) 5. Sentiment anomalies: - Any spikes in negative sentiment? What triggered them? (Product issue, PR event, policy change) - Any unexpected positive spikes? What can we replicate? 6. Marketing implications: - Which proven positive themes should be amplified in marketing messages? - Which negative themes represent reputation risks that marketing must address? Return: sentiment score trends, theme analysis, NPS driver breakdown, competitive comparison, and marketing implications.

Build a competitive marketing intelligence framework for {{company}}. Competitors: {{competitor_list}} Analysis dimensions: {{dimensions}} 1. Digital presence benchmarking: For each competitor: - Website traffic estimate (SimilarWeb, SEMrush) - Organic keyword ranking count and estimated traffic - Paid search spend estimate (SEMrush, SpyFu) - Social media followers and engagement rate by platform - App store ratings and review count (if applicable) 2. SEO competitive analysis: - Keyword gap: keywords competitors rank for that we do not - Content gap: topics competitors have content on that we do not - Backlink comparison: domain authority and linking root domains - Top content by traffic for each competitor 3. Paid advertising analysis: - Estimated monthly paid search spend per competitor - Ad copy analysis: what messages and value propositions are they using? - Landing page analysis: what does their conversion experience look like? - Facebook Ad Library: active social ad creative and messaging 4. Messaging and positioning: - For each competitor: primary value proposition (from homepage) - Target audience stated or implied - Key differentiators claimed - Pricing tier and model (if visible) - Create a positioning map: plot competitors on 2 axes (e.g. price vs feature depth) 5. Share of voice: - Estimated organic search share of voice for target keyword set - Social mention volume comparison - PR and news coverage volume 6. Competitive threats and opportunities: - Where are competitors investing heavily? (Threat) - Where are competitors weak? (Opportunity) - What positioning gaps exist that no competitor is occupying? Return: competitor benchmarking table, SEO gap analysis, paid ad insights, positioning map, share of voice, and threat/opportunity matrix.

Estimate the Total Addressable Market (TAM), Serviceable Addressable Market (SAM), and Serviceable Obtainable Market (SOM) for this business. Business: {{business_description}} Product/service: {{product}} Geography: {{geography}} 1. TAM (Total Addressable Market): The total market demand if the product captured 100% of the market. Top-down approach: - Start with a published industry market size (from Gartner, IDC, IBISWorld, etc.) - Narrow to the specific segment relevant to this product - Adjust for the geographic scope Bottom-up approach: - Count the number of potential customers (from public data, census, industry directories) - Estimate average annual spend per customer - TAM = customer count x average spend - Use both approaches and triangulate 2. SAM (Serviceable Addressable Market): The portion of TAM that can realistically be served given product scope, geography, and channel. - Exclude segments the product is not designed for - Exclude geographies where the company does not or cannot operate - Exclude customer sizes that do not match the go-to-market motion 3. SOM (Serviceable Obtainable Market): The realistic market share the business can capture in 3-5 years. - Benchmark against comparable companies at similar stages - Consider: competitive intensity, sales capacity, brand awareness, capital available - Typical SOM = 1-10% of SAM in year 3-5 for venture-stage companies 4. Market growth rate: - Historical CAGR of the market - Forward-looking drivers: what is accelerating or decelerating market growth? - TAM in 5 years at current growth rate 5. Sanity check: - Revenue target / SOM: what market share does the business plan imply? - Is that market share realistic given competitors and market dynamics? Return: TAM, SAM, and SOM estimates with both top-down and bottom-up methodology, market growth rate, and sanity check on business plan assumptions.

Analyze this marketing survey and extract actionable insights. Survey data: {{survey_data}} Survey type: {{survey_type}} (NPS, CSAT, brand awareness, customer effort, market research) Respondents: {{n_respondents}} 1. Response quality check: - Response rate and completion rate - Speeders: respondents who completed the survey in < 30% of median time (unreliable data) - Straightliners: respondents who gave the same answer to every scale question - Recommend excluding speeders and straightliners from analysis 2. Quantitative analysis: - For each closed-ended question: frequency distribution (count and % per response option) - For scale questions (1-10 NPS, 1-5 satisfaction): mean, median, standard deviation - Cross-tabulation: how do responses differ by key demographic or segment? 3. NPS analysis (if applicable): - Promoters (9-10), Passives (7-8), Detractors (0-6): count and % - NPS = % Promoters - % Detractors - NPS by segment: which customer group has the highest / lowest NPS? - NPS trend vs prior survey wave 4. Open-text analysis: - Theme extraction: top 10 themes from open-ended responses - Sentiment per theme: positive, neutral, negative - Volume and sentiment for: Promoters vs Detractors vs Passives - Most actionable verbatims: select 5 representative quotes per theme 5. Correlation with behavior: - Match survey respondents to CRM/behavioral data - Do high-NPS customers actually have higher retention rates? - Do customers who cite price as a concern have higher churn rates? 6. Marketing implications: - Promoter themes to amplify in marketing messaging - Detractor themes that are reputation risks to address - Awareness and perception gaps revealed by the survey Return: response quality check, quantitative summary, NPS calculation, theme analysis, behavioral correlation, and marketing implications.