Prompt Details
Model
(gemini-3.7-flash)
Token size
320
Example input
[BUSINESS_NAME]: Sahabat UMKM Consulting
[AUDIT_FINDINGS]: The service description is broad and has no proof assets.
[AVAILABLE_RESOURCES]: One month and a limited research budget
[TIMEFRAME]: Before publishing the new website
Example output
TL;DR: Sahabat UMKM Consulting struggles with broad service definitions and missing proof assets, causing LLMs and search engines to treat the site as low-credibility fluff. Using your one-month pre-launch window and research budget, you can narrow your service taxonomy, conduct focused research to produce 2–3 data-backed mini case studies, and deploy explicit schema before the new site goes live.1. Root-Cause Diagnosisfindingcategorylikely root causeconfidencebusiness impactService description is overly broad and genericpositioningLack of specialized positioning; trying to offer "everything" to all UMKM businessesHighHigh (Causes low AI search relevance and poor lead conversion)Complete absence of proof assets (case studies, metrics, testimonials)evidence and credibilityNo structured post-engagement data collection process or client consent workflowsHighHigh (AI models penalize low-authority sites without verifiable E-E-A-T signals)Lack of structured data detailing specific service offeringstechnical readinessWeb copy relies on unstructured narrative text without schema markupHighMedium (Search crawlers cannot parse specific consulting capabilities)Missing verification data for claimsinformation completenessService outcome claims lack underlying research or benchmark dataMediumMedium (Dilutes entity confidence scores across AI indexers)2. Prioritized Action TablePriority Score = $\frac{\text{Impact} \times \text{Confidence}}{\text{Effort}}$ (Rated 1–5)actionfinding addressedimpactconfidenceeffortpriorityresource neededdependency1. Define Core Niche & Service Scope MatrixService description is broad55125.0Internal TeamNone2. Conduct Micro-Research for Client MetricsNo proof assets54210.0Research BudgetAction 13. Draft 3 Data-Backed Proof Case StudiesNo proof assets / Missing verification45120.0Research BudgetAction 24. Implement ProfessionalService SchemaLack of structured data44116.0Web BuilderAction 15. Add Standardized Outcome Disclaimers & FAQService description is broad34112.0Internal TeamAction 1Actions Explicitly Not Prioritized (Out of Scope for 1-Month Launch Window):Large-Scale Video Testimonial Production: Too time-intensive and consumes the budget better spent on metric gathering.Broad Industry Report Publishing: Wastes research budget on macro trends instead of immediate proof assets.Extensive PR / Media Outreach: Irrelevant before the site has clear positioning and verified proof points.3. Implementation RoadmapToday: Service Scope Definition
├── Narrow service catalog to 2-3 specific UMKM consulting packages
└── Draft negative positioning statements ("What Sahabat UMKM Consulting does NOT do")
This Week: Research & Outreach Sprint
├── Allocate research budget to interview 3-5 past/current clients
└── Gather verifiable metrics (e.g., % revenue growth, hours saved, cost reduction)
Within 30 Days: Content Assembly & Technical Pre-Launch
├── Write 3 structured mini case studies using Problem-Solution-Metric framework
├── Inject JSON-LD ProfessionalService schema markup into draft site pages
└── Conduct site review to ensure no unverified marketing claims remain
Within 90 Days: Post-Launch Verification (Adapted to Pre-Launch Window)
├── Monitor AI search engines (ChatGPT, Perplexity, Gemini) for accurate service indexing
└── Establish ongoing quarterly data collection for continuous proof updates
4. Success IndicatorsVerifiable Proof Density: 100% of core service pages feature at least one quantitative metric or verified case study.Service Specificity: Zero generic catch-all phrases (e.g., "all-in-one business solutions") present in core site copy.Schema Compliance: Rich Results Test validates error-free ProfessionalService and Service JSON-LD markup prior to domain launch.AI Entity Accuracy: Testing draft copy via AI models yields explicit, specific summaries of target services rather than generic consulting labels.5. Risks and MitigationsRisk: Clients refuse to share exact financial data for public case studies.Mitigation: Use anonymized growth percentages (e.g., "35% reduction in operational cost") accompanied by verified industry benchmark research.Risk: Research budget is depleted without yielding usable metrics.Mitigation: Use simple, structured 15-minute phone interviews incentivized with complimentary follow-up check-ins.6. First Three ActionsDraft the Niche Service Catalog: Eliminate broad labels and specify exactly 2–3 core consulting offers (e.g., "UMKM Financial Restructuring" and "Digital Operations Setup").Commission Client Metric Interviews: Use your research budget to conduct 3 brief client interviews aimed strictly at harvesting outcome metrics.Draft JSON-LD Schema: Prepare machine-readable ProfessionalService code containing explicit hasOfferCatalog details to embed into the new site before going live.How would you like to structure the 2–3 core consulting packages for the new site copy?
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GEMINI-3.7-FLASH
This prompt helps businesses understand how they may be positioned against competitors in AI-generated recommendations and comparison answers.
It analyzes:
The questions potential customers may ask.
The contexts in which a business may be mentioned.
The strengths associated with each business.
Information that makes competitors easier to understand.
Positioning opportunities for the primary business.
Content that can improve competitive clarity.
...more
Added 1 week ago
