SanatiLeads/lib/types.ts

// Enhanced Types for Deep Analysis

export type PlatformId = string

export type SearchStrategy =
  | 'direct-keywords'
  | 'problem-pain'
  | 'competitor-alternative'
  | 'how-to'
  | 'emotional-frustrated'
  | 'comparison'
  | 'recommendation'

export interface PlatformConfig {
  id: PlatformId
  name: string
  icon: string
  enabled: boolean
  searchTemplate: string
  rateLimit: number
  site?: string
  custom?: boolean
}

export interface SearchConfig {
  platforms: PlatformConfig[]
  strategies: SearchStrategy[]
  maxResults: number
  timeFilter?: 'past-day' | 'past-week' | 'past-month' | 'past-year' | 'all'
}

export interface GeneratedQuery {
  query: string
  platform: PlatformId
  strategy: SearchStrategy
  priority: number
  expectedIntent: string
}

export interface Opportunity {
  id: string
  title: string
  url: string
  snippet: string
  platform: string
  source: string

  relevanceScore: number
  emotionalIntensity: 'low' | 'medium' | 'high'
  intent: 'frustrated' | 'looking' | 'comparing' | 'learning' | 'recommending'

  matchedKeywords: string[]
  matchedProblems: string[]
  matchedPersona?: string

  engagement?: {
    upvotes?: number
    comments?: number
    views?: number
  }
  postedAt?: string

  status: 'new' | 'viewed' | 'contacted' | 'responded' | 'converted' | 'ignored'
  notes?: string
  tags?: string[]

  suggestedApproach: string
  replyTemplate?: string
  softPitch: boolean

  scoringBreakdown?: {
    keywordMatches: number
    problemMatches: number
    emotionalIntensity: number
    competitorMention: number
    recency: number
    engagement: number
  }
}

export interface Feature {
  name: string
  description: string
  benefits: string[]
  useCases: string[]
}

export interface Problem {
  problem: string
  severity: 'high' | 'medium' | 'low'
  currentWorkarounds: string[]
  emotionalImpact: string
  searchTerms: string[]
}

export interface Persona {
  name: string
  role: string
  companySize: string
  industry: string
  painPoints: string[]
  goals: string[]
  techSavvy: 'low' | 'medium' | 'high'
  objections: string[]
  searchBehavior: string[]
}

export interface Keyword {
  term: string
  type: 'product' | 'problem' | 'solution' | 'competitor' | 'feature' | 'longtail' | 'differentiator'
  searchVolume: 'high' | 'medium' | 'low'
  intent: 'informational' | 'navigational' | 'transactional'
  funnel: 'awareness' | 'consideration' | 'decision'
  emotionalIntensity: 'frustrated' | 'curious' | 'ready'
}

export interface UseCase {
  scenario: string
  trigger: string
  emotionalState: string
  currentWorkflow: string[]
  desiredOutcome: string
  alternativeProducts: string[]
  whyThisProduct: string
  churnRisk: string[]
}

export interface Competitor {
  name: string
  differentiator: string
  theirStrength: string
  switchTrigger: string
  theirWeakness: string
}

export interface DorkQuery {
  query: string
  platform: 'reddit' | 'hackernews' | 'indiehackers' | 'twitter' | 'quora' | 'stackoverflow'
  intent: 'looking-for' | 'frustrated' | 'alternative' | 'comparison' | 'problem-solving' | 'tutorial'
  priority: 'high' | 'medium' | 'low'
}

export interface EnhancedProductAnalysis {
  productName: string
  tagline: string
  description: string
  category: string
  positioning: string

  features: Feature[]
  problemsSolved: Problem[]
  personas: Persona[]
  keywords: Keyword[]
  useCases: UseCase[]
  competitors: Competitor[]
  dorkQueries: DorkQuery[]

  scrapedAt: string
  analysisVersion: string
}

// Legacy types for backwards compatibility
export interface ProductAnalysis {
  productName: string
  tagline: string
  description: string
  features: string[]
  problemsSolved: string[]
  targetAudience: string[]
  valuePropositions: string[]
  keywords: string[]
  scrapedAt: string
}

export interface ScrapedContent {
  url: string
  title: string
  metaDescription: string
  headings: string[]
  paragraphs: string[]
  featureList: string[]
  links: string[]
  rawText: string
}

export interface SearchResults {
  productAnalysis: EnhancedProductAnalysis
  totalFound: number
  opportunities: Opportunity[]
  searchStats: {
    queriesUsed: number
    platformsSearched: string[]
    averageRelevance: number
  }
}