SayPro Gather and classify 10,000+ unique consumer insights

Plan to Gather and Classify 10,000+ Unique Consumer Insights

1. Data Collection

• Sources:
  • Surveys and feedback forms (online/offline)
  • Social media posts, comments, and mentions
  • Customer support transcripts (calls, chats, emails)
  • Product reviews and ratings
  • Focus groups and interviews transcripts
  • SayPro platform activity logs (course reviews, engagement data)
• Automation Tips:
  • Use APIs to pull data automatically from social media and CRM systems.
  • Deploy chatbots or feedback widgets to capture new insights continuously.

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2. Data Processing & Cleaning

• Remove duplicates and spam.
• Normalize text (remove slang, correct typos).
• Filter out irrelevant content.

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3. Insight Extraction

• Use GPT or similar LLMs to extract key insights from raw text.
  • Example prompt:
    “Extract unique consumer insights related to [topic] from the following text.”
• Break down large datasets into manageable batches for processing.

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4. Classification & Categorization

• Define categories/themes:
  • Product Features
  • Customer Service
  • Pricing & Value
  • User Experience
  • Accessibility & Inclusivity
  • Platform Performance
  • Marketing & Communication
  • Competitor Comparisons
  • Other
• Use NLP models or GPT to assign each insight to a category.
• Perform sentiment analysis to label insights as Positive, Neutral, or Negative.

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5. Storage & Management

• Store insights in a database with metadata: category, sentiment, source, date.
• Use tagging systems for easier search and retrieval.

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6. Validation & Deduplication

• Implement automated checks for duplicates.
• Conduct periodic manual reviews for quality assurance.

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7. Reporting & Utilization

• Generate dashboards showing volume by category, sentiment trends, and emerging issues.
• Share actionable insights regularly with relevant departments.

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Tools & Technologies to Consider

• Data Collection: APIs, web scraping tools, survey platforms (Qualtrics, SurveyMonkey)
• Processing & Extraction: Python (spaCy, NLTK), GPT via OpenAI API
• Classification & Sentiment: Custom ML models, GPT prompts, pre-built sentiment analysis APIs
• Storage: SQL/NoSQL databases, Airtable, or cloud data warehouses
• Visualization: Power BI, Tableau, Google Data Studio, or custom dashboards