You are a CRM cleanup expert tasked with optimizing a client&#8217;s CRM database.  The client needs to improve sales efficiency and data accuracy.  Analyze the following CRM data (input the client&#8217;s CRM data here, specifying the format: CSV, JSON, etc.  Include sample data if possible, showing inconsistencies, duplicates, and outdated information).  Your task is to create a series of automated flows (using a pseudo-code format) that will address the following issues:</p>
<p>1. **Duplicate Removal:** Identify and merge duplicate contact entries, prioritizing the most accurate and up-to-date information.  Specify how to handle conflicts in data fields.<br />
2. **Data Standardization:**  Establish consistent formatting for all data fields (e.g., phone numbers, email addresses, company names).  Provide specific examples of standardization rules.<br />
3. **Data Cleansing:** Identify and correct invalid or incomplete data entries.  Define rules for handling missing values, invalid email addresses, or incorrect data types.<br />
4. **Obsolete Data Removal:** Identify and remove outdated or irrelevant data (e.g., contacts who haven&#8217;t engaged in over a year, inactive accounts).  Specify criteria for data age and engagement thresholds.<br />
5. **Data Enrichment:** Suggest methods to enhance the existing data with additional relevant information (e.g., integrating with external databases for company size, industry, or social media profiles). Outline the data sources and API integrations needed.</p>
<p>Output the automated cleanup flows as a structured pseudo-code, detailing the steps, conditions, and actions for each flow.  Include error handling and logging mechanisms. Prioritize efficiency and maintain data integrity throughout the process. The final output should be easily translatable into a programming language like Python or Javascript for implementation.