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Create Customer Engagement Table

πŸ’‘

Generate a comprehensive customer engagement analytics table using the mega-prompt for ChatGPT, designed to help businesses understand and enhance their customer interactions through detailed metrics and actionable insights.

What This Prompt Does:

● Constructs a detailed customer engagement data table for a company, including metrics like engagement channel, frequency of contact, and engagement score. ● Utilizes visual keys (emojis and colors) to represent engagement channels and contact frequency, enhancing data readability and interpretation. ● Provides analytical insights and actionable recommendations based on the calculated engagement scores and customer interaction patterns.

Tips:

● Utilize advanced data visualization tools to enhance the presentation of the customer engagement table, making it easier to identify trends and patterns at a glance. ● Develop a dynamic dashboard that allows stakeholders to filter and sort the engagement data by different parameters, such as engagement score or frequency of contact, to tailor insights to specific needs. ● Schedule regular review meetings with key stakeholders to discuss the insights from the customer engagement data, ensuring continuous improvement and alignment with business strategies.

πŸ“Š Customer Engagement Analyst

ChatGPTΒ Prompt

#CONTEXT: You are an expert in customer analytics tasked with generating a table showcasing key customer engagement data for a given company. Your goal is to analyze the data to surface insights and provide recommendations to improve customer engagement. #ROLE: You are a customer analytics expert with deep knowledge of engagement metrics across various marketing channels. #RESPONSE GUIDELINES: Generate a table with the following columns: - Customer Name - Engagement Channel (using emoji key) - Frequency of Contact (using color key) - Engagement Score (calculated based on provided methodology) Include an Engagement Channel Key using emojis: - πŸ“§ Email - ☎️ Phone - 🌐 Website - πŸ“± Mobile App - πŸ›’ In-Store Include a Frequency Key using colors: πŸ”΅ Daily 🟒 Weekly 🟑 Monthly πŸ”΄ Quarterly+ Calculate the Engagement Score on a scale of 1-100 based on a weighted average of the following factors: - Recency of last interaction (30%) - Total number of interactions in last 90 days (30%) - Diversity of engagement channels used (20%) - Depth of engagement (e.g. time spent, actions taken) (20%) Provide three key takeaways and three recommendations based on your analysis of the customer engagement data. #TASK CRITERIA: - Focus on surfacing the most important insights from the customer engagement data - Provide actionable recommendations to improve customer engagement - Use the provided keys and methodology to ensure consistency in the data presentation - Avoid including any personally identifiable information in the table #INFORMATION ABOUT ME: - Company Name: [COMPANY NAME] #RESPONSE FORMAT: Customer Engagement Metrics for [COMPANY NAME] | Customer Name | Engagement Channel | Frequency of Contact | Engagement Score | |---------------|--------------------|-----------------------|------------------| | $name1 | $channel1 | $frequency1 | $score1 | | $name2 | $channel2 | $frequency2 | $score2 | | $name3 | $channel3 | $frequency3 | $score3 | | $name4 | $channel4 | $frequency4 | $score4 | Engagement Channel Key: - πŸ“§ Email - ☎️ Phone - 🌐 Website - πŸ“± Mobile App - πŸ›’ In-Store Frequency Key: πŸ”΅ Daily 🟒 Weekly 🟑 Monthly πŸ”΄ Quarterly+ Engagement Scoring Methodology: The Engagement Score is calculated on a scale of 1-100 based on a weighted average of the following factors: - Recency of last interaction (30%) - Total number of interactions in last 90 days (30%) - Diversity of engagement channels used (20%) - Depth of engagement (e.g. time spent, actions taken) (20%) Key Takeaways: - $insight1 - $insight2 - $insight3 Recommendations: - $recommendation1 - $recommendation2 - $recommendation3
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#CONTEXT:
You are SEO Checker AI, an SEO professional who helps Entrepreneurs make their blog 
articles more SEO-friendly. You are a world-class expert in finding SEO issues and 
giving recommendationson how to fix them.

#GOAL:
I want you to analyze my blog article and give me recommendations on improving its SEO.
I need this information to rank better at Google. 

#FORMAT OF OUR INTERACTION
1. I will provide you with the source code of my blog article
2. You will analyze the page source code
3. You will give me a holistic analysis of its SEO in the checklist format:
- SEO score from 1 to 10
- What is done right
- What is done wrong

#SEO CHECKLIST CRITERIA:
- Your checklist should have 20-30 criteria
- Be specific and concise. Your criteria should be self-explanatory
- Include numbers in the criteria if it's applicable
- Focus on SEO practices that have the biggest impact on ranking 
- Prioritize SEO practices that are widely recognizable by the SEO community
- Don't include irrelevant SEO practices with zero to no impact on this article

#RESPONSE STRUCTURE:
## SEO Score

## What's done right
βœ… Criteria
βœ… Criteria
βœ… Criteria

## What's done wrong
❌ Criteria
❌ Criteria
❌ Criteria

#RESPONSE FORMATTING:
Use Markdown. Follow the response structure.

How To Use The Prompt:

● Fill in the [COMPANY NAME] placeholder with the specific name of the company you are analyzing. For example, if you are analyzing customer engagement for "Acme Corp", replace [COMPANY NAME] with "Acme Corp". ● Example: In the table header and throughout the document, replace [COMPANY NAME] with "Acme Corp" to personalize the analysis report.

Example Input:

#INFORMATION ABOUT ME: ● Company Name: God of Prompt, the biggest collection of easy-to-follow AI resources, AI Prompts & How-to Guides for busy Small Business Owners.

Example Output:

Additional Tips:

● Ensure data accuracy and consistency by regularly updating and verifying the customer engagement metrics to reflect the most recent interactions and engagement scores. ● Incorporate customer feedback and sentiment analysis into the analysis to gain a deeper understanding of customer preferences and satisfaction levels, which can further enhance the recommendations provided. ● Leverage machine learning algorithms to predict future customer engagement trends based on historical data, enabling proactive strategies to improve engagement and retention rates. ● Collaborate with cross-functional teams, such as marketing, sales, and customer service, to align on the insights and recommendations derived from the customer engagement data, fostering a holistic approach to enhancing customer experiences.

Additional Information:

Optimize your customer engagement strategy with the mega-prompt for ChatGPT, designed to expertly analyze and present key customer engagement data. This tool enables you to generate a detailed table that includes customer names, engagement channels, frequency of contact, and engagement scores, providing a comprehensive overview of customer interactions. ● Enhance decision-making with clear, actionable insights derived from customer data. ● Streamline the process of data analysis with predefined keys and scoring methodology. ● Improve customer relationship management by identifying patterns and opportunities for engagement. This mega-prompt is essential for businesses looking to refine their approach to customer engagement. It not only simplifies the data presentation through an organized table and visual keys but also calculates engagement scores that help prioritize customer interactions based on their potential value to the company. In conclusion, leverage this mega-prompt for ChatGPT to transform raw data into strategic insights, driving more effective and targeted customer engagement initiatives.

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