Email Subject Line Optimizer

**Context**: 
Email subject lines are a crucial factor in determining the success of email marketing campaigns. A well-crafted subject line can significantly increase open rates, while a poorly written one can lead to low engagement and missed opportunities. With the ever-increasing volume of emails, it's becoming increasingly challenging to grab the attention of potential customers. An effective email subject line optimizer tool can help businesses and marketers craft subject lines that resonate with their target audience, improve email open rates, and ultimately drive conversions.

**Detailed Instructions**: 
Design an advanced email subject line optimizer that can analyze a given subject line and provide suggestions for improvement. The optimizer should consider various factors such as keyword relevance, character length, emotional appeal, personalization, and spam filter evasion. The tool should be able to handle a wide range of industries and email types, including promotional, transactional, and relational emails. The optimizer should also be able to provide insights on the subject line's potential performance, including predicted open rates and click-through rates.

The optimizer should be able to:

1. Analyze the input subject line for keyword density, sentiment, and tone.
2. Provide suggestions for improvement, including alternative subject lines, word substitutions, and character adjustments.
3. Offer personalization options, such as inserting the recipient's name or referencing their previous interactions with the brand.
4. Evaluate the subject line's potential to evade spam filters and suggest modifications to minimize the risk of being flagged as spam.
5. Predict the subject line's performance, including open rates and click-through rates, based on historical data and industry benchmarks.

**Output Format**: 
The output should be a JSON object containing the following fields:

* `original_subject_line`: The input subject line.
* `optimized_subject_line`: A suggested improved subject line.
* `analysis`: An object containing the results of the analysis, including keyword density, sentiment, tone, and spam filter risk.
* `personalization_options`: A list of personalization options, including recipient name insertion and previous interaction references.
* `performance_prediction`: An object containing the predicted open rates and click-through rates.
* `suggestions`: A list of alternative subject lines and word substitutions.

**Examples**: 

Input: "Summer Sale: 20% Off All Products"
Output: 
```json
{
  "original_subject_line": "Summer Sale: 20% Off All Products",
  "optimized_subject_line": "Exclusive Summer Sale: 20% Off Your Favorite Products",
  "analysis": {
    "keyword_density": 0.5,
    "sentiment": "positive",
    "tone": "promotional",
    "spam_filter_risk": 0.2
  },
  "personalization_options": [
    "Insert recipient name",
    "Reference previous purchase"
  ],
  "performance_prediction": {
    "open_rate": 0.25,
    "click_through_rate": 0.05
  },
  "suggestions": [
    "Summer Sale: Limited Time Offer",
    "20% Off Summer Favorites"
  ]
}
```