Engagement index
The purpose of MessageGears’ Engagement Index model is to predict your customers' likelihood to engage with your brand.
How does it work?​
This model evaluates your customers' engagement across available channels and generates a score representing their predicted level of engagement with your brand. The model’s output is a normalized SCORE that ranks customers with a range from 100 (most likely) to 1 (least likely) to engage. A customer with a score of 99 is considered more likely to engage than a customer with a score of 75, who in turn more likely to engage than a customer with a score of 25. You can then use the engagement score in segmentation or personalization for a wide variety of marketing use cases.
Requirements​
- Email engagement data (clicks, opens, sends)
- Web/Pixel engagement data
- Data Input Schemas for Transaction/conversion data
Schema​
| MG Field Name | Type | Range | Description |
|---|---|---|---|
| RecipientId | VARCHAR | The unique customer identifier, the key to join back to customer tables. | |
| MLEngagedScore | INT | 1-100 | 1-100 normalized output of scoring. |
| MLEngagedLow | BOOL | 0 or 1 | Predefined segments. Our recommended audience definitions today break out high/medium/low, where the top quintile = high; mid three quintiles = medium; bottom quintile = low. However, we can customize this during implementation. |
| MLEngagedMedium | BOOL | 0 or 1 | |
| MLEngagedHigh | BOOL | 0 or 1 |