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Calculated by dividing the number of emails opened by the total number of emails sent (excluding those that bounced), multiplied by 100. It's important for fashion retailers to measure engagement with their email marketing campaigns, to optimize their content and send timings.

Not a single metric, but a category that tracks where online visitors are coming from (search engines, social media, direct visits, etc.). It is important for understanding which marketing channels are most effective at driving traffic.

A collective term for various metrics such as likes, shares, comments, and follows, representing how users interact with a brand's content. High engagement is important for fashion retailers to increase brand presence and loyalty.

Calculated by dividing the number of single-page sessions by the total number of sessions and multiplying by 100. A high bounce rate can indicate that the site's landing pages are not relevant or engaging enough for visitors, which is crucial for online fashion retailers to address.

Calculated by dividing the number of completed purchases by the number of shopping carts created, subtracting this from 1 and multiplying by 100 to get a percentage. It is important because it helps identify issues in the checkout process that could be optimized.

Calculated by dividing the revenue generated from ad campaigns by the cost of those campaigns. It is important because it measures the effectiveness of advertising spend, ensuring that fashion marketers are getting a good return on their marketing investments.

CLV is calculated by multiplying the average purchase value by the average purchase frequency rate, and then multiplying that by the average customer lifespan. It's important for understanding how much revenue a customer can potentially generate over their relationship with the brand.

Calculated by dividing the number of purchases by the number of website visitors and multiplying by 100 to get a percentage. It is important because it measures the effectiveness of the site in persuading visitors to make a purchase.

Calculated by dividing total revenue by the number of orders. It helps retailers understand the average amount spent per transaction, which can lead to better pricing strategies and product promotion.