Understanding your analytics metrics

The Analytics page shows key metrics to help you understand how customers use virtual try-on and its impact on your business.

Key performance indicators

Four KPI cards appear at the top of your dashboard:

Total Try-Ons

The total number of virtual try-ons completed during the selected time period. This is your primary engagement metric.

• Higher numbers indicate strong customer interest in the feature
• Watch for growth trends as customers discover try-on

Unique Users

The number of distinct customers who used virtual try-on. One customer trying multiple products counts as one unique user.

• Shows how many customers are actually engaging with the feature
• Compare to Total Try-Ons to understand usage patterns

Avg. Try-Ons per User

The average number of try-ons each user performs. Calculated as Total Try-Ons ÷ Unique Users.

• Higher values suggest customers are exploring multiple products
• Typical range: 1.5–3.0 try-ons per user

Revenue per Try-On

The average revenue generated per try-on, helping you understand the ROI of the feature.

• Calculated from orders where customers used try-on before purchasing
• Use this to measure try-on's contribution to sales

Trend badges

Each metric card shows a trend badge comparing to the previous equivalent period:

• Green ↑ — Metric increased compared to last period
• Red ↓ — Metric decreased compared to last period
• "No prior data" — Not enough history to compare

For example, if viewing "30d", the trend compares the last 30 days to the 30 days before that.

Charts and breakdowns

Daily Try-Ons chart

Shows try-on volume over time. Use this to:

• Identify peak usage days (often weekends)
• Spot the impact of marketing campaigns
• Track growth trends over time

Failure Breakdown

Shows why some try-ons didn't complete successfully. Common reasons include:

• Face not detected — Customer's photo didn't have a clear face
• Garment unsupported — Product image isn't compatible
• NSFW blocked — Content moderation prevented the try-on
• Timeout — Processing took too long
• Image load failed — Problem loading the customer or product image

A failure rate under 10% is typical. Higher rates may indicate image quality issues.

Conversions by Category

Breaks down try-ons by clothing category, showing:

• Number of try-ons per category
• Conversion rate (% of try-ons that led to purchase)

Use this to see which product types benefit most from virtual try-on.

Campaign Performance

If you've created email campaigns through MirrorNex, this table tracks:

• Recipients — How many customers received the campaign
• Open rate — % who opened the email
• Click rate — % who clicked a link
• Revenue — Total revenue attributed to the campaign

Using metrics to improve

Low total try-ons?

• Make the try-on button more visible on product pages
• Enable try-on on more products
• Promote the feature in marketing emails

High failure rate?

• Check if product images have clean backgrounds
• Ensure product photos show the full garment clearly
• Review the Failure Breakdown for specific issues

Low revenue per try-on?

• Enable try-on on higher-value products
• Ensure the checkout flow is smooth after try-on
• Consider follow-up emails for abandoned try-ons