What analytics does Simple Chat provide?

Simple Chat’s Analytics page shows how support work is being handled over time. It is an operational view for merchants who want to measure automation impact, staff involvement, and billing-related usage—not just raw chat volume.

Open Analytics from the Simple Chat navigation in Shopify Admin when you are reviewing weekly performance or preparing for a capacity planning conversation.

Metrics you can review

The Analytics page focuses on outcomes and quality signals, including:

• Conversation volume — How many conversations are flowing through support over the selected period.
• AI-resolved vs staff-resolved outcomes — Whether threads are finishing with automation or human involvement.
• Staff validation and rejection of AI resolutions — How often your team agrees the AI closed correctly versus sends a resolution back for correction.
• Billing-related summaries — How usage-based billing maps to resolved conversation volume so finance and support leads are looking at the same numbers.

Use these together rather than in isolation. Rising AI resolution only matters if validation rates stay healthy; spikes in staff resolution may be intentional during a launch week.

Date ranges and granularity

Analytics supports common rolling windows such as 7, 14, 30, and 90 days, so you can zoom in on a launch or step back for a quarterly review.

Depending on the view, data can be shown with daily or weekly granularity, which helps you spot day-of-week patterns (weekend surges, BFCM spikes) without mistaking noise for a trend.

When comparing periods, keep seasonality in mind—compare 30-day windows to prior 30-day windows rather than a quiet week to your busiest sale.

Questions Analytics is meant to answer

Merchants typically use Analytics to decide:

• Is AI resolution increasing while customer issues stay under control?
• Where does staff still need to step in—and is that concentrated in certain weeks?
• Does resolved conversation volume align with what we expect on our usage-based plan?

Pair Analytics with the Reports page when you need thematic detail (products, topics, sentiment). Analytics tells you how the support operation is performing; Reports helps explain what customers are talking about.

Example review cadence for operators

Many merchants adopt a lightweight weekly routine:

1. Open Analytics with a 30-day range and note total conversation volume plus the split between AI-resolved and staff-resolved outcomes.
2. Compare validation vs rejection of AI resolutions—rising rejections often mean policy gaps or product issues worth fixing in content, not just more staff.
3. Check billing-related summaries against your billing expectations before month-end invoices surprise finance.
4. Switch to a 7-day window after a product drop or policy change to see if the trend moved immediately.

Share a one-page summary with leadership: volume trend, automation share, and one sentence on where humans still matter. That keeps Analytics actionable instead of a chart you only open when something breaks.