Customer Behavior

Customer Behavior is the dashboard-level view of how shoppers interact with your store: what % return, what device they use, what channel brought them. Open from the Analytics dashboard. For deeper drill-down (per-customer / per-cohort), see Customer Behavior Report + Customer Cohort Analysis.

You'll work at /admin/store/{storeId}/analytics.

Key signals to read

Before you begin

• You are signed in to your Tanqory store admin.
• You have View analytics permission.
• The store has enough traffic for meaningful behavior signals (few hundred sessions minimum).

Steps

1. Open Analytics

2. Find the Customer Behavior KPI panel

The Analytics dashboard surfaces a Customer Behavior panel: typically showing returning-customer rate + device split + channel split.

3. Read the headline numbers

Note: returning rate, device mix (mobile %), top channel.

4. Compare against your benchmarks

• Returning rate: 20-40% is healthy DTC mature; lower = retention work needed.
• Mobile %: 60-80% typical; mismatch with your design effort = problem.
• Top channel: should match your marketing investment.

5. Drill into per-segment detail

For deeper analysis, drill into:

• Customer Behavior Report: aggregate-level deep dive.
• Customer Cohort Analysis: cohort retention.
• Customer Insights: segment composition.

6. Action on signals

• Low returning rate → retention work (post-purchase email, loyalty program).
• Mobile-heavy but desktop-optimized site → mobile UX investment.
• Single dominant channel → diversification (channel risk).

Verify the result

• All signals render on the dashboard.
• Drill-downs open the underlying reports.
• Numbers triangulate (e.g., returning + new = total customers).

Best practices

• Track returning rate as a north-star retention metric.
• Watch device split monthly. Mobile share grows; design priorities shift.
• Don't let one channel dominate. Channel concentration = business risk.
• Compare against same-period prior year, not just yesterday.
• Cross-reference with cohort analysis for unit-economics view.

Common mistakes

• Reading absolutes without context. A 30% returning rate is good for some categories, bad for others.
• Reacting to a daily blip. Use 7-day or 30-day moving averages.
• Ignoring channel concentration risk.
• Skipping cohort analysis when behavior shifts: cohort tells you when + why.

If something goes wrong

• Signals missing on dashboard: verify your store has enough traffic; new stores show zero.
• Numbers feel wrong: verify tracking pixel is firing (Settings > Tracking).
• Drill-down doesn't open: verify your role has permission.
• Permission denied: your role lacks View analytics.

Next steps

• Customer Behavior Report
• Customer Cohort Analysis
• Customer Insights

Related articles

• Returning Customer Rate
• Sessions Over Time
• Analytics Dashboard