Scan Breakdowns
This page explains how to analyze scan activity with device, location, and time-based views. Use these breakdowns to understand context, diagnose performance issues, and inform placement and scheduling.
Views
• Overview — Total Scans trend over the selected date range. Use to spot peaks, dips, and overall momentum.
• Devices — Breaks down scans by device/OS (for example, iOS vs. Android). Use to validate testing coverage and identify platform-specific issues.
• Locations — Shows where scans occur (for example, country, region, city). Use for regional targeting and to compare results against planned placements.
• Time Patterns — Aggregates scans by hour of day and day of week. Use to plan staffing, flighting, and creative rotation.
Filters and scope
• Date range — Focus analysis on a specific window (launch week, campaign flight, or monthly view).
• Campaign filter — Narrow results to a single campaign for focused reviews.
• Code-level review — For code-specific analysis, open the code from its campaign and view its breakdowns in context.
How to interpret breakdowns
• Devices — If one platform underperforms, re-test scannability and destination behavior on that platform. Check page performance, redirects, and consent flows on mobile.
• Locations — Treat geography as directional. Use trends to compare regions or placements; avoid drawing conclusions from very small counts.
• Time Patterns — Align peaks with media schedules, store hours, or event timelines. Use off-peak insights to adjust placements or CTAs.
• Anomalies — Sudden spikes can indicate successful placements or bot-like activity. Compare against GA4 traffic for the same period and confirm UTMs.
Using with GA4
• Alignment — Keep a consistent UTM pattern so GA4 sessions can be compared with BaseQR scans by campaign and channel.
• Expect differences — BaseQR counts scan events; GA4 counts sessions after page load and may filter traffic. Compare trends, not one-to-one totals.
Exports
• Formats — CSV, Excel, and PDF.
• Categories — Total Scans, Device Breakdown, Location Breakdown, and Time Patterns.
• Use cases — Share weekly summaries, annotate spikes with campaign notes, and archive monthly snapshots for year-over-year comparisons.
Best practices
• Define questions first — Decide what you want to learn (for example, “Which placements drove weekend peaks?”) and pick the relevant view.
• Segment consistently — Mirror campaign names in utm_campaign and standardize utm_source/utm_medium so GA4 dashboards align with BaseQR breakdowns.
• Validate outliers — When a region, device, or hour stands out, re-test in that context and review creative, placement, and destination performance.
• Document decisions — Capture the actions you take (for example, size increase, CTA change, destination tweak) so future reviews connect outcomes to changes.