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Customer Order Viewed Log Documentation

Menu Location: (Customer detail page or order tracking)

Access Level: Manager and above

Last Updated: 2026-03-01


Overview

Customer Order Viewed Log tracks when customers view their orders on the customer-facing website. This engagement metric helps identify customer interest, potential order issues, and customer service opportunities.

Primary Functions:

  • Track when customers view their orders
  • Monitor customer engagement with order details
  • Identify customers repeatedly checking orders (may indicate concern)
  • Measure post-purchase engagement
  • Support customer service investigations
  • Understand customer behavior patterns

What is Tracked

Logged Events:

  • Customer ID who viewed order
  • Order ID that was viewed
  • Date and time of viewing
  • Number of views per order
  • Customer's device/browser (optional)

Use Cases for Data:

  • Identify anxious customers checking order status repeatedly
  • Measure engagement with order tracking
  • Correlate viewing with customer service contacts
  • Understand post-purchase customer journey
  • Identify orders generating most customer interest

Accessing the Log

View Options:

  • From Customer Detail: See all order views for specific customer
  • From Order Detail: See viewing history for specific order
  • Standalone Report: All order views across all customers

Typical Display:

  • Date/Time viewed
  • Customer name (link to customer detail)
  • Order ID (link to order)
  • View count (how many times viewed)
  • Days since order placed

Common Use Cases

Use Case 1: Identify Concerned Customers

Customer viewed same order 8 times in 2 days - may be worried about delivery.

Action: Proactively contact to provide update and reassurance.

Use Case 2: Correlate with Support Tickets

Customer contacted support asking about order - check if they viewed order first.

Insight: If yes, order page info may be insufficient. If no, customer may not know how to check order status.

Use Case 3: Engagement Metric

Track what percentage of customers view their orders after purchase.

Benchmark: High engagement = customers interested in tracking. Low = may need better communication about tracking availability.

Use Case 4: Delivery Problem Indicator

Customer viewing order 20+ times day before delivery = potential delivery anxiety.

Action: Check order for address issues, verify tracking info accurate.

Use Case 5: Feature Usage Analysis

Determine if customers use order viewing feature.

Result: If low usage, may need to promote tracking feature. If high usage, ensure page provides valuable information.


Interpreting View Patterns

Normal Patterns:

  • 1-3 views total per order
  • Views concentrated around order placed and delivery dates
  • Single view to confirm order details

Concern Indicators:

  • 5+ views in 24 hours
  • Repeated views with no order updates
  • Viewing immediately before contacting support
  • Daily views for weeks after delivery

What Repeated Viewing May Indicate:

  • Missing or unclear tracking information
  • Delayed shipment
  • Customer anxious about delivery
  • Checking for updates/changes
  • Quality concerns about order contents

Proactive Customer Service

When to Contact Customer

High-Priority Situations:

  • 10+ views in 48 hours
  • Viewing daily for week with no shipment updates
  • Multiple customers viewing same order (gift/business account)
  • Repeated viewing after delivery (may indicate problem)

Contact Approach:

  1. Review order details first
  2. Check for any issues (delayed, wrong address, etc.)
  3. Prepare update before calling
  4. "I noticed you've been checking your order - wanted to reach out with update"
  5. Provide reassurance and information

Benefits:

  • Prevent support tickets
  • Build customer confidence
  • Resolve issues before they escalate
  • Demonstrate attentive service
  • Reduce delivery anxiety

Reporting & Analysis

Useful Reports:

  • Orders with 5+ views in last 7 days
  • Customers who never view orders (may need email updates)
  • Average views per order (engagement metric)
  • View patterns by customer segment
  • Time of day customers check orders

Optimization Opportunities:

  • Low viewing = promote order tracking feature in confirmation emails
  • High viewing with no updates = improve tracking information frequency
  • Repeated viewing = add more detail to order status page
  • Pre-delivery surge = send proactive delivery notification

Best Practices

  1. Review daily - Check for customers viewing orders excessively
  2. Proactive outreach - Contact high-view customers before they contact you
  3. Improve transparency - Reduce anxiety by providing detailed order updates
  4. Track patterns - Understand normal vs. concerning viewing behavior
  5. Correlate with CSAT - See if view count correlates with satisfaction

Quick Reference Card

Task Action
View customer's order views Go to customer detail, check order viewed log
See views for specific order Go to order detail, review viewing history
Find high-view orders Run report filtering for 5+ views
Check recent views Filter log to last 24-48 hours
Identify engaged customers Look for consistent order checking across multiple orders

FAQs

Do customers know we track this?

This is standard analytics, similar to website analytics. Not customer-facing data.

Can I see what customers viewed on order page?

Depends on tracking detail. Typically tracks page view only, not specific sections clicked.

Why do some customers never view orders?

May prefer email updates, already know delivery date, or trust process without tracking.

Is high viewing always a problem?

Not necessarily. Some customers just like staying informed. Pattern matters more than absolute count.

Can customers opt out of tracking?

This is server-side logging for service improvement, not opt-out-able. No personal data collected beyond order relationship.

How long is data retained?

Typically 90-180 days. Older data may be archived or aggregated.


End of Documentation

For additional help, contact your system administrator or Kiva Logic support.