Average Edit Time
Customers edited orders within an average of 5 minutes after purchase. About 66.7% made multiple edits in the same order.
→ Shows how quickly customers act and whether they often revise more than once.

Top Edit Location
Example: Customers from Texas made the highest number of order edits this week.
→ Helps identify regions where edits are most frequent, which can inform localized strategies.

Address Changes
Example: Most edits were related to shipping address changes.
→ Highlights the most common edit type, often signaling checkout issues that can be optimized.

If customers use post-purchase editing or upsell offers, every product they add appears here.

Helps measure the effectiveness of upsell strategies and whether customers are engaging with order edits to increase cart size.

A high number indicates strong customer responsiveness to upsell opportunities.

Shows which products are the most attractive for upselling.

Allows merchants to fine-tune upsell strategies by featuring products that consistently perform well.

Can also reveal trends — e.g., seasonal items or discounted products being added most frequently.

Example: A 5% growth means more orders are coming in compared to usual.

Helps merchants quickly see if sales are trending upward or downward week-over-week.

Useful for spotting the impact of promotions, seasonal spikes, or marketing campaigns.

Example: If Tuesday has the most edits, merchants may plan support staff availability or upsell offers around that day.

Useful for identifying patterns in customer activity and aligning operational or promotional efforts accordingly.

Example: If 1% of edits are address-related, merchants can assess whether customers face common shipping mistakes.

A higher percentage could indicate issues like unclear address input fields or frequent customer relocations.

Helps merchants decide whether to improve checkout UX or add extra address validation steps.

Example: If customers frequently update addresses, it could highlight checkout errors or last-minute delivery changes.

Helps merchants evaluate whether they need to improve address validation or provide clearer delivery instructions.

Useful for shipping accuracy and reducing failed deliveries.

Example: If most edits come from a specific region, it may indicate localized issues (e.g., payment gateways, shipping carriers, or address formats in that area).

Enables merchants to spot regional behavior patterns and optimize customer experience by region.

Example: A high number suggests customers rely on invoices for record-keeping, tax purposes, or returns.

Helps merchants monitor invoice engagement and determine whether they need to improve invoice customization or add features like tax breakdowns.

Example: If a customer buys a T-shirt and then accepts an upsell offer for matching accessories, the revenue is recorded here.

Helps merchants measure the effectiveness of upsell campaigns.

A low or zero value might mean upsell conditions need adjusting (e.g., wrong product pairing, no discounts, or poor targeting).

Example: If "Water Bottle" is the most accepted upsell, merchants know it pairs well with other items.

Identifies customer-preferred upsell products so merchants can replicate success across more campaigns.

Provides insight into which items have the highest add-on potential.

Displays the specific reasons customers canceled their orders (e.g., wrong size, delayed delivery, changed mind, duplicate order).

Helps merchants identify recurring issues that lead to cancellations.

Example: If most cancellations are due to shipping delays, the store can improve logistics or offer faster delivery options.

Insight: This metric is critical for reducing preventable cancellations and improving the post-purchase experience.

Tracks the total number of order cancellations processed within the selected time frame.

Shows whether cancellations are being handled efficiently (e.g., refunds processed, stock updated).

Example: If 10 cancellations occurred but only 6 were handled, it signals a potential backlog in order management.

Insight: This helps merchants ensure cancellation requests don’t slip through, maintaining trust and reducing support tickets.

Why orders are canceled (the root cause).

How many cancellations were managed (the operational response).

This section provides a high-level overview of cancellation trends within the selected time frame.

Instead of focusing on individual reasons or handled cases, it shows patterns and insights that help merchants understand the bigger picture.

Example insights might include:

Value: These insights help merchants spot recurring behaviors and prevent future cancellations by improving product descriptions, inventory availability, or delivery timelines.