Calculate the Error Frequency:
Use the values from the columns "[Column with total number of errors]" and "[Column with total number of user interactions]" in the attached CSV to calculate Error Frequency using the following formula:
Error Frequency = (Total Number of Errors ÷ Total Number of User Interactions) × 100
After calculating the Error Frequency, report where it lands on the following scale (lower is better):
Very Good = below 5%
Good = 5–9%
Average = 10–19%
Poor = 20–29%
Very Poor = 30% and above
Next, analyze the responses in the column "[Column with qualitative explanations]" in the CSV (e.g., open-text feedback or error descriptions) to identify the most common error types and provide clear, actionable suggestions for how Error Frequency could be reduced.
Error Frequency — Example Report
Summary
Error Frequency: 13.0% → Average
Total User Interactions: 25,000
Total Errors: 3,250
Calculation
Error Frequency
=
3,250
25,000
×
100
=
13.0
%
Error Frequency=
25,000
3,250
×100=13.0%
Scale placement: 13.0% falls in Average (10–19%).
Key Breakdowns (from CSV)
By device
Mobile: 14,500 interactions / 2,320 errors → 16.0% (Average–Poor)
Desktop: 10,500 interactions / 930 errors → 8.9% (Good)
By step (top contributors)
Step Interactions Errors Error Freq
Shipping address form 5,800 1,220 21.0% (Poor)
Payment entry 4,200 620 14.8% (Average)
Account creation 3,700 410 11.1% (Average)
Cart 6,300 520 8.3% (Good)
Review/Confirm 5,000 480 9.6% (Good)
By error type
Validation—format mismatch (email/phone/zip): 34%
Field required / missing: 26%
Payment declines / tokenization errors: 18%
Form submission timeout / network: 12%
Promo code invalid / expired: 10%
Qualitative Insights (from explanations column)
“Zip code kept rejecting on mobile keyboard with spaces.”
“Payment form cleared after an error—had to retype everything.”
“Didn’t know which fields were required; tiny labels.”
“Promo code applied on desktop but failed on phone.”
Recommendations (prioritized)
Harden validation UX on mobile forms: normalize input (strip spaces, auto-format), show inline, specific instructions (e.g., “5 digits, numbers only”).
Make required fields explicit: larger labels, “Required” badges, and real-time completion ticks; reduce nonessential required fields on Shipping.
Improve payment resilience: preserve field values on error, retry with clearer reasons (issuer decline vs. AVS mismatch), and enable network-aware resubmits.
Stabilize mobile network flows: add optimistic UI + exponential retry for submit, surface offline banner when disconnected.
Unify promo code logic across devices; pre-validate before submit and expose rule hints (min spend, item exclusions).
Next Checks
Ship form normalization + inline validation on Shipping; success metric: Shipping error frequency ≤ 12% (from 21%).
Track error frequency by device weekly; target mobile ≤ 10% (Good).
Add error taxonomy logging (type, field, step, device) to isolate the next biggest driver.
Run a quick usability test on the Shipping form with mobile participants to confirm reduced validation friction.
Target: reduce overall Error Frequency from 13.0% → ≤9.0% (Good) within the next iteration.