Fix Issues

Beta

Find and fix data quality problems across your catalog

82

Quality Score

82%

across 1,247 products

Issues to Fix

102
12 critical
34 medium
56 minor

After Fixing All Issues

8285
+3 pts

Work through the steps below to reach your projected score

Speed up your fixes with Bulk Actions

Select multiple products and apply bulk actions to fix issues faster

102 products need attention

Open Products
1
Filter by issueSelect issue type
2
Select productsCheck the boxes
3
Apply actionUse bulk menu
Done!Issues fixed

Quality Improvement Roadmap

Step by step toward better data quality

82
Current
97
Projected
+15 pts
Overall Progress0 of 4 phases complete

Target: 85% quality score

Complete all phases to exceed your target!

Quick Wins

Quick improvements that move your score the most

1
Content
+8

Add missing product descriptions

224 products are missing descriptions. Adding descriptions can improve SEO and conversion rates.

high impact
medium effort
15-30 min
Fix Products
2
SEO
+6

Complete meta titles

312 products need meta titles for better search engine visibility.

high impact
low effort
10-15 min
Fix Products
3
SEO
+4

Add missing meta descriptions

474 products are missing meta descriptions. This affects click-through rates from search results.

medium impact
medium effort
15-20 min
Fix Products

Issues by Category

Pick a category to review. The one with the biggest potential score gain is pre-selected.

SEO Fields

Search engine optimization fields

2 Important

SEO & Conversion Deep Dive

Scores broken down by component

Good balance, continue improving both
SEO Score
71%
Focus: Keyword Optimization
Conversion Score
78%
Focus: Persuasive Content
SEO Components
Meta Tags
69%
Content Structure
75%
Keyword Optimization
Priority
63%
Technical SEO
91%
Conversion Components
Persuasive Content
Priority
75%
Trust Signals
94%
Visual Appeal
87%
Purchase Enablers
98%
Scores are well balanced across both domains

Schema Suggestions

Attributes spotted in supplier feeds or on competitor pages that you haven't added to your data model yet.

4 suggestions

Material

select

material

Supplier feed
Prevalence in Acme Distribution84%
Examples:
Stainless steel
Aluminium
Recycled PET

Most supplier rows carry a material value, and it's a common shopper filter.

Warranty period

text

warranty_period

Competitor
Prevalence in competitor-store.com63%
Examples:
2 years
5 years
Lifetime

Competitor product pages consistently show a warranty period above the fold.

Energy rating

select

energy_rating

Marketplace
Prevalence in Bol.com41%
Examples:
A
A++
B

Marketplace listings in this category require an EU energy label.

Country of origin

text

country_of_origin

Supplier feed
Prevalence in Nord Supply57%
Examples:
Germany
Netherlands
Italy

Better with your actual data

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