SleekView for WP Review: ratings & reviews as customizable tables
Read WP Review's review meta from the post being reviewed. Pivot criteria scores, average rating, and user vote counts into proper columns. Spot inconsistent ratings across the entire review corpus in one view.
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Review ratings as a real corpus, not per-post fields
WP Review (MyThemeShop) attaches the review box to the post being reviewed and stores the criteria scores, overall rating, user vote tallies, and review type in postmeta on that post. Common keys include wp_review_total, wp_review_type, wp_review_user_total, and per-criterion meta. The plugin was closed on WordPress.org in May 2025 due to a security issue, but existing installs continue to work and the data still lives in your database.
SleekView reads across every reviewed post and pivots the criteria scores into columns. The corpus view is what an SEO lead or editorial manager actually needs: editor score next to user average, vote counts visible, last-updated date sortable. Stale reviews surface immediately when sorted by last-updated, and scoring drift between reviewers shows up when criteria scores are visible side by side rather than buried in individual review posts.
Inline edits write through update_post_meta(), so any caching the plugin maintains is invalidated normally. SleekView is also a useful migration aid if you're moving off WP Review post-closure: the entire review corpus exports to CSV from the table view, which makes seeding the destination plugin's import path straightforward.
Workflow
From per-post review meta to a corpus refresh queue
Discover the review meta
postmeta for the WP Review keys (wp_review_total, wp_review_type, wp_review_user_total, per-criterion keys) and lists every post that has them attached.
Pivot criteria into columns
Save the refresh queue
Inline-update after retesting
Sample columns
A typical WP Review corpus view
postmeta keys for each reviewed post and pivots criteria scores into columns.
wp_postmeta (review meta on parent post)
| Post | Type | Score | User Avg | Votes | Updated |
|---|---|---|---|---|---|
| Best 4K Monitors 2026 | Star | 8.4 | 7.9 | 184 | Apr 24 |
| Mechanical Keyboards | Point | 9.1 | 8.6 | 412 | Apr 22 |
| Standing Desks | Star | 7.2 | 6.8 | 92 | Feb 18 |
| Old Webcam Roundup | Percent | 6.0 | 5.4 | 12 | 2023-08-04 |
Comparison
Default WP Review admin vs SleekView
Default WP Review admin
- Review data is per-post — no corpus view to spot inconsistencies
- Criteria scores live in postmeta but aren't surfaced in any list
- Average user-rating drift over time isn't easy to track
- Stale reviews (no updates in months) blend into the post list
- Comparing two reviews requires opening both posts side by side
SleekView
- Read review postmeta across every reviewed post
- Pivot criteria scores into columns for easy comparison
- Spot stale reviews with the last-updated column sorted
- Surface user-rating averages alongside editor scores
- Filter by review type (star, point, percent) and category
Features
What SleekView gives you for WP Review
Corpus-wide rating overview
See every reviewed post in one table with editor score, user average, and vote count side by side. Spot scoring drift between reviewers and visitors at a glance.
Inline-edit criteria scores
Update individual criteria scores or the overall rating directly in the row. Useful for refresh passes after retesting products without opening each post.
Find stale reviews fast
Sort by last-updated and filter by category to find reviews that haven't been refreshed in 12+ months — the SEO-critical refresh queue, surfaced in one click.
Audience
Who uses SleekView for WP Review
Editorial teams
Refresh queue: stale reviews sorted by last-updated, filtered by category, with criteria scores visible to identify exactly what to retest first.
SEO leads
Reviews with declining user ratings — spot products that aged poorly and either retest or de-emphasize before rankings start eroding from trust signals.
Reviewers
Cross-check criteria-score patterns across your own reviews. Catch unconscious scoring drift before a pattern becomes a credibility problem with readers.
The bigger picture
Why a review corpus needs corpus-level visibility
Review-driven SEO sites live or die by trust signals: consistent scoring, recent updates, and alignment between editor and user opinion. WP Review attaches review meta to individual posts, which is fine for displaying a single review but useless for managing 200 reviews across a corpus. Editorial drift is the silent killer — one reviewer scores keyboards harshly, another scores monitors generously, and the inconsistency shows up only when readers compare reviews and notice.
Stale reviews are the second silent killer. A 2023 "best webcam roundup" still ranking in 2026 with no updates either gets quietly de-prioritized by Google or actively harms credibility when readers spot outdated picks. The default WP Review admin gives no corpus view to surface either problem.
SleekView pivots the meta into a table sorted however the editorial team needs it: by last-updated to find the refresh queue, by user-vs-editor delta to find scoring drift, by criterion to find reviewers whose scoring patterns lean a particular direction. None of that requires the WP Review plugin to be active — once data is in postmeta, SleekView reads it independent of the plugin's UI, which matters specifically because the plugin itself is closed.
Questions
Common questions about SleekView for WP Review
On the post being reviewed, in postmeta. Common keys include wp_review_total for the editor's overall score, wp_review_type for the rating style (star, point, percent), wp_review_user_total for the user-rating average, and per-criterion meta keys for each criterion you've configured. SleekView reads them all without depending on the plugin's admin.
The plugin was closed on WordPress.org in May 2025 due to a security issue. Existing installs continue to work — WordPress doesn't auto-deactivate closed plugins — and the review data is still in your database. SleekView reads it independent of the plugin's UI, which matters specifically because the plugin itself is no longer receiving updates and the admin may break with future WordPress releases.
 
Yes. WP Review stores both — the editor score in wp_review_total and the user-rating average in wp_review_user_total. Add both as columns, sort by the delta between them, and you immediately spot reviews where the editor's verdict and the visitor consensus have drifted apart. That's the most useful single view for trust audits.
Yes. Inline edits go through update_post_meta(), which is the standard WordPress meta API. Any caching the plugin does keyed on those meta keys is invalidated normally. The front-end review boxes re-render with the new values on the next page load. No extra cache flushing is required for the meta changes themselves.
Yes. Review type is stored in wp_review_type as a meta key on each reviewed post. SleekView treats it as a filterable column. Useful when you've migrated rating styles between criteria sets and want to audit which posts are still on the legacy type — sort by type, filter by old value, refresh in a batch.
SleekView is a great migration aid for exactly this case. See all your reviews in one table, export as CSV, and use that to seed whichever review plugin you move to. Postmeta-based reviews are easy to map because the data structure is flat. Once migrated, you can keep SleekView pointing at the new plugin's storage to maintain the corpus view.
 WP Review writes JSON-LD review schema based on the postmeta values. SleekView only changes the meta values when you edit them; it doesn't touch the schema generation. Updated scores produce updated schema on the next render. If you're retesting and rescoring, the rich-result preview reflects the new value automatically.
 Yes. Add category as a column and group or filter by it. Sort by editor score within a category to produce "best monitors" or "best keyboards" leaderboards inside the admin. That same data export feeds programmatic landing pages — pair this view with SleekRank if you want public-facing leaderboards generated from the corpus.
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