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✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

SleekView Feedback for Perplexity AI for WP

Perplexity AI for WP logs every query, answer, and source citation inside WordPress. SleekView Feedback reads those rows and renders them as a sorted board with votes, status pills, and category tags so your team can flag weak sources, request better topics, and track which answers get shipped.

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SleekView Feedback board for Perplexity AI for WP

From Perplexity answer logs to a live review board

Perplexity AI for WP saves every query and the answer it returned, with the model, the citations, and the timestamp attached as meta. That is great when you want to debug one bad answer, but it is a poor interface for a team that wants to know which of the last hundred research queries actually held up, which citations were broken, and which topics keep coming back.

SleekView Feedback reads any data source you point it at, including a custom query against wp_posts, the plugin log table, or a filtered slice of postmeta by topic. It renders one card per query with the answer summary, vote count, author, category pill, and status pill, and votes write straight back to the score column you wire up.

The board becomes a shared review surface where citation problems, fact check requests, and topic suggestions all live next to the answer they refer to. Editors triage what to publish, researchers track what needs a re run, and readers contribute the signal you cannot get from a back office logs table.

Workflow

From Perplexity queries to a sorted feedback board

1

Pick the Perplexity source

Point SleekView at the post type or log table Perplexity AI for WP writes to. Saved answers in posts, queries in a CPT, or run logs all work. Apply a WHERE clause to scope by model or date so the board only surfaces the queries your team is reviewing.
2

Map vote, status, category

Choose the column that counts as upvotes, the column holding the status label such as draft or approved, and the column carrying the topic or campaign tag. SleekView reads those columns on every render so the board reflects what Perplexity did last.
3

Embed the feedback view

Drop the SleekView block on a page or use the shortcode. Visitors see a paginated list of answers with title, vote count, author, status pill, and category pill. Filter by topic or status, restrict to editors, or open the board to readers with one setting.
4

Votes write back to the source

Every upvote increments the score column on the row. Future Perplexity queries sort by that score, prioritise topics with traction, and retire ones that keep returning weak citations. The feedback loop becomes a number on the row instead of a hunch in Slack.

Sample board

Sample Perplexity AI review board

A look at how recent Perplexity answers land on a SleekView Feedback board, with citation flags, topic requests, and editor praise mixed together in one sortable list.
312 votes
Citations for SaaS pricing answers link to dead pages
Mira Schroeder Citation Investigating
204 votes
Add a research preset for European VAT rules
@taxnerdjen Topic request Planned
138 votes
Answer length feels short for technical queries
Devon Carter Quality In progress
97 votes
Switching to sonar large model improved sourcing
Anders Lindquist Praise Shipped
62 votes
Saved answer block crashes when no citations exist
@buildwithliu Bug Open
18 votes
Allow follow up queries in the same saved thread
Hugo Bertrand Feature request Under review

Comparison

Plugin admin screens vs SleekView Feedback

Perplexity plugin defaults

  • Query logs sit in a back office screen only the AI admin ever opens
  • No way for editors or readers to upvote answers that held up to review
  • Bad citation reports live in Slack screenshots, not next to the answer
  • Status of each saved answer is buried in row level meta with no shared view
  • No public queue to show clients which topics are queued, shipped, or killed

SleekView Feedback

  • One card per Perplexity answer with title, votes, status pill, and category tag
  • Upvote writes back to the source column so future queries can sort by score
  • Filter by model, topic, or status using any column in wp_posts
  • Embed on a public page or behind a login with one block or shortcode
  • Citation flags live next to the answer so researchers can fix the source

Features

What SleekView Feedback gives you for Perplexity AI for WP

Citation review inline

Each Perplexity answer becomes a votable card with its citations attached. Readers and editors flag broken links or weak sources with one click, and the researcher sees the flag in the WordPress admin instead of hunting through a Slack thread.

Topic backlog from real signal

Add a Topic request category and the board doubles as a public research backlog. The team can see which topics readers keep asking for, prioritise the ones with traction, and retire saved queries that get no engagement at all.

Upvotes feed back into runs

Because votes write to the source column, you can sort Perplexity saved answers by score, give high voted topics more research time, and quietly drop the ones that fall flat. The feedback loop becomes a number in the database that the next run can read.

Audience

How teams use the Perplexity feedback board

Editorial team review

Editors upvote the Perplexity answers worth turning into articles and flag the ones that need a rerun. The board replaces a messy doc and gives the editor in chief one screen to triage research every morning.

Client facing topic vote

Agencies share the board with clients so they can vote on which Perplexity research threads to keep. The client sees exactly what is shipping next week and feels in control without ever opening the WordPress admin.

Citation audit queue

Fact check teams use the board as a citation queue. Anything flagged with a high vote count gets reviewed first, and resolved items move to a Fixed status so the audit trail stays visible without trawling raw query logs.

The bigger picture

Why a Perplexity feedback board changes the workflow

Perplexity AI for WP gives you cited research at scale, but the value of that research collapses the moment a citation breaks, a source is misread, or a topic stops mattering. Most teams find out about these problems weeks later, usually from a reader complaint or a SEO audit, by which point the answer has already been republished, summarised, and quoted across three other pages. A feedback board fixes that pattern.

Each saved answer becomes a public artifact your team and your audience can react to. Bad citations get flagged the day they go live, topics with no upvotes get retired before the researcher burns more hours on them, and high voted threads become the backbone of your next quarter of content. Because every vote writes back to the source row, the next Perplexity run already knows which topics earned reader attention and which sources held up to scrutiny.

The result is fewer broken citations, fewer wasted research hours, and a much shorter loop between a question your audience cares about and an answer you can defend in writing.

Questions

Common questions about SleekView Feedback for Perplexity AI for WP

No. SleekView Feedback reads directly from whatever table or post type the Perplexity plugin uses. You point it at the source, pick the columns for votes, status, category, author, and title, and the board renders. No ETL job, no sync, no duplicated data. Anything Perplexity writes shows up on the next page load.

 

Yes. SleekView ships with anonymous voting backed by cookies so public visitors can upvote answers and topic requests without an account. You can also require login to restrict the board to editors or paying members, and the same view handles both modes with one toggle.

 

Citation is just a category value on the row. The flag stores the visitor note and links back to the source answer in the WordPress admin, so the researcher who built the saved query can review the flag, fix the source, and rerun without leaving WordPress.

 

Yes. SleekView accepts a WHERE clause when you wire up the data source, so you can scope the board to sonar large runs, sonar small runs, runs from a particular topic cluster, or any combination of meta fields. Different boards on different pages can use different filters.

 

Each visitor gets a cookie scoped vote token per item. Logged in users are tracked by user ID. A built in rate limit caps how often a single IP can hit the vote endpoint, which keeps public boards honest without forcing a signup wall in front of casual readers.

 

They write back to the source column, which means the plugin and any of your own queries can sort future saved answers, reruns, and topic queues by that score. Several teams use the score to gate which topics get more research time, which makes the board operational and not just a vanity dashboard.

 

Both. SleekView ships as a Gutenberg block, an Elementor widget, a Bricks element, and a classic shortcode. Theme developers can also call the render function from PHP and pass a configuration array, so you can mount the board on any template without touching the page editor.

 

The view paginates server side and only loads the rows it needs to render the current page. Indexed columns stay fast even on long tables. For larger projects, scoping the board by topic or campaign keeps both the query and the audience focused so the page feels snappy even at scale.

 

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