No. SleekView Feedback reads directly from whatever table or post type you use to mirror FullStory data in WordPress. 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 FullStory writes shows up on the next load.

Yes. SleekView only needs a WordPress account, and support agents can be members or contributors without paying for an extra FullStory seat. They open the board, upvote the session card, and the vote writes back to the same row the product team queries later in FullStory itself.

Each logged in user is tracked by user ID, and anonymous voters are scoped by cookie token. The plugin also exposes a rate limit so one IP cannot spam the board, which is enough to keep both internal and customer facing boards honest without forcing extra friction or signups.

Yes. SleekView accepts a WHERE clause when you wire up the data source, so you can scope the board to a saved segment, a release version, a single funnel step, or any combination of meta fields you already store. Different boards on different pages can use different filters.

Dead click is just a category value on the row. You can write it into a meta key you already use or a dedicated column. Either way it shows up in the WordPress admin alongside the session, so the engineer who fixes the button can see the flag without leaving WordPress or hunting in JIRA.

They write back to the source column in WordPress, which means saved segments, CSV exports, and any of your own queries can sort by that score. Several teams use the score to gate which sessions get reviewed first, 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 really big projects, scoping the board by segment or release keeps both the query and the audience focused, so the page feels snappy even at scale.