No. SleekView Feedback reads directly from whatever table or post type you use to mirror Optimize experiments 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 Optimize writes shows up on the next load.

Yes. SleekView only needs a WordPress account, and designers and editors can be members or contributors without paying for an extra Google seat. They open the board, upvote the variant card, and the vote writes back to the same row the growth analyst queries later in Optimize.

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 a single IP cannot spam the board, which is enough to keep both internal and client facing boards honest without forcing any extra friction.

Yes. SleekView accepts a WHERE clause when you wire up the data source, so you can scope the board to a single landing page, a property, a date range, or any combination of meta fields you already store. Different boards on different pages can use different filters.

Broken 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 experiment, so the developer who fixes the variant can see the flag without leaving WordPress or hunting in Slack.

They write back to the source column in WordPress, which means CRO dashboards, exports, and any of your own queries can sort by that score. Several teams use the score to gate which winners get rolled out first, which makes the board operational and not just a vanity widget for the wall.

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 programs, scoping the board by quarter or property keeps both the query and the audience focused, so the page feels snappy even at scale.