I have over 300 post-its randomly scattered over my miro board. The post its have different colours and tags (13 tags). Firstly, I want to separate these post-its based on their tags and then organise each group of post-its into rows and columns (post-its evenly spaced out from each other instead of randomly spaced out)
- Probably the simplest way would be to export all of the sticky note to a CVS file, open in a spreadsheet application (Excel, Google Sheets), sort the sticky notes by tag, and the copy-and-paste the spreadsheet cells back to the board by in groups by tags (note, you would have to add the tag again if it is still needed).
Example - export to CSV:
And how they look in Excel:
Move on exporting to CSV in the Board Export → Export to spreadsheet (CSV) Help Center article:
#2 - You could also try is to install the Clusterizer app, which will group sticky notes by their tags - check it out here: https://miro.com/marketplace/clusterizer/
You can use the board’s search functionality to filter objects by tags.
At the top-right corner of the board, click
- Search
- the filter icon
- click on Everywhere to open the menu
- and then click on tags
And now use Ctrl+click to individually select a group of objects by their tag (I think Cmd+click on a Mac?) and now they are selected and you can drag them off on their own and use the auto-layout feature to make them pretty :)
Here’s one idea that uses Clusterizer then Miro’s auto-layout tool. Video demo below.
Clusterizer can struggle with too many tags… if the tag combinations are too densely interconnected… but may work just fine for you.
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Hope it gives some food for thought.
I see what you did there… nice find! It seems the assumption is that one clones off all tags into a grouping based on each tag… So, if N tags, then N groups and items with K number of tags will be duplicated K# of times into their respective (per-tag) groups.
I like this approach and have been thinking of adding it as a Clusterizer feature… where its just about … “what’s tagged by each tag? … let me scan by tag...”
However -- if a person is seeking combinatorial goodness…
Just keep in mind - (nerd alert) - that,
if… N = Number of Tags,
then number of tag groupings (clusters / unique sets of tags) = 2^N
So for @ Tanish … at N=13, there are a possible 8192 tag groupings…
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