Generating combined tag statistics
Sometimes, further visual properties are manipulated in addition to font size, such as the font color, intensity, or weight. The decision for an optimal layout should be driven by the expected user goals. Tag cloud visual taxonomy is determined by a number of attributes: A tag cloud on the web must address problems of modeling and controlling aesthetics, constructing a two-dimensional layout of tags, and all these must be done in short time on volatile browser platform.
Tags clouds to be used on the web must be in HTML , not graphics, to make them robot-readable, they must be constructed on the client side using the fonts available in the browser, and they must fit in a rectangular box .
A text cloud or word cloud is a visualization of word frequency in a given text as a weighted list. Extending the principles of a text cloud, a collocate cloud provides a more focused view of a document or corpus.
Instead of summarising an entire document, the collocate cloud examines the usage of a particular word. The resulting cloud contains the words which are often used in conjunction with the search word. These collocates are formatted to show frequency as size as well as collocational strength as brightness. This provides interactive ways to browse and explore language.
Tag clouds have been subject of investigation in several usability studies. The following summary is based on an overview of research results given by Lohmann et al.: They also compared how different arrangement of the words affects performance.
In principle, the font size of a tag in a tag cloud is determined by its incidence. For a word cloud of categories like weblogs, frequency, for example, corresponds to the number of weblog entries that are assigned to a category. For smaller frequencies one can specify font sizes directly, from one to whatever the maximum font size.
For larger values, a scaling should be made. Since the number of indexed items per descriptor is usually distributed according to a power law ,  for larger ranges of values, a logarithmic representation makes sense. Implementations of tag clouds also include text parsing and filtering out unhelpful tags such as common words, numbers, and punctuation.
There are also websites creating artificially or randomly weighted tag clouds, for advertising, or for humorous results. From Wikipedia, the free encyclopedia. In the comments of a blog entry Archived at the Wayback Machine. Archived from the original on Tag clusters as information retrieval interfaces Archived at the Wayback Machine.. Comparison of Tag Cloud Layouts: Self-organising map based tag clouds — Creating spatially meaningful representations of tagging data Archived at the Wayback Machine..
Fast algorithms for online construction of web tag clouds , Engineering Applications of Artificial Intelligence 64, pp. World Population Data Cloud. State of the Union". A New Form of Tag Cloud? Archived PDF from the original on Collaborative thesaurus tagging the Wikipedia way.
April "Archived copy". Tag Cloud Font Distribution Algorithm. Before jumping in, ask yourself if there is an easier method to get the same result. One way to track this is to automatically add "region1," "region2," and "region3" tags when a ticket is created.
That works well in Zendesk business rules, but it makes reporting more difficult. Since a ticket can only come from one region, you can create a custom drop-down field for it. You can then report on fields rather than tags. Reports using custom fields are easier to filter. You can just use the field attribute, instead of going through all the required steps to report on ticket tags.
As described before, tag data won't function in a report unless the metric connects to the tags dataset. The default Tickets metric does this for tag inclusion, but to exclude tags from your report you will need to follow the steps outlined in this section. This section will instruct you on how to build these filters using a custom metric and a numeric range filter.
This metric does two things. The inner part of the metric uses the default Tickets metric to count all tickets with a certain tag. Please note, you can't just copy and paste in the metric editor. You need to select the items below from the Elements drop-down list:. After you create your metrics, you can use them to filter your report. If you do not want to use numeric range filters to filter your report see, Adding tag filters within a custom metric.
After you add your filters, you can remove the custom metrics from your report. As long as the report is looking at ticket data, the filters should keep working. With the filters in place, only the VIP tickets that have not merged will be included in the report. The image below demonstrates the change in results:. These numeric range filters will apply to the whole report, but that is not always ideal. For example, you might want to compare the VIP resolution time above to the overall resolution time.
With report-level filters, you can't see both numbers in the same report at the same time. In cases like this, you would need to build a new metric that includes the tag filter s. This will vary a bit, depending on the metric. However, the tag filtering portion should look like this:. That way, you can filter each metric individually. This enables you to compare metrics with different filters. They have their own spot in the data model with complicated architecture to maintain their unique relationships.
Fortunately, the hard work is already done. After you create these metrics, you can apply them to any ticket-based report. Is it possible to apply this filtration at the level of a custom metric, rather than applying the filter to the whole report? I have several tags that I would like to compare on a single report, rather than creating a separate report for each tag. Essentially, I'm trying to find a way to slice Replies [Avg] by a select number of tags.
The numeric range filter is basically forcing the metric to run for each Ticket Id and then seeing if that ticket matches the conditions counting "1" ticket if it has that tag.
To get this working within a metric we need to set up this as a filter clause using MAQL:. Replace "billing" with whatever tag you want to report on. I believe this should work but let me know if you run into any snags. How would I create a metric that only returns tickets that have two specific tags? I too am trying to avoid using filters for this. If you nest metrics you can make separate calculations on the same ticket, allowing you to check for combinations of tags:.
I haven't had the opportunity to QA this extensively but from my preliminary testing it appears to work. Can you track the time in days or hours from when the specific tag was added and report it? I am trying to create a report to see how long a ticket "sits" in a specific stage. Here are 2 great resources for learning more on that:. Building Custom Metrics for the Events Model. Duration between two events in minutes.
I hope this helps! If you have questions, just drop us a line at support zendesk. I just wanted to hop in here and let you know that we've revamped this article to include additional information and clarify some things. Be sure to give it a look! That actually tries to add the metric to your report.
It's the last button you should click, once everything else is complete. That should put the color-coded element in your metric and allow you to continue. I'm trying the same thing Sean mentioned earlier, creating a metric for tickets with two specific tags.
I used the steps Joseph lists and I'm returning no results. Has anyone verified how to do this? Those steps should work. We've also updated this article since those comments were posted. There are screenshots above showing very similar metric recipes. There are a lot of moving parts in a recipe like this.
I'm going to start up a ticket for you, so we can take a closer look at your report so far. I wondered whether you could help with something I'm really struggling with or even if you can tell me whether it's possible using Insights at all we're on the Professional plan. However, this doesn't seem to work like that. I couldn't see to create what I'm after using the metrics already set up, so I built out some custom metrics.
I tried to create custom FRT metrics for tickets where the tag was 'subscribed' and for tickets where the tag was not 'subscribed' i. I then set up a report with: WHAT - the two custom metrics above.
The results however were identical for each metric and seemed to draw on the FRT metric without the 'subscribed' tag. You can see this on the date of the 3. Does anyone have any suggestions as to how I can get around this issue. It's creating a fairly large blockage in our work. If it's not possible at all in Insights, even that would be great to know so we can start exploring other methods and tools.
Ticket tags are not like other attributes. You can have any number of tags on a ticket at the same time, and you may need to report on any one of them.
To make that possible, tag data is stored in a separate dataset. This means you need to take special steps to use tags in a report. You need to use a metric that connects to the tag dataset, and you need to construct filters that work with that metric. The article above goes into the theory behind tag reporting, and it shows some examples of metrics that do and do not connect to tag data.
Tags are not like other attributes. Tickets can have any number of tags at the same time. That makes things quite a bit more complicated. A ticket may have one of the tags from your filter, but not another. There are lot of ways to handle those situations, and Insights doesn't know which one you need. Because of all this, ticket tags do not consistently work in a dashboard filter like the one in your screenshot.
We do not recommend putting a tag filter on a dashboard. If you want to use tags, you must use custom tag filtering metrics within your reports.