The Adobe Experience Cloud Debugger is indeed an official tool developed and provided by Adobe, so it is as reliable as the DigitalPulse Debugger.I would argue that it is more user friendly, since it provides friendly names for the evars and sprops. It also works with the rest of the Adobe Experienc...

Occurrences counts the times the value (in this case c1) was set and persisted. It's basically page views + events on that page. Visits are basically sessions. Google Analytics uses page views, sessions and users; whereas Adobe Analytics uses page views, visits and unique visitors. These are roughly...

In the Report you have Visits as the metric. In the Workspace table you have Occurrences. Try changing one of the metrics to match the other.

It looks like they are using the Adobe Experience Cloud Debugger: Adobe Experience Cloud Debugger - Chrome Web Store Neither omnibug nor the Adobe Debugging Tool provide the functionality this user is looking for. Namely, instead of just prop12, they want to see the friendly name their organization ...

To find this information you'll need some implementation. You'll want to have two custom events fire: one when a user is presented with the chat button, and another when the user clicks the button.You'll be able to see volume and clickthrough, but also on which pages people see/click on the button.F...

It sounds like you are trying to track app actions and add in context data. Basically when a user picks a hair color, you'd create an Context Data object with your params/values. Then you'd make the tracking call.On Android this would look like this:HashMap<String, Object> exampleContextData = new H...

It could be a problem with your Processing Rules for Marketing Channels. What rules do you have identifying Paid Search, Display, and Email?What URL parameter(s) do you use for campaign codes in those channels?You have to tell analytics how to differentiate between the channels for it to give you a ...

If you don't have access to Data Warehouse, and you also do not capture the IP address as an s.prop or something, you could try to narrow it down by other information about their technology.Does the majority of these downloads come from a single ISP? This would be the Domain dimension. Are they all ...

That seems about right to me, with the volume of total Leads. You could look at a simple table with Page as the dimension and your Participation Lead as the metric, but I believe this will show you the same two articles.Looks like during that time period you had two articles that were involved in vi...

See if you can do something like a contribution analysis. There is a built-in tool.You could also look to see if you can manually find the source of the anomaly. Were the anomalous downloads all from one specific geographic region? Did they all use the same browser or have the same ISP? Did they all...