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the age and gender page is similar to the what matters most page it's going to show you the different age and gender buckets together with the total spend on those buckets the percentage of the total so you can quickly see what's most important to you number of sales and the percentage of sales along with roads just as we had before with the difference compared to the average and where the revenue is coming from now this time because we're looking here at um impressions and rowers we are able to see this on uh with two y axes which makes it much much easier to see and across here i've actually put a trend line or a uh using the words a line to show the the average rowers for the whole thing that we're looking at so again if we change this and let's go search only our total there are average row as for everything that we're looking at now changes to 12.4 and so the average line on the chart changes to 12.4 that's the average of whatever it is that we've segmented so if we look at desktop only maybe for just uh everything except brand let's say if they were brand campaigns now again we've got an average row as here of 10 and we can see which age buckets are getting impressions but over performing it looks like 35 to 44 and this undetermined bucket here are over performing in terms of rowers you can see that shown in the table by the darker red colors and then similar sort of thing down here for the gender you should see undetermined be a fairly small percentage of your account these days so around about 10 to 15 is pretty normal if you're seeing anything higher than 25 maybe 30 percent then maybe dig into that it might just be the industry you're in where maybe you don't have as many logged in users and again we're looking at you know where are we spending money compared to where our results are and where are there big differences in that so if i'm spending 17 percent of my money here but only getting 13 of my results whereas in this bucket i'm spending 15 of my money and getting 19 my rev then maybe i start to dig into that i at least start thinking about bid modifiers on age and gender if we're not using smart bidding but also think about how you can use this data in other ways