Google PPC – Visualise & optimise your demographic data

Demographic exclusion is an easy win to make your campaigns more effective. Straight away you can see who is and isn’t buying your product. If you already have a good grasp on who your target audience is you can make these campaign changes right from the start.

Here is a very easy way to see where your money is being spent and how to make changes. This is using the new Adwords interface.

For this client the people who buy the different products can be very different. So we will be looking at this on a campaign by campaign basis.

First of all select your campaign from the black bar on the far left. Or if you want to take a look at overall demographic data then select ‘all campaigns’ at the top left of the page.

Next, click on ‘demographics’ on the light grey bar which is second in.

Next is to make sure that you have conversion data in the report as the standard view doesn’t have this in. Click on the symbol as highlighted below which in on the right of the page. Click on conversions and tick the conversions box. At this stage I recommend ticking ‘cost/conv’ and ‘conv. Rate’ too and also ‘conv. Value’ if you have this setup and save the set of columns for later use to make reporting and optimising easier.

Next on the chart area click on the drop down that’s next to clicks and select conversions.

This gives us a quick and easy overview on what age groups are converting. For this particular product only people in the 45-54 age group and 'unknown' were buying. This also confirms with our clients own historic data that this is our target age group so we excluded the 18-24 and 25 -34 age groups from the campaign. This is easily done by clicking ‘more’ button and clicking on exclusions then simply tick the box of the age group that you want to exclude and click save.

We can also follow this process for gender and household income to refine further.

Where this report could fall down depends if your product can be bought for a gift particularly around Christmas, Halloween, Valentine’s day etc. Look at historic data around these and any other time frames of interest to see if the buying profile of customers change. If it does then make sure to adapt the strategy depending on the time of the year.


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