From the course: Marketing Tips

Best practices for organizing UTM tags for campaigns

From the course: Marketing Tips

Best practices for organizing UTM tags for campaigns

- [Brad] Hey, and welcome to another episode of Marketing Tips. I'm Brad Batesole, and this week, I wanna give you a great approach to organizing your UTM tags. Now, I'm going to assume that you're already familiar with UTM tagging and Google Analytics, and this is where you add tracking parameters to your URL in order to track your source, medium, and campaign. Now you'll see an example here of how a URL looks once all the tracking is in place. Now, one thing that I run into often when working with new marketing teams is a mess of campaign tags. This lack of organization can really impact your productivity, and make it challenging to extract the data that you need to see how your campaigns really performed. To frame the problem better, let's start by talking through a scenario. Let's say that we're going to run a campaign for back-to-school. Perhaps we run an online store that sells backpacks, notebooks, and pens. So, I might start by walking through a strategy. Here I have my back-to-school campaign, I'm planning on running Facebook ads and Twitter ads, and for each of these, I will run ads for backpacks, notebooks, and pens, and each of those will have a different offer that I'm going to compare. Say it'll be 10% off, free shipping, or a free gift. I'm going to run all of this simultaneously, and determine which of these perform the best. So, we'll launch the campaign, and typically build a simple spreadsheet for ourselves as a way to remember what campaign tags we used for each of the offers. Now you may have a slight structure to your tagging, or you may simply use whatever seems appropriate, and create a mess that looks similar to this campaign tag column. Here I don't really have any rhyme or reason, I've simply use whatever made sense at the time, but I made a key for myself, which means it should be straightforward. I can simply go pole this campaign tag, capture how many sales or other important pieces of data were relevant to that campaign, and attach it to my spreadsheet. Easy enough. Now it works, but it's not really that efficient. Let me show you a better approach. I prefer to instead use a formula. I take the key campaign, and then I add in all of the shared elements, like building blocks. So I'll build these on top of that campaign name, and then I'll add anything that is special or unique at the very end. Let me walk you through our previous scenario to explain what I mean here. So, here we have our previous campaign outline. So back-to-school is my campaign. This is the first building block. Now, Facebook ads is going to show up in the source and medium as Facebook and paid-social, so that's not important to our campaign tag. We can leave those out since that data is already existing somewhere else. So the next shared block is going to be whether it's backpacks, notebooks, or pens. These are like the ad group. And then the other shared block is whatever the offer is, 10% off, free shipping, or free gift. So this might show up as back2school as the campaign, backpacks, 10off, and then ad1, or free shipping and ad1, or notebooks, 10off, and ad1. Now in this example, I may end up with a spreadsheet that looks more like this. So here you can see there's a very unified structure. I have back2school as the campaign that I'm running. Now these are all of the backpacks, and they all share the same offer name, 10off, free shipping, or freegift, and then maybe there's a unique value at the very end, a call to action variation that I'm using. So what this lets me do is identify various key points very quickly in aggregate. Now, normally you'd be polling this data in Google Analytics using filters, but I don't have this in Google Analytics, so I'm going to filter here on the spreadsheet, but pretend that I'm in Google Analytics. So for starters, we could see how back-to-school performed as a whole. So all of the aspects of our campaign in aggregate. We'd simply have to create a filter in Google Analytics for back-to-school, and would see all of this. Let's say that instead, we wanted to see how all backpacks performed in the back-to-school campaign. Now, perhaps we had multiple campaigns running, and so we may have different campaign tags, but we do have backpack as a unified piece. So, I could start by looking for back2school-backpack. And now I'm going to see how all of my backpack campaigns performed. But let's say that I wanted to see how all of my free shipping offers compared across all of the different products that I sold. Well what I can do now is simply search for freeship. And what this lets me do is see between backpack, notebooks, and pens, how the free shipping offers compare in aggregate. As you can see, you have building blocks, so you can get granular as you do your filters, or you can look at things in big swaths. This allows you to generate reports a lot quicker, as well as demonstrate your results on specific items of your campaigns. It takes just a few minutes to come up with a naming convention, but I encourage you to dial in a best practice that makes sense for your workflow.

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