Google Analytics is at the core of many marketing campaigns, giving the data professionals need to adapt, improve and refine their efforts. However, what is often an afterthought in this process is the attribution model.
No matter what option you've chosen for your attribution model, it's crucial that it aligns and works in harmony alongside your Google Analytics. There's still much confusion about the difference between web analytics and attribution, and what you need to do in order to get them to be complementary.
What's the difference between Google Analytics and attribution?
Google Analytics is the data collected from any website that helps optimize its usage, while attribution is a formula that dictates how you want to assign credit to certain user actions. You can find out more about attribution models and what they mean for your marketing campaign in our guide.
In this way, the tools have very different but equally important roles in marketing. Web analytics tools are based around sessions, while attribution looks at the wider user journey from first point of contact to conversion. It's crucial that brands use both and do so in a way that allows each to perform.
How to marry Analytics and Attribution
With attribution being implemented into Google's Marketing Platform, it's easy to access both your analytics and attribution data. It's important that you have both set up in a way that the whole team understands. Why have you chosen that model and why prioritize those KPIs? You need to know this so you can align both your attribution and analytics data to your wider marketing goals.
If you measure success differently depending on what marketing channel you're looking at, your data will be inconsistent and even contradictory, leaving you with more questions than answers.
Aligning your goals in analytics and attribution
Accurate attribution depends on defining and setting goals that are applicable to both tools. This means you need to have goal conversion tracking set up properly to ensure you are able to collect as much quality data as possible.
For example, if your goal is to increase Twitter followers and you have last click attribution set up, you may find that your results are misleading. You may witness a jump in Twitter followers but the credit for conversion is being assigned to their last click, which is on your website. This means that you can't prove the value of social media in your user journey, and you can't understand what role Twitter followers have in your marketing.
However, having the same goal but using a multi-channel attribution model and tracking the actions of your Twitter followers will give you a much better idea of how valuable this segment of your audience is to your brand.
Why is alignment important?
Marketers are under more pressure than ever to prove the return on investment (ROI) for their campaigns. This means that marketing needs to be based on data proving what is of the highest value - or potential value - to the brand. Without aligning your attribution and analytics goals, it's practically impossible to achieve this, as you'll only get half of the picture. You'll see a jump in traffic on your website but you'll have no idea what brought them there or if they'll go on to convert.
Creating goals and KPIs that are trackable in both tools gives marketers much more accurate insight into the performance of their brand and the impact of their latest campaign.