If you’re using analytics data to measure performance or make a business case, you must be sure you can depend on it. An audit is often the first step to ensuring accuracy and maximizing the benefits of your analytics tools.
Two situations commonly call for an audit: Your data will tell you, or your business will call for it.
Signs in Your Data
You might have observed some of these issues that signal the need for an audit:
- Key metrics appear inaccurate or are not counting anything at all
- Key metrics differ significantly between your analytics, ad tools, CRM or eCommerce systems
- You observe significant traffic fluctuations that are unaccounted for
- Marketing reports appear to be missing traffic from significant sources, or traffic appears to be incorrectly bucketed
- You have “referrals” from your own domains
- Your transaction data doesn’t match between your analytics tool and your database
- Content reports contain pages that don’t belong or multiple versions of the same page
Or, that you are unable to answer basic questions like:
- What is the true impact of my marketing efforts?
- What elements are users engaging with on this page?
- What is my conversion rate among non-members?
- What percentage of my users are returning members
- Where are users falling out in my conversion funnel?
- Where are users going when they exit my site?
Signs in Your Business
Shifting business conditions are also optimal times to conduct an audit.
When upgrading your analytics product. For example, you’re preparing to upgrade from Google Analytics FREE to Analytics 360. Audit your implementation to ensure you are able to maximize the value of your analytics investment.
When you relaunch your site or app. You may choose to audit and fix your analytics before a relaunch in order to get a baseline for comparison. A relaunch is an ideal time to ensure your analytics tools are implemented optimally.
When key staff has turned over. Losing the person in charge of your analytics implementation can be hard, but it’s a great time to audit the implementation and make sure you can trust the data and can answer important business questions.
When starting a testing program. Before starting split-testing it’s important you can make data-driven hypotheses and then measure and test performance accurately.
When you are about to ramp up ad spend. Before increasing spend, you’ll need to be sure that key conversions are tracked and attributed correctly.
An analytics audit is meant to identify problems, not solve them; it’s a first step, never a last step. An audit seeks to identify any shortcomings of an analytics implementation. It answers key questions: Is our data reliable? If not, why? And are we taking full advantage of the tools available to us? The end goal is to identify and then implement fixes that will ensure the accuracy of data and enable more strategic use of analytics tool features. You can’t fix what you don’t know is wrong. A comprehensive analytics audit is the diagnosis that reveals a recommended treatment.
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