Unless data is high-quality, it’s useless. Even the data from Google Analytics can fail to meet quality standards, due to noise, irrelevancy or inaccuracy. For one thing, you need to bear in mind that spiders, bots, and crawlers are visiting your website along with real people, and this activity may all mixed be in with the data. Furthermore, you may be collecting unnecessary data or you may misunderstand what the data means or is telling you.
There are a few steps every website owner needs to take to filter out spam and junk. Only then can you feel sure that you are making the right decisions.
Determine the Purpose of Your Website
It is impossible to know what data you need if you are unsure about what role your website has in your business strategy. You should have a main goal and several secondary goals that support it. For instance, the main goal of your website could be to sell a product or receive a booking. The supporting goals could be downloads of premium content, signups for free trials, and subscriptions to your newsletter.
Before you go any further, define these goals. They will immediately show you if the data you have been collecting is useful.
Understand the Terminology of Google Analytics
Once you know what you want to measure, you still need to pick the right metrics. Make sure that you are clear on what various terms in Google Analytics mean. On the surface, some may seem similar whereas, in fact, they tell quite different stories — bounce rate and exit rate are prime examples.
By hovering over the “?” after the name of metrics in your reports, you’ll see a description. However, you may need to research further if you have any doubt about which would be most appropriate for your goals. For instance, it’s important to know which metrics are calculated according to unique users and which refer to sessions.
Run an Analytics Audit
The next stage is to ensure that Google Analytics is providing you with accurate data. Run an audit to search for errors and flaws by checking the following:
- Google Analytics version. Confirm that you are using the latest version.
- Analytics structure. It should be logical and free from redundant views.
- Basic metrics. Among other basics, check that you have set the right currency, timezone, default page, excluding parameters, and internal filters.
- Tracking code. Use a tool or check manually that tracking code is present on every page of your site. Also ensure that you have set up user ID, UTM, and cross-domain tracking and that there are no duplicates.
- Linked accounts. Ensure that you have listed all your Google Analytics accounts and that you have linked them to any AdWords and Search Console accounts.
- Enhanced link attribution. Check if this is turned on.
- Bot filtering. Turn on bot filtering to exclude hits from all known bots and spiders.
Before you add an implementation to your live website, test it in a staging environment. This will prevent mistakes that you may have never foreseen.
If you want to work with domain filters, you should set up a separate view for testing. This involves heading to “Filters” in the admin interface. Choose “Create New Filter” and give your filter a name. Choose “Custom,” select “Hostname” in the filter field, and input the filter pattern. Before proceeding further, wait at least one hour to ensure that the filter is active.
Use Google Analytics for Trends
Furthermore, if you have a large amount of data, identifying trends will be easier. If you have a new website and just a few visitors, however, you need to remember that apparent trends in limited data may actually be insignificant. Always make sure that you are considering enough data before you jump to any conclusions.
If you are just starting out, it’s fine to keep things simple. When you read about Google Analytics, you’ll see it has the potential to provide you with deep insights, allowing you to tweak every aspect of your website. Those with a long history online and large influx of visitors will want to use Google Analytics to its full extent. However, if you’re a small company and only just starting to become data-driven, you should begin by focusing on just the few metrics that matter and build up from there.