If you’re a digital marketer these days, odds are extremely good that web analytics is a major part of your toolkit. With its massive adoption in the market, odds are also good that the tool you’re using is Google Analytics.
But are you really getting everything you can out of it?
Here at Cardinal Path, we help our customers extract the most value they possibly can from data, and that means leveraging the most powerful, obscure, underutilized bells and whistles of Google Analytics’ standard and 360 products.
Here’s a checklist that can help ensure you’re taking advantage of the many value-added features within Google Analytics.
Enable and activate those core configurations and features!
We’ll start out with the basics. There are a lot of settings, configurations and core features to work through, but each of them can be used to help you clean up your data, make reports easier to use, and ultimately help you make data-driven decisions more efficiently.
Here are some commonly overlooked areas to take a closer look at in your account(s):
- Organize your account using the hierarchy of properties and views.
- Use data filter configurations to clean up your data or zero in on specific sets of data.
- Use URL parameter exclusions to avoid messy reports and page data duplication.
- Use annotations to document key changes in the data and the context for the reports you’re looking at.
- Put in place custom alerts to monitor data quality or quickly see anomalies.
- Schedule emails to automate getting the right data in front of the right people.
- Set up goals and funnels so you know what you’re analyzing and optimizing everything else against.
- If you still haven’t, set up Enhanced Ecommerce to gain insights into your product lists, cart/ checkout functionality, and a host of additional features.
- Dive into Cohort Analysis reports to see how long it takes visitors to convert and when to engage them with the optimal messaging.
- Tag all of your campaigns and channels so you can see exactly what’s driving visits and behaviors within those visits.
- Use MultiChannel Funnel, Model Comparison and Data Driven Attribution* reports to understand how your different campaigns are impacting the final conversions along the path to purchase.
Enabling Google integrations
Google Analytics is, of course, a Google product, and over the years, they’ve done a really good job of seamlessly integrating the tool across a host of other Google offerings.
Integrations like AdWords, DoubleClick (DCM, DBM, DFP)*, Google Search Console, BigQuery Export*, Google Play, and even Postbacks for sending deep-link conversions to non-Google ad networks are relatively straightforward ways to get a holistic look across a host of marketing activity.
Integrate with third-party platforms & tools
The reality is that your marketing technology landscape includes more than just Google, and integrations with third-party platforms and tools can help you do everything from bringing in pre-click cost data from other digital advertising channels to loading up your custom dimensions with CRM (customer relationship management)-driven customer attributes.
Integrating Google Analytics with CRM data bridges the gap between data sets that typically exist in silos, allowing you to see the pivot points between, say, someone’s website activity and their “offline” activity like phone calls or visits to a physical storefront — and how those actions play into a conversion.
With a Salesforce.com and Google Analytics integration, for example, you can draw insights from purchase behaviors over an entire lifetime and understand how your website contributes to the bottom line.
Use custom dimensions & metrics
This really comes down to getting analytics to work harder for your business. We’ve found that many organizations aren’t taking advantage of the ways in which Google Analytics can be customized to meet specific business needs.
Out-of-the box implementations are common, but customizing your implementation to capture more — and more meaningful — data can make it that much more actionable.
As an example, we’ve used third-party tools and custom dimensions in the financial sector to give us an idea, based on an IP address, of the company a visitor might be visiting from. No Personally Identifiable Information (PII) — we’re talking business and not personal banking here. We can then quickly determine if this visit represents a new prospect or an existing client — and if so, we can even identify what level of client they are.
By attaching this rich data to the actions and behaviors we’re tracking, the team is able to understand high-value vs. medium-value targets and test, optimize and personalize the website based on the relationship these visitors have with the bank.
Think of all the custom data you’d like to be able to use in your own analysis — inevitably, these insights will give you the ability to understand customers and prospects and more effectively market to them and grow your business.
Segments, audiences & activation!
Google Analytics has an exceptionally flexible, intuitive segmentation feature that allows you to quickly and easily home in on just about any logical combination or sequence of behaviors and attributes to define very specific customer segments. And while this can be extremely valuable from an analysis perspective, inside the Google environment, you can activate these audiences with just a few more clicks.
What’s that, you say? You found a segment that’s twice as likely to convert on a particular offer? Export that audience over to AdWords or DoubleClick* and fire up a campaign to target (or retarget) them! It’s really that easy.
And don’t forget those integrations: By applying machine learning, data science techniques and traditional statistical approaches, you can use your CRM data, Google Analytics data, and even third-party data (optional) to group your customers across various segments, allowing you to tap into a wealth of opportunities from within your customer data.
Google Analytics tracks more than just websites. If apps are part of your digital strategy, then make sure to take advantage of all the app-specific reports and features.
Specifically, we’ve found that a lot of organizations still aren’t fully leveraging the Google Analytics mobile software development kits (iOS and Android) to properly track marketing campaigns or installs from the Google Play or iTunes App Store.
Thoughtfully configuring your implementation to capture this information and having a proper campaign taxonomy in place to allow your analysts to make sense of the data generated can help improve the overall value that your mobile-focused campaigns drive for your business.
And if you’re able to identify the same user through logins or interactions across different devices and experiences, make sure to leverage the User ID feature that opens up Cross Device reports. This will help you understand how users traverse your digital footprint in their interactions with you and your brand.
Bridge the online/offline divide
The reality is that most organizations don’t live exclusively online. For those, it’s essential to make use of proxies for success offline, through digitally created metrics.
As an example, we work with one of the world’s largest corporations that conducts an enormous amount of business offline. With a swath of integrations, custom dimensions and custom metrics, we created a customized, multi-sourced, weighted engagement scoring model. Using statistical and data science techniques, we then correlate that model to offline data sets to quantify the impact of online to the offline world.
In another example, we use Google Analytics data to inform purchase intent data models that can be used to predict not only in-store sales, but specific predicted contributions of online actions to bottom-line value, segmented by product groups, geographies and more.
Go get the most out of your Google Analytics implementation!
Hopefully, these recommendations will help you identify more ways to take advantage of all that Google Analytics has to offer and inspire some new plans for getting the most out of your investment in data and the tools that help drive value from it.