Here are the top 5 reasons to upgrade from your free analytics vendor to an enterprise for-pay model. Note that we are not distinguishing between Google Analytics Premium and Adobe Analytics (more on that here), or between Webtrends, Localytics, MixPanel, etc.—that’s a whole other conversation.
1. Sampling has become a problem.
One of the ways that vendors keep their platforms free is by limiting the data quality to show only a statistically significant portion of traffic in your reports. This is a well-known issue and a very common scenario with Google’s free analytics platform. It’s important to remember that sampled data is still very actionable—the trends shown in free GA are accurate and will show the true direction of your data, even when it’s sampled! But the more filters you apply to a profile and the more segments you apply to a report within that profile, the more your data will be skewed. All web analytics platforms provide several ways to slice and dice your data to answer a question; if you find that your colleagues are slicing data differently than you are then you’ll probably end up with different answers in a sampled platform. When you find that you’re spending more time arguing over which way to skin your cat than you are deciding what to do with it, it may be time to look into an enterprise platform.
If you’re looking to integrate your data outside of your web analytics tool at the cookie/visitor ID level, you’ll need to access your raw, unassembled data through a for-pay platform. If you foresee the need for a well-integrated business intelligence or data warehouse platform, enterprise platforms are the way to go.
2. Cardinality is of importance.
I’d say this is related to sampling, but it’s different enough that it has earned its own section—here’s why. We’re currently working with an enormous global brand here at Search Discovery that has over 6.5 million unique product IDs and growing. At any given time an analyst may need to report on the most trafficked product ID or the least trafficked one. Free analytics platforms generally have a limit on the number of unique dimensional values that can be displayed in a report. Even paid platforms may institute a limit in their web-based reporting engine! The brilliant thing about a paid platform is that you’ll have access to the raw, unsampled data via the vendor’s data warehouse or API. When our client, an Adobe Analytics user, needs to report on a very important product that gets very limited traffic, they can always fallback to Adobe’s Data Warehouse product. In addition, they have the ability to request increased cardinality for certain reports so they can see all 6.5 million IDs in the web-based reporting engine. If you’re dealing with limited access to your most important yet casually visited values, it may be time to look into an enterprise platform.
The brilliant thing about a paid platform is that you’ll have access to the raw, unsampled data via the vendor’s data warehouse or API. When our client, an Adobe Analytics user, needs to report on a very important product that gets very limited traffic, they can always fallback to Adobe’s Data Warehouse product. In addition, they have the ability to request increased cardinality for certain reports so they can see all 6.5 million IDs in the web-based reporting engine. If you’re dealing with limited access to your most important yet casually visited values, it may be time to look into an enterprise platform.
3. Integration with other platforms has become a focus.
There comes a time in an organization’s analytics maturity when integration becomes a focus for their data. Integrating with display media, paid search, SEO, email service providers, testing and optimization platforms, personalization platforms, offline data systems, and CRMs are often keys to increasing your analytics agility and actionability. Many free platforms offer little to no integrations. Enterprise platforms generally provide prebuilt connections with the most-used platforms that you’ll want to integrate with: DoubleClick, AdWords, BrightEdge, CheetahMail, Optimizely, Target, Salesforce, and more. Integrating these platforms will allow you to slice your data based on many new dimensions and get you closer to that goal of a 360-degree view of your customer base. Most enterprise platforms include an option for importing custom data too! Adobe Analytics uses a system called Data Sources whereas Google Analytics uses Custom Dimensions and Measures for data import. Just make sure to factor this into your platform costs while investigating a jump to a for-pay platform!
4. Data governance is key.
As unsexy a word as it is, data governance is a hugely important factor for the larger organizations with which we work. Several of Search Discovery’s clients have hundreds of brands in dozens of countries with a multitude of ad agencies, offices, and end-users of their analytics data. Keeping this data consistent, accessible, and properly managed can turn into a scenario where you’re trying to herd cats—it just cannot be done. Most free platforms do not grant user-based permissions at the granularity that these types of organizations require. For example, a current SDI client utilizes a centrally managed digital analytics model—one group that owns every data-related marketing system across the entire massive company. This would be much more than a difficult undertaking with several free platforms, it’d be virtually impossible! Enterprise platforms also provide administrators with the ability to ‘login as’ a user to see what the experience will be like for that user to ensure proper access rights.
I’m reminded of a client from my days as a Business Analyst at an agency in Philadelphia which granted my personal Gmail access to their Google Analytics platform as an admin. Almost a decade later I still have this admin access today. Don’t let this happen to you! Use an enterprise platform to ensure logins for third-party agencies have an expiration date.
But data governance is more than just user management, some enterprise platforms allow you to lock down custom dimensions, metrics, and segments. This grants global users confidence that data viewed for one brand within the organization will have the same meaning as the next brand. Try doing that with a platform that doesn’t allow you to globally apply data filters!
Finally, what happens when your CMO asks, “How is our organization using the data that we send to our analytics platform?” Hopefully this is on your CMO’s mind already. Most free analytics platforms don’t have the ability to internally report on its users. What reports are used most? What users are using the platforms extended capabilities? An enterprise platform should enable you to answer these questions and more—which will help further prove the ROI of your platform.
5. Custom dimensions and metric limitations.
Here’s a tough question for you—what can you do if you’ve reached the limit of custom dimensions that you pass into your platform? Give up? The answer is not much. You can always try to squeeze more data into a single dimension via concatenation, but at some point, you’ll outgrow this method too. And how about custom metrics? If you’re squeezing more than one metric into single variable you are living dangerously. If these issues are common during your implementation process, it may be time to consider implementing an enterprise platform that can handle your organization’s size.
There are hundreds more reasons that clients decide to pay for an analytics platform. What others has your organization used to prove the case for an upgrade?