Google Analytics vs. Clicky Analytics

Google Analytics- What Is It Good For?

It is no surprise that Google Analytics (GA) receives a lot of buzz as one of the most popular web analytics tools. In fact, GA is often considered the industry standard, and the fact that it is a free tool is another large draw for users. To put user base into perspective, close to 75% of the top 100,000 websites use GA, as of a publication from July 2018 (Ringvee, 2018). Besides the fact that GA is offered as a free tool, there are multiple other reasons why marketers and businesses choose it for their web analytics measuring tool:

1.     Automatic collection of data

2.     You can create customization reports

3.     Easy integration with other tools and platforms

4.     Ability to measure internal site search

5.     To understand why visitors are bouncing off your website

6.     To know the age, gender, interest, device and location of your audience

7.     To understand which social platforms to target

8.     To understand what kind of content you should write

9.     To check if you are achieving goals (Thakur, 2017).

…But There Are Also Some Cons to the Google Analytics Platform

 Heavy users of GA tend to have a love/hate relationship with the tool, the “hate” portion coming primarily from the number of changes that Google roles out on a regular basis. To be fair, “hate” is likely too strong a term in this scenario, and the word “frustrating” would be better suited. GA users are forced to adjust to the changes, but change generally brings about some level of frustration for most.

In addition to these changes, GA has some terminology and “tainted” data that marketers must understand to fully utilize the platform. Analytics blogger Neil Patel labels these as GA “lies.” These “lies” include the following:

1.     “Dark traffic” on the rise- This can be thought of as hidden traffic. GA lists this as “direct traffic,” as it is too difficult to track every type of traffic source. As an example, Groupon discovered that as much as 60% of their direct traffic was actually organic traffic:

(Patel, 2018).

The solution? Utilizing UTM builders (which enable you to add code snippets to URL’s) or being sure to tag your links across social and email before they go live.

1.     Hidden social referral traffic- Since Google and Facebook, for example, track visitors in different ways, the data is not always accurate. This is an opportunity to use the Google URL builder to make sense of the data.

2.     Emphasis on vanity metrics- One primary example is visitors. The marketer/user must realize that a large monthly visitor rate is not necessarily a positive thing. Metrics such as exit rates and bounce rates must be analyzed as well.

3.     Misleading ghost spam links- What is ghost spam? Good question. Here’s a good infographic explaining the process:

(Patel, 2018).

            To help curb this issue, Bot Filtering can be turned on in GA.

4.     Positive A/B tests- False positives are common in these tests, and because 5 variations (instead of 2) must be tested for the best results, these tests take a lot of time for the tester. “If you let more people through the gate to your site, but they are lower-quality leads, then positive A/B tests won’t always tell the truth.”

5.     Too much emphasis on leads instead of sales- Closed sales are worth more than leads, and lifetime value (LTV) of a customer is even more important. Marketing analytics and sales teams must merge to create specific goals relating to sales over leads alone.

6.     False conversion costs- As an example, if a customer sees your ad online, they might not click on it right away. However, if they remember your brand and the specific offering, they might conduct a Google search at a later time based on the ad they saw prior. This will not get tracked as direct traffic, but it can be seen as direct traffic nonetheless. In order to alleviate this issue, you should consider factoring in the timing of a specific campaign into your conversion rates. This can help you understand whether the campaign led to the increase in sales.

7.     Last-touch attribution bias- “Last-touch attribution is when Google gives all the credit of any given conversion to the last touch point before the conversion” (Patel, 2018). In relation to sales, GA takes last-touch attribution into account, which is why multi-touch attribution must be analyzed when looking at conversion rates. Here’s a visual for last-touch attribution:

(Patel, 2018).

These “lies” are important to understand in order to make sure you are working around them to obtain the most accurate data possible. These “lies” do roll over to other web analytics platforms as well; GA is not the only

All of this being said, there are some other web analytics platforms that rival GA, even with taking the good and not-as-good aspects of GA into consideration. In this post, I’ll be discussing Clicky Analytics in particular, a well-reviewed web analytics platform.

 

Clicky Analytics- How It Compares to Google Analytics

To start, below are some features Clicky Analytics offers that GA does not:

1.     On-site heat maps- An example can be found below. These heat maps can also be segmented via split tests, which help Clicky users understand how visitors are clicking on various versions of landing pages. 

(Taplin, n.d.).

2.     Your favorite stats can be accessed through one button- Clicky users can post a short code on their site, giving them an icon to their favorite stats that only they can access by logging in and using their specific User ID.

3.     Real-time information about all of your visitors- This is self-explanatory. The difference here is that GA has about a 24-hour delay in most cases.

4.     A simple interface displaying the day’s stats- Compared to GA, the user interface is considered easier to use. Here’s a quick look at a typical dashboard:

(Taplin, n.d.).

5.     A better way of measuring bounce rate- Here’s the breakdown directly from the Clicky blog:

“A visitor who has only one pageview, and who is on your site for less than 30 seconds is what we now consider a bounce. So any visitor who has more than one pageview, or any visitor who has only one pageview but is on your site for at least 30 seconds, is now what we consider "engaged" / not a bounce.

Say you have a blog post that you have shared on a few social media networks like Facebook and Reddit, and you get 1000 visitors to it. Chances are that 95% of these visitors will only view the article that is being linked to - one pageview. Maybe half will read the whole article, half will read part of it, and a few will click through to your front page to see more. Any other analytics service would report a 95% bounce rate for these visitors. But a bounce is negative, so it makes it sound like only 5% of these visitors were engaged. But that's not true at all - half of them read the entire stinking article!” (Why Clicky’s new bounce rate is the best…, 2010).

6.     Video and Twitter analytics- Clicky measures things like when users hit pause and how long they watch a specific video, called “pause-seek monitoring”.

7.     Search rankings position for each visitor- This one is pretty self-explanatory as well. Here’s a look at what a ranking statistic would look like on Clicky:

(Taplin, n.d.).

8.     Live links- Again, this real-time offering is something that GA doesn’t offer.

In addition, Clicky is offered for free, but the Pro+ and Platinum packages, at a monthly cost, offer additional tools for subscribers. According to writers at Blogtyrant.com, Clicky Analytics is a great option for serious marketers serious about using web analytics to grow and expand their business.

Please leave a comment if you have any experience with Clicky Analytics! Let us know what you like and what you don’t like as much as compared to Google Analytics.

References

Patel, N. (2018, June 27). 8 Data Lies Google Analytics is Telling You (And How to Fix Each One). Retrieved November 11, 2018, from https://neilpatel.com/blog/google-analytics-lies/

Ringvee, S. (2018, July 30). Most common Google Analytics issues (in-depth overview). Retrieved November 11, 2018, from https://reflectivedata.com/common-google-analytics-issues-in-depth-overview/

Taplin, R. (n.d.). A Review of Clicky Analytics (and Why it Beats Google). Retrieved November 11, 2018, from https://www.blogtyrant.com/a-review-of-clicky-analytics-and-why-it-beats-google/

Thakur, D. (2017, July 20). 10 Good Reasons Why You Should Use Google Analytics. Retrieved November 11, 2018, from https://medium.com/@dineshsem/10-good-reasons-why-you-should-use-google-analytics-699f10194834

Why Clicky's new bounce rate is the best in the biz. (2010, April 26). Retrieved November 11, 2018, from https://clicky.com/blog/214/why-clickys-new-bounce-rate-is-the-best-in-the-biz