The basic pursuit of all scientific works have been to “quantify” the man’s concerns. From temperature to weight, technology aids us in understanding the “how much” in precise details, instead of guessing and using ambiguous terms such as “big” or “small”. In context to digital marketing, where enormous amount of available and accessible data remains open to rigorous analysis, Google Analytics plays a key role in estimating the key results and also in extracting insights to formulate strategies. While Google Analytics is one of the best web analytics tools, it is not as perfect as many of us assume. Let us look at some of the common issues this tool has, and we shall learn how to fix them up to suit our requirements.
How to check for JavaScript “Tag.”
How does Google Analytics works? We know that by embedding a JavaScript “tag” into your page codes, Google Analytics can calculate and analyze your page records. That means, if there is no tag on a particular page or website, Google Analytics can no longer extract any information regarding it. In case we have a less number of pages on the website, say 5 or 6, manually checking whether the script (tag) is present or not is easy. But imagine you have a website containing more than 500 pages! It is going to consume a lot of your time and energy if you go on searching for the code on each page.
Solution: – There are many tools available to check if your pages are properly tagged or not. Apart from the common method, provided by Google itself, you can also use Screaming Frog SEO Spider for this purpose. A tiny program as it is, you can get it installed on your computer to check for images, CSS, scripts, etc. Frog allows you to view, analyze and filter the crawl data as it’s gathered and updated continuously in the program’s user interface.
Goal evaluation
Suppose you have some call to action buttons on various pages of your website. Now, you will need to track down all the user activities for such button. Or for any other section of the website for that matter, whether a form submission or a Subscribing to a newsletter, etc.
How can you achieve this? You can set up Goals to estimate and record those activities and also analyze the device specifications, location and source of the traffic. In case you wish to be more particular, you may like to assign some monetary value to each of your set goals so that you can get an idea of ROI optimization.
Most of the goals have many intermediate steps, like filling the form, etc. To get more details on each page, and to analyze user’s activities on each intermediary step, you can use Funnel Visualization tool as well. This will help you examine all the possible leak outs and will provide you insights into how to make the website’s user experience better.
Sampling errors
In most of data analysis, sampling plays a major role in determining the quality and precision of extracted insights. Selecting a subset of the given set of data, statisticians can estimate the qualities of the whole population. While this may seem a tricky method, it can indeed be very helpful when dealing with a very large volume of data. Using careful sampling, by statistical theory and probability theory, one can find the characteristics properties of the whole set by spending less time and effort.
The default sample in Google Analytics has a cardinal value of 25000 visits. However, one can anytime make the sample more concise by altering the slider ( situated on the top right of the page). Though results based on sampled data are not accurate numbers, they give meaningful reports about your page view or bounce rates, etc. However, there is a problem.
After a certain value, the numbers occur to repeat time and again. Like it can read the same value for different campaigns, thus rendering the reports inaccuracy and inconsistency.
Solutions:-
A)Modifying Data range
Change the period, from yearly basis to monthly basis. It helps you get a more in-depth idea about a shorter span of time so that you can analyze your reports more specifically and with a higher precision. Later you may copy the data in a spreadsheet, and store it for future references.
b)Set the Number of site tracking
You can cut down the traffic volume in a particular property. Then you will be able to avoid the data reaching the peak whereafter inconsistencies arrive. That is to say, if you have some 40 websites having 80K visits per unit time, Google Analytics will create a sampled data report. So if you want a report from an unsampled data, you only need to fragment the 40 websites so that the data gets divided, and you get analyzed reports for each website separately.
Fishy Bounce Rates
Bounce rates are good measures of your site’s relevancy. A low bounce rate indicates that your landing page is relevant and useful to user’s search query. Whether a user stays on your page for long or just goes away can be a hint about where you need to improve your website for a better user experience (UX). Bounce rates vary from site to site but a typically low bounce rate, shrinking to a single digit value, can mean something is wrong.
Solution: – For some reasons, your GA report can show erroneous figures about bounce rates. It is also related to multiple instances of the same code. You can add multiple instances of the code (analytics.js) to the website but then you also have to change the snippet for each distinct property that you want to view the data.
Results from other property show up in different data cluster
Having multiple accounts, or a single account with many properties in the same GA account can result in the messy representation of results. It is also likely that you might have copied the code from the undesired “property”.
Solution:- You will have to log in and then proceed Admin-> Account-> Property-> Tracking Info-> Tracking code. View the code snippet and tally if it is the same as you installed on your website. If not, then you might consider making the changes to get the issue fixed.
On to a more precise and concrete analysis
Now that we have covered some of the major issues pertaining to Google Analytics, one can hope to get a more accurate and relevant report about the websites. While data clusters may suffer from inconsistency at times, one needs to handle the situation intelligently and should try to employ the solutions, mentioned above, to find data reports useful in deriving actionable insights.
