Finding Your Website's Pain Points

Before you can begin the testing and optimization process you must first identify pain points or areas of opportunity. This essentially comes down to three critical steps:

1. Providing clean data

2. Translating that data into valuable insights

3. Analyzing the data for opportunities.

 

Start with Clean Data

The first step towards identifying opportunities in your site is to first make sure the data you’re getting in is sterile, validated, and accurate. This data provides the foundation off of which you’ll be identifying opportunities, analyzing the user experience, and building test cases so it is imperative that the data be accurate.

 

Track Every Critical User Interaction

Every step of the user experience should be tracked in analytics. In addition to basic category, product, cart and checkout pageviews, other common tasks also need to be tracked. Analytics debuggers are available in the form of browser extensions and can be helpful in ensuring everything is tracking properly. Is site search being tracked? Filtering and narrowing options for search results pages should also be tracked.

Google Analytics Debugger Extension for Chrome
Google Analytics Debugger Extension for Chrome

Once the “normal” functions throughout the site are being tracked, it’s time to take a deeper look and ensure all other important events are being tracked. These are often overlooked but can be crucial in understanding the user experience. These additional areas often include things such as:

  • Option selection
  • Error dialogues
  • Important links
  • Videos
  • Email signup
  • And more… every site is different
Filter Out Bot And Internal Traffic

A typical retail site will see a large amount of traffic from internal IP addresses such as company headquarters and customer service departments. Since internal users do not behave the way a “normal” user would, it is important to create a second profile within Google Analytics and begin filtering this traffic out in order to harvest more accurate data that is representative of a “real” user experience.

It is wise to create a second profile to add filtering to, maintaining a raw, unfiltered profile. Down the road if you start to notice inconsistencies or a spike/drop in key metrics, this will provide a baseline of unfiltered data to compare with. Note that filters are not retroactive, so it is good practice to implement these early on in the process and begin collecting clean data as soon as possible.

If you need expert help regarding data management then visit https://www.radiusbridge.com/it-management/.

 

Create filters within the admin panel of Google Analytics
Create filters within the admin panel of Google Analytics

Seek Out Anomalies And Inconsistencies

Now that all critical user interactions are being tracked and unqualified data is being filtered out, the last step in verifying clean data is to do a final check through analytics to ensure that there are no more outliers or conspicuous traffic sources tainting your data.

A combination of several simple reports available within Google Analytics will allow you to single out major offenders. After identifying these, they can be filtered out using profile filters as described above. Some things to watch for:

  • Large amounts of traffic from unknown browser types, i.e. Internet Explorer version 99.9
  • Unusually high traffic from very specific geographic areas
  • Specific traffic with extremely low, or extremely high eCommerce conversion rate
  • Specific traffic with extremely low, or extremely high bounce rate
High levels of concentrated traffic with 0% conversion rate is one example of in indication of automated traffic
High levels of concentrated traffic with 0% conversion rate is one example of in indication of automated traffic

Get the Most Out of Your Data

Now that you know you’re getting clean and accurate data, it’s time to take that data and do some actionable reporting. This means taking simple data points and using them to calculate additional pieces of data that will provide further insight into the user experience.

Segmentation Around Progression

For the typical retail site, the customer experience revolves around the product page. It is where the most critical evaluation is done, and where the initial decision to begin the conversion funnel is first made. Based around the product page, the key progression points of a typical retail website are as follows:

  1. Home/Category ? Sub-category
  2. Sub-category ? Product
  3. Product ? Cart
  4. Cart ? Checkout
  5. Checkout ? Transaction

Create segments within analytics to accurately measure these key progression points. Google Analytics features a new segmentation feature that allows not only condition based segmentation, but also sequential segments, allowing us to garner even more accurate data.

Creating a sequential segment within Google Analytics
Creating a sequential segment within Google Analytics

 

Identify Trends And Opportunities

Now that the data has been expanded and improved, it’s time to take that data and conduct further analysis. In addition to pulling simple reports from analytics, it’s a good exercise to generate custom reports of your own that fit your business processes. This will make the data itself more easily digestible for stakeholders, as well as allow you to quickly identify areas of opportunity.

Breakdown KPIs and Critical Data

In addition to analyzing progression points, it can be helpful to make use of several simple reports within analytics to provide an overview of the user experience. This will help identify other potential pain points or testing opportunities. Things to look for include specific pages with high traffic but high bounce rate or particular types of visitors that are having a poor experience. Does mobile traffic see an exceptionally high bounce rate? Are IE users struggling to complete the sales process?

Some things to look for:

  • Mobile performance
  • Smartphone
  • Tablet
  • Top landing pages
  • Geographic info
  • Top traffic sources
Breakdown of traffic into various segments and demographics can help identify testing opportunities
Breakdown of traffic into various segments and demographics can help identify testing opportunities

Progression Rates and Trend Reports

Using the segments created above, it is possible to create comprehensive data displaying the full picture of how the site has been performing in key areas. It can be especially helpful to create something similar to a 30-60-90 day trend report, offering not only current performance, but to identify positive or negative trends. These types of reports will not only assist your analysis team in identifying opportunities, but can be leveraged later in building a strong case to begin the testing process.

In this example, the product page progression rate of only ~5% presents a strong case for testing
In this example, the product page progression rate of only ~5% presents a strong case for testing

Analyze Data for Opportunity

Once you have all the data in front of you, you’re able to see the entire picture, essentially a broad snapshot of the current user experience.

Using this data, we can identify pain points, what’s performing well, as well as areas of improvement. Where are users falling out of the process? What parts of the site are users struggling with? Is there functionality on the site that users are not taking advantage of? These are all areas that may present a strong case for testing and growth.