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How To Use Data Analytics To Get Customer Insights and Improve Performance

Gillian Mays
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The importance of data in running a website is no secret. The more you understand your performance, the easier it is to optimize it. However, recognizing the value of data doesn’t always translate into effectively leveraging it.

That’s where this article comes in. We’ll give you an overview of using data analysis to achieve tangible improvements in site performance and customer satisfaction in two phases: understanding, then applying. Let’s dive right in.

Section titled Phase I: Understanding data analysis

Accurate analytics form a direct path to your success. That’s because it’s not generalized information or one-size-fits-all advice. It’s a data-based strategy that takes your unique goals and needs into account.

Let’s start with the basics.

Section titled Types of data

There are four main types of data analysis techniques:

Descriptive analyticsUnderstanding past performance to inform decisions. This helps you track trends, update KPI performance, and identify areas of improvement.A retail business reviews their sales data from last year to identify the top-selling products so they can more efficiently plan inventory management and marketing campaigns for this year.
Diagnostic analyticsIdentifying why events occurred by examining historical data and relationships between variables. This allows for deeper analysis that can often uncover root causes of positive or negative outcomes.A software company sees a decline in customer satisfaction metrics. They analyze their customer support tickets, product usage, and customer feedback alongside those metrics. This allows them to fix underlying issues.
Predictive analyticsUsing algorithms and machine learning to analyze historical data and make predictions. This helps forecast what is likely to happen.An eCommerce company uses technology to forecast customer demand during the holiday season based on previous purchases and external factors. This helps them optimize inventory levels, pricing strategies, and marketing plans.
Prescriptive analyticsNot only predicting future outcomes but also recommending actions to achieve them and avoid negative ones. This leverages optimization and simulation techniques to ID the best course of action based on available data and goals.A retail business uses prescriptive analytics to determine the best pricing strategy for their products in real-time. By analyzing factors such as demand, competitor pricing, seasonality, and customer behavior, algorithms can recommend optimal price adjustments to maximize revenue and profit margins.

Descriptive and diagnostic analytics can usually be used by applying a basic data collection tool and performing manual analysis. However, for techniques like predictive and prescriptive analytics, you may need to leverage a more sophisticated collection tool or even a data analysis service.

Using a more technological approach can give you more insights, but it may also be more expensive or time-consuming. If you’re new to data analysis, start simple. Even basic, manual data analysis can reveal insights capable of greatly improving your performance.


All of the above are examples of passive data analytics. You can also take advantage of active data collection to supplement your data set. This includes things like customer surveys and feedback forms.

Section titled Choosing a data collection tool

The next step is to collect your site’s core data. There are countless services to choose from. When making your choice, be sure to weigh aspects such as budget, usability, and user reviews.

Using free trials or personalized demos can also help you get an idea of options that are a good fit. Google Analytics is a good place to start for many users thanks to its reputation as an industry giant and its beginner resources.

A person with dark hair and a blue shirt sits at a desk and looks at a laptop, while an info panel on the left side of the screen reads "Get essential customer insights".

The homepage for Google Analytics

After you’ve set up your data collection tools, there may be a waiting period as the program collects your data. For example, Google Analytics starts collecting information as soon as you implement it. You can see real-time reports almost immediately, but they might not be the most reliable since they're not based on a large set of data.

The more data you have, the more accurate your insights will be. You can start collecting information for basic analysis with about a week’s worth of data. However, for more accurate insights, it’ll take anywhere from 1-3 months.


Comprehensive results that can best inform long-term trends take anywhere from 6-12 months to collect – so the sooner you can set up an analytics tool, the better.

Section titled Phase II: Leveraging data analysis

For both customer insights and site performance, utilizing the data you’ve collected relies on the same basic three steps: understand, optimize, and monitor. Let’s break that down for each area.

Section titled For customer insights

Section titled Step 1: Understand

After you’ve used your data collection tool of choice, it’s time to break it down and understand it. Start with some of the more important metrics.

  • Website visits: Website visit data can show you where your traffic is coming from. Direct, referral, organic, paid search, social – all these different types of traffic tell you something about how your brand is performing. Differentiating between types is a smart way to assess the performance of multiple marketing strategies. Website visit data can also tell you more about your visitor demographics, including location, device type, and how many are returning customers. This is all core data to better understand who your site is reaching – and who it isn’t.
  • Clicks and interactions: Users will interact with the parts of your website that they find most interesting. This alone is an important metric showing where and how people engage with your brand, but you can also dig even deeper. For example, clicks can show you navigation pathways. This reveals what typical path a user takes when visiting your site. It can even show potential navigation issues. You can also look at the specific engagement metrics and Click-Through Rates (CTRs) for targeted data. This shows how effective the links, buttons, and ads on your site are.
  • Browsing patterns: This includes time spent on your site overall as well as individual page views. Session duration shows how long people spend on your site, which can reflect how engaging your content is for your audience. Bounce rates can show how many users leave your site after only viewing one page. This can help indicate if there’s an issue with the user experience or even site performance.

When you have an understanding of these metrics, you should also have a good idea of where you can improve. It should reveal pages that aren’t getting enough traffic, highlight popular pathways, and show what your customers really want from you.

Section titled Step 2: Optimize

Armed with that information, you can start making changes. This may include eliminating no-traffic pages, investing in ones with high CTRs, revamping your navigation – whatever your data says your customers like most.

Another way to optimize is by segmenting your audiences. Segmentation is dividing your customers into groups based on their demographics and behaviors on your website. This helps you target audiences more effectively.

For example, imagine the data shows that shoppers on mobile tend to buy your products in bulk, especially after spending a lot of time navigating through a certain path. You might decide to optimize that content path to mobile shoppers and offer better bundle deals than those on desktop. Since this demographic is most likely to use that navigation, you’re doubling down on something that already works.

By using data like this, you’re making evidence-supported changes and rolling them out to the specific audience they were designed for. This can lead to a more efficient use of your time and resources.

Section titled Step 3: Monitor

Customer insights will evolve as your audience does. Make sure to keep your eye on how the data evolves so you can make timely, informed decisions that cater to them.

Let’s say you have content about a product type that is underperforming. You can try different content formats or topics to see if it improves. However, if adjusting the content type continuously still doesn’t yield any results, the problem might lie with the product itself. This can inform your product development team and help you make an overall better-selling result.


Custom analytics are a great jumping-off point, but they're only one piece of a successful strategy. Make sure to leave some room for trial and error.

Section titled For improving site performance

Section titled Step 1: Understand

As a basic rule of thumb, customers will avoid pages with poor performance. This includes those that load slowly or display content irregularly. Here are some key aspects to look out for that could indicate this problem.

  • Bounce rate: While a high bounce rate can reflect content issues as discussed above, it might be due to load times as well. The only way to tell will be to check for yourself and see what changes make the most difference. Similarly, low average session duration could point towards the same issue.
  • Exit rates on key pages: With areas like product and checkout pages, minimizing exit rates is essential. If you’re seeing high exit rates on these low-content pages, it most likely indicates a performance problem. This could be poor design or slow loading times. Cart abandonment rates can also indicate payment errors or compatibility issues at the most crucial point of the purchase.
  • Poor mobile performance: Measure your key metrics specifically for mobile users. Many users will access your site from their mobile devices, and if they run into issues they wouldn’t normally on desktop, it’s still going to be frustrating and hurt your bottom line. In a mobile-first world, these issues need to be treated with just as much attention as the desktop site.

If you want to zero in on a page’s load times, try PageSpeed Insights. This allows you to view your load time among other metrics. It also breaks it down to mobile vs desktop, too.

Section titled Step 2: Optimize

Once you have those stats collected, find where you can improve. A good place to start is with slow loading times. Audiences today have very low patience for them. The sooner you can present your content, the more likely they are to see it.

Prioritizing the purchase pages (products, shopping cart, checkout) is also a good idea. Minimize your images, use caching, and do away with needless features or code that could be slowing it down. This all reduces the friction between your customers and their purchases.

Section titled Step 3: Monitor

As with customer insights, you should keep monitoring your site performance. Technologies can evolve and change, which may also alter your site performance. It’s also a good precaution to track metrics whenever you make big site changes to make sure you’re heading in the right direction.


It’s also important to track if the performance improvements you make actually have an impact. Some issues can be solved with minor changes, but if you see a trend of performance issues and those adjustments aren’t cutting it, it may be time to rethink your tech stack.

Section titled Conclusion

Most everyone understands the importance of data. Nevertheless, the true challenge lies in navigating your site's unique results to arrive at the ideal outcome. By optimizing your data collection methods and strategically applying the insights gained, you can significantly improve your site's performance and better serve your customers.