Top 12 Website Metrics to Track for Online Businesses

Last Modified on January 16, 2025

Website metrics help us track the performance of what we are trying to achieve through our website or app. But with many of them available, things can get confusing quickly.

It also depends on the type of website or business you’re running, so not every metric is relevant to you.

So, focus on the metrics that make a difference to your business. Many of us often make a mistake when starting as we want to ‘measure it all.’

In this blog post, we’ll discuss the top 12 website metrics to track, with the following categories:

• Generic Website Metrics
• Content Metrics
• eCommerce Metrics
• SaaS Metrics

We’ll also examine why they should be measured, how we can optimize them, any limitations, and some tools available to monitor them. Let’s get started!

Generic Website Metrics

These metrics should be looked at to measure the performance of your website regardless of what category or industry you operate it in:

1. Conversion Rate
2. Bounce Rate
3. Average Session Duration
4. Total and Unique Visitors
5. Funnel Completion Rate
6. New vs Returning Users

Let’s dive into each one of them.

1. Conversion Rate

Conversion rate measures the rate of website visitors who complete a desired action, such as making a purchase, filling out a lead form, or subscribing to a service.

The conversion rate aka CR is measured with the following formula:

CR = (Number of conversions / Total visitors) * 100

Considering these actions are generally why your website exists, tracking conversion rate helps to understand how well your site achieves your business goals, e.g., sales or lead generation. 

Optimization

There’s a whole industry of conversion rate optimization (CRO) that focuses on improving this metric with the help of the following techniques:

• AB testing
• Quantitative research
• Qualitative research (surveys, interviews, user testing, exit polls, heuristics analysis, and so on)

Most of these research methods are focused on understanding the user behavior and the motivations behind their actions.

Limitations

Metrics don’t show the ‘whys’ and ‘hows’ which also extends to conversion rate. So, while you can see what your CR is like, you need deeper studies like the ones in the CRO industry to understand user motivation or lack thereof.

Tools

Since it’s an important metric, it’s available in most analytics tools, e.g., Google Analytics 4, Piwik Pro, Mixpanel, etc. Where it’s unavailable, you can calculate from external tools like Sheets or Looker Studio based on the formula provided.

It’s important to remember that the formula above talks about visitors so it’s a visitor conversion rate. If you’re looking at the conversion rate for traffic sessions, your formula will look like this:

CR = (Number of conversions / Total sessions) * 100

Based on what type of conversion rate you’re looking for, you’d replace that in the denominator.

Analysis Tips

Below are a few things to keep in mind when analyzing conversion rates:

• Analyze how different traffic sources perform when converting users, e.g., organic vs paid.
• Look at the device type that’s converting more or worse. It could be that the mobile site isn’t as optimized as the desktop, yet most of your traffic is coming to mobile.
• Monitor trends based on time. For example, you just did a full redesign but the CR has dropped, while the same period last year performed well. This could indicate issues with your design and should trigger further investigation.
• If your landing pages are getting high traffic but their conversion rate is low, there might be some friction or it could indicate other issues like the low-quality traffic or the content is not quite relevant for the users based on what they saw in your ad, social media post, or email.

These should help you when you’re starting, but they are not the only tips when analyzing conversion rates.

2. Bounce Rate

Generally, bounce rate refers to the percentage of users who leave the page without engaging, or leaving the website after a specific period, e.g., 5 seconds. The formula is as follows:

Bounce rate = (Total users to a page who left the site without interaction / Total visitors) * 100

However, the exact definition of bounce rate and its calculation can differfrom tool to tool. For instance, in GA4 a bounce rate is based on the following formula:

Bounce rate (GA4) = (Non-engaged sessions / Total sessions) * 100

Non-engaged sessions are defined by the following criteria when the user:

• Stayed on the page for less than 10 seconds
• Did not trigger any conversion event
• Did not move to any other page on the site

Therefore, it’s important to keep these nuances in mind when looking at certain website metrics depending on the tool you’re using.

The bounce rate can be a valid indicator if the page content or messaging is good enough to keep users engaged. A low bounce rate would mean users engaging with the page and in general exploring more of your site.

Optimization

Some ways to optimize this metric are:

• Improving the page load speed.
• Ensuring the page content is relevant for the users.
• Using good internal linking to send users to other pages.

Limitations

High bounce rates are not always bad, especially in the case of single-page websites. So, it also requires qualitative further investigation.

Tools

Bounce rate is another popular metric available in most mainstream tools like: GA4, Matomo, Clarity, etc.

Analysis Tips

Here are some tips for analyzing bounce rate:

• Analyze bounce rate by page type, e.g., landing pages and blog pages often have higher bounce rates, but that doesn’t always mean it’s terrible. But if it’s a product page with over 70% bounce rate, that’s an issue.
• Pair it with other metrics like average session duration. A high bounce rate and short average session duration might indicate that the content is not appealing to visitors.
• If your website/industry has a long sales cycle, then that means users can take longer to engage. In this case, if your analytics tool allows you to increase the engaged session duration, then you can do that. GA4 allows you to do that, for instance.

3. Average Session Duration

As the name says it’s the average time people spend on your site during a session. It’s defined by the following formula:

Average Session Duration = Total duration of all sessions/Total sessions

But as with the bounce rate, how it’s defined can change depending on the tool you’re using. For instance, GA4’s formula is as follows:

Average Session Duration (GA4) = Total duration of engaged sessions / Total sessions

It can help to understand user engagement and if the quality of content and/or site navigation is good enough. Longer average session duration can mean that people find value in your content.

Optimization

Here are some optimization tips:

• Create high-quality, engaging content.
• Where relevant use other forms of media, i.e., videos, graphics, etc.
• Simplify navigation to make it easier for users to explore the site.

Limitations

While longer average session duration can mean people are engaging with content, it might also be due to the complexity of the product or service you’re providing.

Moreover, the metric doesn’t take into account what page most of the time is being spent on.

Analysis Tips

Here are some tips for analyzing average session duration:

• Combine with other engagement metrics like scroll depth. Otherwise, it might simply mean idle time.
• Look at the data on the page or content type. For example, blogs, webinars, etc. will have longer durations vs product pages.
• Try co-relating with other metrics like conversions because if users spend a long time on your site, it should ideally lead to purchases, signups, etc. For instance, if your average session duration increases after adding specific content but has no effect on the conversions, then you can re-evaluate the messaging.

4. Total and Unique Visitors

Total visitors are simply the total number of visitors or users who visit your site in a given period (including new and returning users).

It’s important to remember that when you’re looking at total visitors, it can count the same user multiple times if they visit your site frequently.

Unique visitors are based on cookies that collect client or user IDs that identify each user and do not count the same user more than once.

It’s beneficial to know your total visitors to understand your site’s reach, whereas unique visitors show true audience growth.

Optimization 

• Create engaging content to encourage repeat visits.
• Your SEO efforts can also help bring in both new and repeat users.

Limitations

While high visitor numbers signal traffic growth, it doesn’t guarantee engagement or conversions. Also, if a user deletes their cookies or uses different devices, it might not be a truly unique visitor.

Tools

Almost all tools include these metrics.

Analysis Tips

Here are some tips when analyzing visitors:

• When launching any new campaigns or updates to your site, it’s a good idea to keep an eye out for any dips or spikes.
• Combine this with other engagement metrics to get more context. For instance, a high number of visitors but low engagement or conversions could mean low-quality traffic.

5. Funnel Completion Rate

This is the percentage of users who complete defined steps, e.g., e-commerce funnels with these steps: Viewed product → Added to cart → Checkout → Purchase.

There are two types of completion rates we can look at, so the formula could vary as follows:

Funnel step completion rate: Users in the current step / Users in the last step * 100
Funnel completion rate: Users in the last step / Users in the first step * 100

The first one is more common and helpful to understand the user behavior in a funnel so those ‘steps’ could be optimized.

For instance, 15,702 users viewed the product and 3,718 added to the cart, which means 23.7% of users completed that step.

The remaining 76.3% of users are those who abandoned the product page, aka abandonment rate.

Optimization 

Here are some optimization strategies:

• Deal with bottlenecks by simplifying the steps and addressing any concerns users might have.
• Use progress indicators to encourage completion, e.g., 70% completed.
• Optimize CTAs for the steps to encourage users to complete steps.

Limitations

Funnels are as good as the tracking is for each step. So, if it breaks anywhere in between, the remaining steps might not have accurate data.

Tools

Most analytics tools have funnel reporting built into them, such as Google Analytics 4, Mixpanel, Piwik Pro, etc.

Analysis Tips

Here are some tips to analyze funnels:

• Find out the steps where the completion rates are low and do qualitative research on what could be causing the drop-off.
• Analyze traffic based on their source. For instance, how does paid vs organic traffic behave in a funnel?
• Compare your funnels after a new campaign or any update to the funnel steps.

6. New vs Returning Users

Generally, they are available as an absolute count, so you look at new vs. returning users. But in some tools, you might find them as percentages in which case the following formulas are used:

New Users % = (New Users / Total Users) * 100
Returning Users % = 100 - New Users %

New visitors are identified by analytics tools as users who have never visited your website whereas returning users have visited your site before. They may or may not have completed a conversion action.

Optimization

We can use the same optimization strategies as discussed in the Total and Unique Visitors chapter but here are a couple more:

• Set relevant targeting for your marketing campaigns to acquire new users.
• Develop retention strategies and loyalty programs to increase returning visitors.
• Retargeting campaigns can help bring back users who might have forgotten about your site/offer.

Limitations

As with most user metrics, it’s hard to tell why users might be leaving or returning without further qualitative data.

Tools

New and returning users as metrics are available in most analytics tools like GA4, Matomo, Piwik, Mixpanel, etc.

Analysis Tips

Here’s how to analyze these metrics:

• Monitor new visitor growth alongside returning ones to understand how many fresh users you’re getting.
• Keep an eye on changes over time. For instance, an upward trend in returning users could signal loyalty or increased interest.
• See how these users behave on landing pages and evaluate how relevant the content is for them. For instance, if returning users are spending more time on product pages vs new users then you can personalize offers for them.
• Returning visitor data can be used to create audiences and used in retargeting campaigns.

Let’s check out more specific website metrics.

Content Metrics

The following two metrics are generally a good starting point to measure content performance:

7. Scroll depth
8. Average time on page

Let’s explore them further.

7. Scroll Depth

The percentage of the page a user scrolls through during their visit, and is typically measured when a page is scrolled to 25%, 50%, 75%, and 100%.

It helps to identify how much content users are consuming on a page or whether they are dropping off early. It can also provide insights into where your important messages or CTAs should be placed.

Optimization

Scroll depth can be optimized as follows:

• Use engaging intros or provide details on what they will learn/consume till the end so it encourages users to scroll more.
• Divide long pages into sections as well as make your content easy to scan if it’s mostly text.

Limitations

Depending on its setup, it will activate all threshold points at once if the page is too short to be scrolled. Moreover, it’s hard to distinguish between intentional and accidental scrolling.

Tools

Scroll tracking is available in tools like GA4, Clarity, and Hotjar.

Analysis Tips

Keep the following things in mind when looking at scroll depth:

• Look for the most common drop-off threshold.
• Pair it with time on page metric because just high scroll depth and low time on the page might mean they are just quickly scanning vs reading.
• Analyze how users scroll on different device types because while mobile users might scroll more they can easily ignore CTAs and other important elements.

8. Average Time on Page

This metric could be named differently depending on the tool you’re using, but the goal is to find how much average time a user spends on the page.

It’s often calculated by the tool’s own definition where the page is in the foreground or actively being browsed.

It’s interesting to understand how much time users are spending on complex or long-form content. It also helps get insight into whether the users are actually reading/engaging with content or just scanning.

Optimization

Some tips to improve average time on the page are:

• Use storytelling techniques with appealing visuals and make relevant content for your users.
• Try not to distract users with other messages or misplaced CTAs that can block the content.
• Optimize the layout for mobile and desktop users.
• Tailor the content depending on the traffic source.

Limitations

It could also include users who leave the tabs open but don’t engage. Needs to be paired with metrics like scroll depth to get a true sense of engagement.

Tools

In GA4 multiple time engagement metrics are available i.e. Average engagement time per active user, User engagement (shows the total time by all users), and Average engagement time per session.

It’s also available as session recordings in Clarity and Chartbeat for real-time Average Reading Time.

Analysis Tips

Some important tips for analyzing average time on page:

• Compare reading time against the average time users are spending on the page e.g. If a blog post takes 5 mins to read and users are spending only 2 mins then they aren’t fully engaging.
• Segment the data by traffic source as users coming from organic search vs social media posts have different intents.
• Compare if spending more time on a page also leads to more conversions. If not then the messaging might not be clear.
• Analyze by page type i.e. blogs, products, and landing pages typically have different reading times due to the nature of these pages.

eCommerce Metrics

While there could be many website metrics for eCommerce, the following three cover a lot of ground when paired with some of the metrics we covered in the generic section:

9. Average Order Value (AOV)
10. Cart Abandonment Rate

Let’s explore them further.

9. Average Order Value (AOV)

It is the average amount of money being spent on each order on your website and serves as a key indicator of the revenue your site is generating from every transaction. It’s derived from the following formula:

Average Order Value (AOV) = Total Revenue / Total Orders

It’s an important metric because it tracks the efficiency of your sales process and marketing campaigns. AOV also opens up conversations about how to increase revenue for each order.

Optimization

Here are some tips to optimize this important metric:

• Bundle your products and offer discounts to encourage visitors to buy more.
• Upsell by offering premium versions or complementary products to get more revenue.
• Set minimum order thresholds to encourage people to buy more.

Limitations

There are the following limitations of AOV:

• AOV does not translate into profitability, it focuses on revenue. Profit margins have to be considered as well.
• Seasonality and marketing campaigns can inflate your AOV temporarily e.g. holidays, Black Friday, etc.

Tools

It’s available in GA4, Shopify, Woocommerce (for WordPress) as well as other analytics tools out there.

Analysis Tips

Following are some tips to analyze AOV:

• Analyze your AOV depending on the traffic sources and other factors like new vs returning users. 
• Compare with the Cost of Acquisition (CAC) to ensure your AOV is above that otherwise, you’re not making a profit.
• As discussed AOV can be temporarily inflated due to seasonality or marketing campaigns and therefore, should be analyzed over time.

10. Cart Abandonment Rate

It tracks the percentage of users who add items to their carts but leaves without completing the order and is calculated with the following formula:

Cart Abandonment Rate = (Carts Abandoned / Total Add to Carts) * 100

It’s also sometimes interchangeably used with checkout abandonment, i.e., a visitor reaches the checkout page but doesn’t complete the purchase and it could be any step in the checkout flow.

High cart abandonment rates might signal issues with your checkout process/steps, surprises like high shipping prices, or simply users not understanding the value proposition.

Improving this metric means you’ll get more conversions and revenue.

Optimization

The following tips can help improve this metric:

• Simplify the checkout process and remove any friction points.
• Be clear on the product’s value proposition so users don’t get second thoughts easily.
• Address any concerns users might have about shopping with you (returns, exchanges, shipping, etc.).
• Send email reminders with incentives like discounts or free shipping to lure them back into the cart.

Limitations

Cart abandonment doesn’t take into account users who return back later to complete their purchase.

Some users simply leave items in their cart to compare prices or just save the items for later which doesn’t make them a true abandonment.

Tools

It might not be readily available as a metric in GA4 and other tools. In GA4, it can be derived from the Purchase journey report or created by using calculated metrics. You can also use tools like Looker Studio to create this metric.

Analysis Tips

Here are some tips when analyzing cart abandonments:

• Find out the steps in the funnel where users are abandoning so they can be further optimized.
• Segment by devices and see if certain device types result in high abandonment. Mobile users often have higher rates due to unfriendly user experience.
• Combine with time on the page to see if users are spending too long on any step and/or do some qualitative analysis with the help of heatmaps and session recordings.

SaaS Metrics

We can track a lot of SaaS metrics. But, apart from the ones discussed in general, the following two are good add-ons:

11. Churn Rate
12. Free/Trial to Paid Customer Rate

Let’s dive in!

11. Churn Rate

The churn rate refers to the percentage of users who cancel/stop using their subscription service over a period. It’s calculated with the following formula:

Churn Rate = Lost Customers / Total Customers at the Start of Period * 100

It’s important to track for SaaS businesses, as high churn can reduce recurring revenue and increase the cost of keeping current customers as well as increasing user growth.

Optimization

The churn rate can be improved by using some of the following strategies:

• Make onboarding smooth so new users can quickly realize the value of your product.
• Engage with customers regularly, whether it’s via emails or in-app notifications, so they are excited about new features, etc.
• Take feedback provided during cancellations seriously and fix the major pain points.

Limitations

Like most website metrics, Churn doesn’t explain ‘why’ users churn and requires further qualitative research. It can also vary widely depending on the pricing tier or customer segment.

Tools

Profitwell metrics, Baremetrics, Woopra, Kissmetrics, and Mixpanel are some tools that provide SaaS business insights.

Analysis Tips

Here are some analysis tips:

• Look at data by pricing tiers, as lower pricing tiers might have higher churn due to less commitment, and premium tiers may see better retention.
• Cohort analysis is a good way to analyze user behavior, e.g., newer cohorts churning a lot could mean issues with the onboarding process.
• Compare with product usage to see if inactive users churn more.

12. Free/Trial to Paid Customer Rate

This metric aims to track the percentage of users on free or trial plans and convert them into paid customers which is essentially a SaaS-specific conversion rate. It’s calculated with the following formulas:

Free to Paid Customer Rate = (Free Converted Users / Total Free Users) * 100
Trial to Paid Customer Rate = (Trial Converted Users / Total Trial Users) * 100

This metric helps to understand the efficacy of your free or trial plans in converting users to paid customers. Higher rates would mean the product delivers enough value that motivate users to convert.

Optimization

The metric can be improved as follows:

• The onboarding process should quickly show users the features and benefits with tutorials and guided tours.
• Communicate the premium features and the values they can deliver to them.
• Limit some of the premium features after some use, so that while users can get a taste, they understand what they will get if they pay for it.

Limitations

These rates can depend on the product-market fit as well as the pricing strategy. Moreover, SaaS users often exploit the free/trial plans without any intention of upgrading.

Tools

The same tools mentioned for the Churn rate can be used to track these website metrics.

Analysis Tips

Here are some tips to analyze this metric:

• Track conversion lag time. I.e., how long does it take for users to convert to paid plans? Longer times could indicate more nurturing needs to be done.
• Compare with features usage. For instance, which free features drive the most upgrades? These features can be highlighted during onboarding.

General Analysis Tips

These tips are not specific to any metric but are something we should bear in mind when analyzing data:

1. Metrics might not reveal everything. For instance, a bounce rate of 60% might be okay for blog pages but worrisome for checkout pages.
2. Always segment data to get more context, as numbers can vary quite a bit between traffic sources, devices, geography, demographics, etc.
3. Benchmark against previous periods and industry standards so you have something to compare against and help you create realistic goals.
4. Combine with other relevant website metrics to get a holistic picture.
5. Identify trends over time vs just one-off outliers as they don’t paint a true picture.
6. Use visualization tools like Looker Studio to make analyzing data easier in one place.

These tips are just the ‘tip’ of the iceberg. As you go deeper into analysis there will be more ways to get the most out of your data depending on your business type and industry. 

Summary

We covered a lot of ground in this post even though we only looked at 12 website metrics, starting with generic ones, which can be helpful regardless of what business we are in.

After that, we landed on content, eCommerce, and SaaS-specific metrics.

The highlight was looking at how some of these metrics are measured with their formulas, and optimizing strategies, their limitations, tools we can find them in, and tips to analyze them.

We topped it up with a few more general analysis tips to help you make more sense of your data.

We discussed Woocommerce in eCommerce metrics, so if you’re interested in using it with GA4, check out our post on Woocommerce Google Analytics 4 Tracking Guide.

So, what are the top website metrics you track? Are they different from what we have mentioned? Let us know it all in the comments below!