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A Simple Guide to Website Traffic Analytics
Ievgen Krasovytskyi, Head of Marketing @ OWOX
When you hear the term "website traffic analytics", what comes to mind? It's essentially a process of collecting, analyzing, and interpreting data about your website's visitors and their activities. By understanding this data, you can make better decisions to attract more visitors, retain them, and ultimately, increase your conversions.
Website traffic analysis isn't just about how many people visit your website. There are several crucial aspects you need to understand:
What is website traffic?
To measure the performance of a website, analysts and marketers look at website traffic: the total number of website visitors along with information on where they came from and how they got from there to the site.
Understanding website traffic analytics becomes much easier when you comprehend the key terms involved. Let's delve deeper into each one, so you have a solid foundation to build upon.
Events (Hits) are requests your site receives from visitors. This includes webpage loads (known as page_view), images or button clicks (click event), interactions with forms on your site (form_start and form_submit events) and much more. However, events may not be a true reflection of a visit because a single page can generate multiple events.
Sessions are set of interactions, such as page views, page iteractions or e-commerce activities that take place within a given time frame by a single user. It's a way to bundle all the events taken by one visitor during their visit to your site in a session by sessionization.
Users refers to unique visitors of your site and taking actions on it. Users can have multiple sessions on your site.
Metrics are units of measurement in data analytics. Metrics provide quantifiable data, such as the number of page views, the time spent on site, or the bounce rate.
Event parameters are specific settings or criteria used to filter or classify your analytics data. They could include geographical location, age, gender, or behavior of your users.
Dimensions describe the characteristics of your data. Dimensions can be used to organize, segment and categorize data for better analysis and reporting. For instance, the 'city' dimension could help you understand where your visitors are located.
Each of these terms plays its own role in web traffic analysis.
Having a proper analytics setup will not only improve your understanding of website traffic analytics, but also help you to analyze and optimize your website more effectively.
How to analyze website traffic
Your toolbox for traffic analysis will contain a number of tools to visualize and explore your site metrics. These services are programmed to examine your website from the inside out and give you a report based on this examination.
Simple tools for website analysis
Google Analytics 4 shows data about website traffic and data on user behavior in the form of events and sessions. Actions on the website are registered as events, and then those events are merged into sessions according to Google Analytics 4 logic.
What you should know about your web traffic are its sources, channels, and metrics. This would help you answer the most important questions as a website manager or owner:
- Which pages are attracting the most visitors?
- How much time they're spending on those pages,
- Where they're coming from (e.g., social media, Google search, paid ads)
- How do they convert website visitors into leads or customers?
- and even the path they take through your site...
This information empowers you to identify what's working well on your website and what's not, where improvements could be made, which marketing strategies are driving traffic, and most importantly, how you could increase your conversion rates to drive business growth.
You can find answers to these questions by looking at sources and channels in reports and dashboards.
Google Analytics is really very powerful for analyzing websites, but it has its limitations which are not so comfortable for marketers and business owners:
- It doesn’t account for internal data (such as sales data from your CMS or CRM)
- It doesn’t take product refunds into consideration
- It doesn’t consider cost data for non-Google campaigns
- Its attribution models are black box and limited
- You can't build LTV or cohort reports, and you can’t evaluate ROPO-effect and build suitable reports because of the lack of necessary data
If you’ve already encountered these limitations and tried to avoid them with the help of Google Analytics 360, you’ll know that sometimes even Google Analytics 360 isn’t enough.
Luckily, for businesses that dream big, there are special tools for end-to-end analytics.
Specialized tools for end-to-end analytics
As a website is part of the overall marketing and business strategy, it’s essential to analyze it in the overall context: connected with advertising channels, affiliate expences, your CRM or CMS systems, email marketing tools and other data flows.
To establish end-to-end analytics, start by collecting all of your marketing and sales data into one place, create a single source of truth for data across your organization and merge the data flows.
We would like to introduce you to OWOX BI — an all-in-one marketing analytics platform designed specifically to avoid the limitations of Google Analytics 4 and to be a powerful personal analytics assistant for marketers.
OWOX BI helps you collect, normalize, and merge data from different sources and prepare for reporting:
- Behavioral data from your website - and correctly find the acquisition sources of conversions;
- Ad cost data - and attribute each dollar spent to users and their sessions across your website;
- Offline sales data - and empower your advertising campaigns with the exact amount of revenue value;
- CRM / CMS / Internal data - and build reports of any complexity so you are able to merge the data that seems unblendable;
- Call tracking data, email marketing data, and much more.
OWOX BI collects all of this data automatically without data sampling so you can create a complete database for all kinds of reports: LTV, ROPO, historical analysis, predictive models, machine learning funnel-based attribution, and forecasted marketing performance.
Have you ever dreamed about a tool that would give you this level of granularity and predictive opportunities in just a few clicks?
Common functionality of analytics systems
Collect online event data
Most of the web traffic analytics systems collect information about actions on the website, registering clicks, scrolling, form submissions, etc. All of these events are gathered by the analytics system and marked with a timestamp and other event parameters from the data trace of each website visitor. This is the event data (in GA Universal it was called hit data), which is essential for web analytics.
In order to track event data, you need to add a tracking code of the analytics system to your website pages - typically called Pixel.
Group events into sessions
Without grouping all these website interactions into sessions, it's impossible to effectively use them for web performance analysis.
Keep in mind that every analytics system has its own unique logic for creating sessions from events. Imagine having a list of all website activities but lacking the details, like who executed those actions, how long they were taking place, or how regularly. Without this information, you would be blind when it comes to analyzing website activities and performance.
This brings us back to sessions - they are fundamental for analyzing web traffic. The total number of sessions is a metric that provides some immediate insights. In fact, it's often the first pre-processed data that you'll spot in your reports.
Website analytics reporting
Website analytics reporting is the way for an analytics system to inform you about the things happening on your website.
You can use prebuilt reports (such as a social media traffic report) or build your reports by combining metrics, parameters, and dimensions.
However, the most insightful reports are built with raw unsampled data (Google Analytics 4 applies data sampling when the volume of data exceeds its limits). The completeness of input data defines the quality of the report and the decisions you take based on this report.
Key entities involved in reporting web traffic analytics
The source of your traffic may be presented as a link to a web address from which each particular visitor came from.
Your sources might be:
- www.owox.com, etc.
The point is that people can visit your website from different types of links and through different channels.
When the source is undefined, typically the traffic is marked as Direct.
This happens for one of 2 main reasons:
- The User types the URL in the browser (or uses a bookmarked tab);
- The source is not specified due to privacy regulations and cookie restrictions.
Channels (presented as a medium in UTM)
The channel refers to the way in which a visitor navigates to your site. For example, these are some of the channels in Google Analytics 4:
- organic (free search traffic: eg. Google or Bing search)
- paid search (paid search: eg. Google ads)
- referral (your partners, affiliates)
- display (banner ads)
- social (social media posts: eg. Instagram stories)
- email (email marketing)
- none (undefined or unset medium)
- other (you can pre-configure custom UTM tags based on your mediums)
You can read more about UTM tagging and use it in your own web traffic analysis. It’s handy to create custom segments on the basis of channels and analyze targeted traffic apart from all other traffic.
For example, here is how Google Analytics 4 lays out each channel and the mediums (the general categories) to which it belongs. The medium description is essential to identify channels and define their type.
A keyword typically refers to a word or phrase that people type into a search engine. Keywords are connected tightly with how a search engine understands the intent of a person who’s looking for something and how it lists links, websites and resources in the search results.
You need to analyze keywords to understand which ones drive good traffic that drives conversions, as well as what your customers actually search for when they’re trying to find your website, service, or goods. You would benefit the most from producing content that’s tightly connected to your customers’ intentions.
The keywords people enter in the search bar are recognized by an analytics tool as the «keyword referral data». As you might have already realized, there are two kinds of keyword referral data:
Data about organic keywords is hidden due to Google’s policies, while data on paid keywords is visible and available for your analysis. That’s the reason, some reports will show a «not provided» value. You can also get «not provided» values from a paid channel if your campaigns are not correctly set.
Here is how OWOX BI helped to discover 2.4 times more keywords assisting in conversions and increasing PPC advertising ROI by 17%.
Now that are familiar with sources, mediums, channels, and keywords, we can proceed to channel grouping - the way to analyze your traffic by your rules.
Channel grouping — default and manual
A channel grouping is a level of classifying web traffic. The default channel grouping in Google Analytics 4 matches the lineup of channels described below.
Channels for Google Ads traffic
- Paid Shopping (Source platform is "Google Ads" AND Google Ads campaign type is "Shopping")
- Paid Search (Source platform is "Google Ads" AND Google Ads ad network type is one of "Google Search", "Google Partners")
- Paid Video (Source platform is "Google Ads" AND Google Ads ad network type is one of "YouTube Search", "YouTube Videos")
- Display (Source platform is "Google Ads" AND Google Ads ad network type is one of "Google Display Network")
- Paid Social (Source platform is "Google Ads" AND Google Ads ad network type is one of "Social")
Channels for other traffic
- Direct (Source exactly matches "(direct)" AND Medium is one of ("(not set)", "(none)")
- Cross-network (Campaign Name contains "cross-network")
- Paid Shopping (Source matches a list of shopping sites OR Campaign Name matches regex ^(.*(([^a-df-z]|^)shop|shopping).*)$) AND Medium matches regex ^(.*cp.*|ppc|retargeting|paid.*)$)
- Paid Search (Source matches a list of search sites AND Medium matches regex ^(.*cp.*|ppc|retargeting|paid.*)$)
- Paid Social (Source matches a regex list of social sites AND Medium matches regex ^(.*cp.*|ppc|retargeting|paid.*)$)
- Paid Video (Source matches a list of video sites AND Medium matches regex ^(.*cp.*|ppc|retargeting|paid.*)$)
- Display (Medium is one of (“display”, “banner”, “expandable”, “interstitial”, “cpm”)
- Paid Other (Medium matches regex ^(.*cp.*|ppc|retargeting|paid.*)$)
- Organic Social (Source matches a regex list of social sites OR Medium is one of (“social”, “social-network”, “social-media”, “sm”, “social network”, “social media”)
- Organic Video (Source matches a list of video sites OR Medium matches regex ^(.*video.*)$)
- Organic Search (Source matches a list of search sites OR Medium exactly matches organic)
- Referral (Medium is one of "referral", "app", or "link")
- Email (Source = email|e-mail|e_mail|e mail OR Medium = email|e-mail|e_mail|e mail)
- Affiliates (Medium = affiliate)
It’s handy to use this grouping in a general way, but as you know, these groups are aggregated, so they can hide some insights that might be useful for you.
For example, if you want to analyze traffic from your outreach campaign, you should create a custom channel group based of a referral channel, separating traffic with the help of UTM tags.
How to analyze website traffic
Dimensions are attributes of your data. Adding dimensions is the most popular and simplest approach to analysis. Here’s an example of a one-dimensional report:
And here’s what we can get by adding one more dimension:
By adding this additional dimension, we can see something that was previously hidden: the fact that the browser influences the pages/session metric quite a lot even for people in the same city.
Choosing the right dimension-metric combination, you can find a lot of useful insights for your website development. Wouldn’t it be great if someone could recall all the dimension-metric combinations for you? OWOX BI Smart Data knows popular dimension-metric combinations to build any kind of report in a couple of clicks, without hours of thinking over the report structure.
Segments offer a great possibility for analysts to compare part of the traffic with the whole picture. Comparing segments to other segments or to total data, you can conduct simple analysis that might be useful for beginners.
Here are some important tips on segments in GA:
- You can only show four segments in one report.
- AdWords cost data won’t be displayed with segments (it will give you a 0 value).
- Conversion segments must be used for multi-channel funnel reports.
Segments are important based on the understanding that aggregate data can’t help you a lot («All data in aggregate is crap,» according to Avinash Kaushik, who knows what he’s talking about). But if you slice and dice your data the right way, you’ll see many interesting insights.
In Google Analytics, you can create a segment in any kind of report.
Here are some examples of segments for you to try out:
The other way to use segments is to create them for better performance of remarketing, trigger emails, and special offer campaigns.
Okay, we’ve gotten through the segmentation part. That’s great! But to prepare you fully, let’s see what web traffic metrics you have to know to analyze everything correctly.
As Peter Drucker once said, «You can’t manage what you don’t measure.» But measuring on its own is a dead end. Explaining and interpreting — that’s how you get profit from measuring. So be careful with metrics; don’t forget about the real people standing behind them.
Here’s a list of essential metrics for an e-commerce website (and the corresponding reports in GA):
- New visits / total traffic
User → User Attributes → Demographic details
If you want to find out where your customers come from to optimize your ads campaigns, develop the website, and email marketing, you need this report. These primary dimensions are available in the Demographic details report: Country, Region, City, Language, Age, Gender, and Interests. The report shows a map of the world by default, and color saturation demonstrates the proportion of sessions from different regions.
- Behavioral metrics: Bounce Rate, Average Visit Duration, Pages per Visit
Audience → Overview
This group of metrics shows your visitors’ behavior on the website: whether they’re active and interested — Average Session Duration metric, how long they stay on the site — Page / Sessions metric, how fast they leave the site — Bounce Rate, etc. Also, in the device and platform dimensions, you can find insights about how page loading speed and website presentation on different devices influence your visitors’ behavior. Sometimes, waiting for the page to load is painful and people leave the website; the bounce rate starts growing, and you can notice this to make improvements.
- Pages investigations: landing & exit pages
Behavior → Site Content → Landing Pages,Behavior → Site Content → Exit Pages
This is another dimension to investigate. Looking at all behavioral metrics at the level of pages will help you understand the most popular and least popular pages and give a hint about what to do to improve the situation. For example, if one of your checkout pages is among the popular exit pages, it might be a sign of technical problems.
- On-page event tracking
Behavior → Site Search
You may track a lot of events on your website, from a simple click anywhere on the page to conversion events: purchases, email subscriptions, comments and feedback, etc. Why do you have to track all of these events? If you want to grow, you should look at keywords your customers are entering in the search bar and identify the most popular and least popular buttons.
- Multi-channel funnel investigations
Conversions → Multi-Channel Funnel → Overview
If you imagine a way to get from anywhere on the internet to make a purchase on your site, you can see that’s a long path. Or a funnel, as marketers call it. Website analytics tools help you understand the sequence of channels that lead a visitor to make a conversion and show the importance of each channel.
If you see that your typical user journey, a sequence of channels that takes to convert you visitor into customer, has more than three channels, you need a perfect attribution model that would evaluate the whole hero's journey and the contribution of each channel at each funnel stage.
The standard attribution model won’t fit your needs, as one of the channels will be overvalued while the value of other channels would be underestimated.
Find out how to solve this attribution problem with OWOX BI.
As you see, metrics and investigations are waiting for you. You can explore more marketing metrics in this article. Remember one more thing while working with metrics and statistics: they’re always dynamic, and the change in values matters more than today’s or yesterday’s values on their own.
Also, don’t forget that statistics about website traffic is not the end of your website analysis. Let’s take it one more step ahead.
Merge internal data with online data
On your way to end-to-end analytics, you’ll get to the stage of merging the sales data, also known as internal / CMS / CRM data with the user behavior data and, basically your cost data.
At this stage, you’ll enrich your on-site analytics data with information about sales performance and completed orders. A simple way to do that is using OWOX BI.
With sales and CRM data, you can evaluate the real value of your marketing efforts, and estimate the whole sales funnel performance without missing important insights.
You can get answers to these questions with OWOX BI:
- What was the order completion rate by the campaign?
- What was the ROAS by gross profit by source and medium?
- How many transactions were recorded in the CRM and how many customers were there in each store over a given period of time?
- What’s my ROPO effect?
- and much more...
Get your questions answered faster. Build an end-to-end analytics system with OWOX BI, make wise decisions about your website performance and cross-channel budget allocation and move from chaos to clarity.
Google Looker Studio templates
For those of you who like to make quick decisions with precision, we’ve prepared a number of Google Looker Studio templates for you!
30 handpicked Google Data Studio dashboards for marketersDownload now
Start with simple tools for investigating web traffic and progress to more sophisticated tools. Every business has to find the perfect set of analytic tools in order to grow. Consider the limitations of free versions of tools and get ready for each step on your way to end-to-end analytics.
After all, web traffic analytics is probably the first step of your journey to gain data clarity.
What is the future of analytics?The future of analytics involves a shift towards advanced analytics techniques such as predictive analytics, machine learning, and artificial intelligence to gain deeper insights and make more informed business decisions.
How will data privacy regulations impact the future of analytics?Data privacy regulations such as GDPR and CCPA will continue to shape the future of analytics by requiring organizations to be transparent about how they collect, store, and process personal data, and giving individuals more control over their data.
What are some of the challenges in implementing advanced analytics techniques?Implementing advanced analytics techniques can be challenging due to the complexity of the technology, the need for specialized skills and expertise, and the potential for biases and errors in the data analysis process.