Les articles publiés sur le site
-
What Are Website KPIs (10 KPIs and Best Ways to Track Them)
3 mai, par ErinTrying to improve your website’s performance?
Have you ever heard the phrase, “What gets measured gets managed?”
To improve, you need to start crunching your numbers.
The question is, what numbers are you supposed to track?
If you want to improve your conversions, then you need to track your website KPIs.
In this guide, we’ll break down the top website KPIs you need to be tracking and how you can track them so you can double down on what’s working with your website (and ditch what’s not).
Let’s begin.
What are website KPIs?
Before we dive into website KPIs, let’s define “KPI.”
A KPI is a key performance indicator.
You can use this measurable metric to track progress toward a specific objective.
A website KPI is a metric to track progress towards a specific website performance objective.
Website KPIs help your business identify strengths and weaknesses on your website, activities you’re doing well (and those you’re struggling with).
Web KPIs can give you and your team a target to reach with simple checkpoints to show you whether you’re on the right track toward your goals.
By tracking website KPIs regularly, you can ensure your organisation performs consistently at a high level.
Whether you’re looking to improve your traffic, leads or revenue, keeping a close eye on your website KPIs can help you reach your goals.
10 Website KPIs to track
If you want to improve your site’s performance, you need to track the right KPIs.
While there are plenty of web analytics solutions on the market today, below we’ll cover KPIs that are automatically tracked in Matomo (and don’t require any configuration).
Here are the top 10 website KPIs you need to track to improve site performance and grow your brand:
1. Pageviews
Website pageviews are one of the most important KPIs to track.
What is it exactly?
It’s simply the number of times a specific web page has been viewed on your site in a specific time period.
For example, your homepage might have had 327 pageviews last month, and only 252 this month.
This is a drop of 23%.
A drop in pageviews could mean your search engine optimisation or traffic campaigns are weakening. Alternatively, if you see pageviews rise, it could mean your marketing initiatives are performing well.
High or low pageviews could also indicate potential issues on specific pages. For example, your visitors might have trouble finding specific pages if you have poor website structure.
2. Average time on page
Now that you understand pageviews, let’s talk about average time on page.
This is simple: it’s the average amount of time your visitors spend on a particular web page on your site.
This isn’t the average time they spend on your website but on a specific page.
If you’re finding that you’re getting steady traffic to a specific web page, but the average time on the page is low, it may mean the content on the page needs to be updated or optimised.
Tracking your average time on page is important, as the longer someone stays on a page, the better the experience.
This isn’t a hard and fast rule, though. For specific types of content like knowledge base articles, you may want a shorter period of time on page to ensure someone gets their answer quickly.
3. Bounce rate
Bounce rate sounds fun, right?
Well, it’s not usually a good thing for your website.
A bounce rate is how many users entered your website but “bounced” away without clicking through to another page.
Your bounce rate is a key KPI that helps you determine the quality of your content and the user experience on individual pages.
You could be getting plenty of traffic to your site, but if the majority are bouncing out before heading to new pages, it could mean that your content isn’t engaging enough for your visitors.
Remember, like average time on page, your bounce rate isn’t a black-and-white KPI.
A higher bounce rate may mean your site visitors got exactly what they needed and are pleased.
But, if you have a high bounce rate on a product page or a landing page, that is a sign you need to optimise the page.
4. Exit rate
Bounce rate is the percentage of people who left the website after visiting one page.
Exit rate, on the other hand, is the percentage of website visits that ended on a specific page.
For example, you may find that a blog post you wrote has a 19% exit rate and received 1,000 visits that month. This means out of the 1,000 people who viewed this page, 190 exited after visiting it.
On the other hand, you may find that a second blog post has 1,000 pageviews, but a 10% exit rate, with only 100 people leaving the site after visiting this page.
What could this mean?
This means the second page did a better job keeping the person on your website longer. This could be because:
- It had more engaging content, keeping the visitors’ interest high
- It had better internal links to other relevant pieces of content
- It had a better call to action, taking someone to another web page
If you’re an e-commerce store and notice that your exit rate is higher on your product, cart or checkout pages, you may need to adjust those pages for better conversions.
5. Average page load time
Want to know another reason you may have a high exit rate or bounce rate on a page?
Your page load time.
The average page load time is the average time it takes (in seconds) from the moment you click through to a page until it has fully rendered within your browser.
In other words, it’s the time it takes after you click on a page for it to be fully functional.
Your average load time is a crucial website KPI because it significantly impacts page performance and the user experience.
How important is your page load time?
Nearly 53% of website visitors expect e-commerce pages to load in 3 seconds or less.
You will likely lose visitors if your pages take too long to load.
You could have the best content on a web page, but if it takes too long to load, your visitors will bounce, exit, or simply be frustrated.
6. Conversions
Conversions.
It’s one of the most popular words in digital marketing circles.
But what does it mean?
A conversion is simply the number of times someone takes a specific action on your website.
For example, it could be wanting someone to:
- Read a blog post
- Click an external link
- Download a PDF guide
- Sign up to your email list
- Comment on your blog post
- Watch a new video you uploaded
- Purchase a limited-edition product
- Sign up for a free trial of your software
To start tracking conversions, you need to first decide what your business goals are for your website.
With Matomo, you can set up conversions easily through the Goals feature. Simply set up your website goals, and Matomo will automatically track the conversions towards that objective (as a goal completion).
Simply choose what conversion you want to track, and you can analyse when conversions occur through the Matomo platform.
7. Conversion rate
Now that you know what a conversion is, it’s time to talk about conversion rate.
This key website KPI will help you analyse your performance towards your goals.
Conversion rate is simply the percentage of visitors who take a desired action, like completing a purchase, signing up for a newsletter, or filling out a form, out of the total number of visitors to your website or landing page.
Understanding this percentage can help you plan your marketing strategy to improve your website and business performance.
For instance, let’s say that 2% of your website visitors purchase a product on your digital storefront.
Knowing this, you could tweak different levers to increase your sales.
If your average order value is $50 and you get 100,000 visits monthly, you make about $100,000.
Let’s say you want to increase your revenue.
One option is to increase your traffic by implementing campaigns to increase different traffic sources, such as social media ads, search ads, organic social traffic, and SEO.
If you can get your traffic to 120,000 visitors monthly, you can increase your revenue to $120,000 — an additional $20,000 monthly for the extra 20,000 visits.
Or, if you wanted to increase revenue, you could ignore traffic growth and simply improve your website with conversion rate optimisation (CRO).
CRO is the practice of making changes to your website or landing page to encourage more visitors to take the desired action.
If you can get your conversion rate up to 2.5%, the calculation looks like this:
100,000 visits x $50 average order value x 2.5% = $125,000/month.
8. Average time spent on forms
If you want more conversions, you need to analyse forms.
Why?
Form analysis is crucial because it helps you pinpoint where users might be facing obstacles.
By identifying these pain points, you can refine the form’s layout and fields to enhance the user experience, leading to higher conversion rates.
In particular, you should track the average time spent on your forms to understand which ones might be causing frustration or confusion.
The average time a visitor spends on a form is calculated by measuring the duration between their first interaction with a form field (such as when they focus on it) and their final interaction.
Find out how Concrete CMS tripled their leads using Form Analytics.
9. Play rate
One often overlooked website KPI you need to be tracking is play rate.
What is it exactly?
The percentage of visitors who click “play” on a video or audio media format on a specific web page.
For example, if you have a video on your homepage, and 50 people watched it out of the 1,000 people who visited your website today, you have a play rate of 5%.
Play rate lets you track whenever someone consumes a particular piece of audio or video content on your website, like a video, podcast, or audiobook.
Not all web analytics solutions offer media analytics. However, Matomo lets you track your media like audio and video without the need for configuration, saving you time and upkeep.
10. Actions per visit
Another crucial website KPI is actions per visit.
This is the average number of interactions a visitor has with your website during a single visit.
For example, someone may visit your website, resulting in a variety of actions:
- Downloading content
- Clicking external links
- Visiting a number of pages
- Conducting specific site searches
Actions per visit is a core KPI that indicates how engaging your website and content are.
The higher the actions per visit, the more engaged your visitors typically are, which can help them stay longer and eventually convert to paying customers.
Track your website KPIs with Matomo today
Running a website is no easy task.
There are dozens of factors to consider and manage:
- Copy
- Design
- Performance
- Tech integrations
- And more
But, to improve your website and grow your business, you must also dive into your web analytics by tracking key website KPIs.
Managing these metrics can be challenging, but Matomo simplifies the process by consolidating all your core KPIs into one easy-to-use platform.
As a privacy-friendly and GDPR-compliant web analytics solution, Matomo tracks 20-40% more data than other solutions. So you gain access to 100% accurate, unsampled insights, enabling confident decision-making.
Join over 1 million websites that trust Matomo as their web analytics solution. Try it free for 21 days — no credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
-
How to Implement Cross-Channel Analytics : A Guide for Marketers
17 avril, par ErinEvery modern marketer knows they have to connect with consumers across several channels. But do you know how well Instagram works alongside organic traffic or your email list? Are you even tracking the impacts of these channels in one place?
You need a cross-channel analytics solution if you answered no to either of these questions.
In this article, we’ll explain cross-channel analytics, why your company probably needs it and how to set up a cross-channel analytics solution as quickly and easily as possible.
What is cross-channel analytics?
Cross-channel analytics is a form of marketing analytics that collects and analyses data from every channel and campaign you use.
The result is a comprehensive view of your customer’s journey and each channel’s role in converting customers.
Cross-channel analytics lets you track every channel you use to convert customers, including:
- Your website
- Social media profiles
- Paid search
- E-commerce
- Retargeting campaigns
Cross-channel analytics solves one of the most significant issues of cross-channel or multi-channel marketing efforts: measurement.
Research shows that only 16% of marketing tech stacks allow for accurate measurement of multi-channel initiatives across channels.
That’s a problem, given the staggering number of touchpoints in a typical buyer’s conversion path. However, it can be fixed using a cross-channel analytics approach that lets you measure the performance of every channel and assign a dollar value to its role in every conversion.
The difference between cross-channel analytics and multi-channel analytics
Cross-channel analytics and multi-channel analytics sound very similar, but there’s one key difference you need to know. Multi-channel analytics measures the performance of several channels, but not necessarily all of them, nor the extent to which they work together to drive conversions. Conversely, cross-channel analytics measures the performance of all your marketing channels and how they work together.
What are the benefits of cross-channel analytics
Cross-channel analytics offers a lot of marketing and business benefits. Here are the ones marketing managers love most.
Get a complete view of the customer journey
Implementing a cross-channel analytics solution is the only way to get a complete view of your customer journey.
Cross-channel marketing analytics lets you see your customer journey in high definition, allowing you to build comprehensive customer profiles using data from multiple sources across every touchpoint.
The result? You get to understand how every customer behaves at every point of the customer journey, why they convert or leave your funnel, and which channels play the biggest role.
In short, you get to see why customers convert so you can learn how to convert more of them.
Personalise the customer experience
According to a McKinsey study, customers demand personalisation, and brands that excel at it generate 40% more revenue. Deliver the personalisation they desire and reap the benefits with cross-channel analytics.
When you understand the customer journey in detail, it becomes much easier to personalise your website and marketing efforts to their preferences and behaviours.
Identify your most effective marketing channels
Cross-channel marketing helps you understand your marketing efforts to see how every channel impacts conversions.
Take a look at the screenshot from Matomo below. Cross-channel analytics lets you get incredibly granular — we can see the number of conversions of organic search drives and the performance of individual search engines.
This makes it easy to identify your most effective marketing channels and allocate your resources appropriately. It also allows you to ask (and answer) which channels are the most effective.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Attribute conversions accurately
An attribution model decides how you assign credit for each customer conversion to different touchpoints on the customer journey. Without a cross-channel analytics solution, you’re stuck using a standard attribution model like first or last click.
These models will show you how customers first found your brand or which channel finally convinced them to convert, but it doesn’t help you understand the role all your channels played in the conversion.
Cross-channel analytics solves this attribution problem. Rather than attributing a conversion to the touchpoint that directly led to the sale, cross-channel data gives you the real picture and allows you to use multi-touch attribution to understand which touchpoints generate the most revenue.
How to set up cross-channel analytics
Now that you know what cross-channel analytics is and why you should use it, here’s how to set up your solution.
Determine your objectives
Defining your marketing goals will help you build a more relevant and actionable cross-channel analytics solution.
If you want to improve marketing attribution, for example, you can choose a platform with that feature built-in. If you care about personalisation, you could choose a platform with A/B testing capabilities to measure the impact of your personalisation efforts.
Set relevant KPIs
You’ll want to track relevant KPIs to measure the marketing effectiveness of each channel. Put top-of-the-funnel metrics aside and focus on conversion metrics.
These include:
- Conversion rate
- Average visit duration
- Bounce rate
Implement tracking and analytics tools
Gathering customer data from every channel and centralising it in a single location is one of the biggest challenges of cross-channel analytics. Still, it’s made easier with the right tracking tool or analytics platform.
The trick is to choose a platform that lets you measure as many of your channels as possible in a single platform. With Matomo, for example, you can track search, paid search, social and email campaigns and your website analytics.
Set up a multi-touch attribution model
Now that you have all of your data in one place, you can set up a multi-touch attribution model that lets you understand the extent to which each marketing channel contributes to your overall success.
There are several attribution models to choose from, including:
Each model has benefits and drawbacks, so choosing the right model for your organisation can be tricky. Rather than take a wild guess, evaluate each model against your marketing objectives, sales length cycle and data availability.
For example, if you want to focus on optimising customer acquisition costs, a model that prioritises earlier touchpoints will be better. If you care about conversions, you might try a time decay model.
Turn data into insights with reports
One of the big benefits of choosing a tool like Matomo, which consolidates data in one place, is that it significantly speeds up and simplifies reporting.
When all the data is stored in one platform, you don’t need to spend hours combing through your social media platforms and copying and pasting analytics data into a spreadsheet. It’s all there and ready for you to run reports.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Take action
There’s no point implementing a cross-channel analytics system if you aren’t going to take action.
But where should you start?
Optimising your budgets and prioritising marketing spend is a great starting point. Use your cross-channel insights to find your most effective marketing channels (they’re the ones that convert the most customers or have the highest ROI) and allocate more of your budget to them.
You can also optimise the channels that aren’t pulling their weight if social media is letting you down; for example, experiment with tactics like social commerce that could drive more conversions. Alternatively, you could choose to stop investing entirely in these channels.
Cross-channel analytics best practices
If you already have a cross-channel analytics solution, take things to the next level with the following best practices.
Use a centralised solution to track everything
Centralising your data in one analytics tool can streamline your marketing efforts and help you stay on top of your data. It won’t just save you from tabbing between different browsers or copying and pasting everything into a spreadsheet, but it can also make it easier to create reports.
Think about consumer privacy
If you are looking at a new cross-channel analytics tool, consider how it accounts for data privacy regulations in your area.
You’re going to be collecting a lot of data, so it’s important to respect their privacy wishes.
It’s best to choose a platform like Matomo that complies with the strictest privacy laws (CCPA, GDPR, etc.).
Monitor data in real time
So, you’ve got a holistic view of your marketing efforts by integrating all your channels into a single tool?
Great, now go further by monitoring the impact of your marketing efforts in real time.
With a web analytics platform like Matomo, you can see who visits your site, what they do, and where they come from through features like the visits log report, which even lets you view individual user sessions. This lets you measure the impact of posting on a particular social channel or launching a new offer.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Reallocate marketing budgets based on performance
When you track every channel, you can use a multi-touch attribution model like position-based or time-decay to give every channel the credit it deserves. But don’t just credit each channel; turn your valuable insights into action.
Use cross-channel attribution analytics data to reallocate your marketing budget to the most profitable channels or spend time optimising the channels that aren’t pulling their weight.
Cross-channel analytics platforms to get started with
The marketing analytics market is huge. Mordor Intelligence valued it at $6.31 billion in 2024 and expects it to reach $11.54 billion by 2029. Many of these platforms offer cross-channel analytics, but few can track the impact of multiple marketing channels in one place.
So, rather than force you to trawl through confusing product pages, we’ve shortlisted three of the best cross-channel analytics solutions.
Matomo
Matomo is a web analytics platform that lets you collect and centralise your marketing data while giving you 100% accurate data. That includes search, social, e-commerce, campaign tracking data and comprehensive website analytics.
Better still, you get the necessary tools to turn those insights into action. Custom reporting lets you track and visualise the metrics that matter, while conversion optimisation tools like built-in A/B testing, heatmaps, session recordings and more let you test your theories.
Google Analytics
Google Analytics is the most popular and widely used tool on the market. The level of analysis and customisation you can do with it is impressive for a free tool. That includes tracking just about any event and creating reports from scratch.
Google Analytics provides some cross-channel marketing features and lets you track the impact of various channels, such as social and search, but there are a couple of drawbacks.
Privacy can be a concern because Google Analytics collects data from your customers for its own remarketing purposes.
It also uses data sampling to generate wider insights from a small subset of your data. This lack of accurate data reporting can cause you to generate false insights.
With Google Analytics, you’ll also need to subscribe to additional tools to gain advanced insights into the user experience. So, consider that while this tool is free, you’ll need to pay for heatmaps, session recording and A/B testing tools to optimise effectively.
Improvado
Improvado is an analytics tool for sales and marketing teams that extracts thousands of metrics from hundreds of sources. It centralises data in data warehouses, from which you can create a range of marketing dashboards.
While Improvado does have analytics capabilities, it is primarily an ETL (extraction, transform, load) tool for organisations that want to centralise all their data. That means marketers who aren’t familiar with data transformations may struggle to get their heads around the complexity of the platform.
Make the most of cross-channel analytics with Matomo
Cross-channel analytics is the only way to get a comprehensive view of your customer journey and understand how your channels work together to drive conversions.
Then you’re dealing with so many channels and data; keeping things as simple as possible is the key to success. That’s why over 1 million websites choose Matomo.
Our all-in-one analytics solution measures traditional web analytics, behavioural analytics, attribution and SEO, so you have 100% accurate data in one place.
Try it free for 21 days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
-
Clickstream Data : Definition, Use Cases, and More
15 avril, par ErinGaining a deeper understanding of user behaviour — customers’ different paths, digital footprints, and engagement patterns — is crucial for providing a personalised experience and making informed marketing decisions.
In that sense, clickstream data, or a comprehensive record of a user’s online activities, is one of the most valuable sources of actionable insights into users’ behavioural patterns.
This article will cover everything marketing teams need to know about clickstream data, from the basic definition and examples to benefits, use cases, and best practices.
What is clickstream data?
As a form of web analytics, clickstream data focuses on tracking and analysing a user’s online activity. These digital breadcrumbs offer insights into the websites the user has visited, the pages they viewed, how much time they spent on a page, and where they went next.
Your clickstream pipeline can be viewed as a “roadmap” that can help you recognise consistent patterns in how users navigate your website.
With that said, you won’t be able to learn much by analysing clickstream data collected from one user’s session. However, a proper analysis of large clickstream datasets can provide a wealth of information about consumers’ online behaviours and trends — which marketing teams can use to make informed decisions and optimise their digital marketing strategy.
Clickstream data collection can serve numerous purposes, but the main goal remains the same — gaining valuable insights into visitors’ behaviours and online activities to deliver a better user experience and improve conversion likelihood.
Depending on the specific events you’re tracking, clickstream data can reveal the following:
- How visitors reach your website
- The terms they type into the search engine
- The first page they land on
- The most popular pages and sections of your website
- The amount of time they spend on a page
- Which elements of the page they interact with, and in what sequence
- The click path they take
- When they convert, cancel, or abandon their cart
- Where the user goes once they leave your website
As you can tell, once you start collecting this type of data, you’ll learn quite a bit about the user’s online journey and the different ways they engage with your website — all without including any personal details about your visitors.
Types of clickstream data
While all clickstream data keeps a record of the interactions that occur while the user is navigating a website or a mobile application — or any other digital platform — it can be divided into two types:
- Aggregated (web traffic) data provides comprehensive insights into the total number of visits and user interactions on a digital platform — such as your website — within a given timeframe
- Unaggregated data is broken up into smaller segments, focusing on an individual user’s online behaviour and website interactions
One thing to remember is that to gain valuable insights into user behaviour and uncover sequential patterns, you need a powerful tool and access to full clickstream datasets. Matomo’s Event Tracking can provide a comprehensive view of user interactions on your website or mobile app — everything from clicking a button and completing a form to adding (or removing) products from their cart.
On that note, based on the specific events you’re tracking when a user visits your website, clickstream data can include:
- Web navigation data: referring URL, visited pages, click path, and exit page
- User interaction data: mouse movements, click rate, scroll depth, and button clicks
- Conversion data: form submissions, sign-ups, and transactions
- Temporal data: page load time, timestamps, and the date and time of day of the user’s last login
- Session data: duration, start, and end times and number of pages viewed per session
- Error data: 404 errors and network or server response issues
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Clickstream data benefits and use cases
Given the actionable insights that clickstream data collection provides, it can serve a wide range of use cases — from identifying behavioural patterns and trends and examining competitors’ performance to helping marketing teams map out customer journeys and improve ROI.
According to the global Clickstream Analytics Market Report 2024, some key applications of clickstream analytics include click-path optimisation, website and app optimisation, customer analysis, basket analysis, personalisation, and traffic analysis.
The behavioural patterns and user preferences revealed by clickstream analytics data can have many applications — we’ve outlined the prominent use cases below.
Customer journey mapping
Clickstream data allows you to analyse the e-commerce customer’s online journey and provides insights into how they navigate your website. With such a comprehensive view of their click path, it becomes easier to understand user behaviour at each stage — from initial awareness to conversion — identify the most effective touchpoints and fine-tune that journey to improve their conversion likelihood.
Identifying customer trends
Clickstream data analytics can also help you identify trends and behavioural patterns — the most common sequences and similarities in how users reached your website and interacted with it — especially when you can access data from many website visitors.
Think about it — there are many ways in which you can use these insights into the sequence of clicks and interactions and recurring patterns to your team’s advantage.
Here’s an example:
It can reveal that some pieces of content and CTAs are performing well in encouraging visitors to take action — which shows how you should optimise other pages and what you should strive to create in the future, too.
Preventing site abandonment
Cart abandonment remains a serious issue for online retailers:
According to a recent report, the global cart abandonment rate in the fourth quarter of 2023 was at 83%.
That means that roughly eight out of ten e-commerce customers will abandon their shopping carts — most commonly due to additional costs, slow website loading times and the requirement to create an account before purchasing.
In addition to cart abandonment predictions, clickstream data analytics can reveal the pages where most visitors tend to leave your website. These drop-off points are clear indicators that something’s not working as it should — and once you can pinpoint them, you’ll be able to address the issue and increase conversion likelihood.
Improving marketing campaign ROI
As previously mentioned, clickstream data analysis provides insights into the customer journey. Still, you may not realise that you can also use this data to keep track of your marketing effectiveness.
Global digital ad spending continues to grow — and is expected to reach $836 billion by 2026. It’s easy to see why relying on accurate data is crucial when deciding which marketing channels to invest in.
You want to ensure you’re allocating your digital marketing and advertising budget to the channels — be it SEO, pay-per-click (PPC) ads, or social media campaigns — that impact driving conversions.
When you combine clickstream e-commerce data with conversion rates, you’ll find the latter in Matomo’s goal reports and have a solid, data-driven foundation for making better marketing decisions.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Delivering a better user experience (UX)
Clickstream data analysis allows you to identify specific “pain points” — areas of the website that are difficult to use and may cause customer frustration.
It’s clear how this would be beneficial to your business:
Once you’ve identified these pain points, you can make the necessary changes to your website’s layout and address any technical issues that users might face, improving usability and delivering a smoother experience to potential customers.
Collecting clickstream data: Tools and legal implications
Your team will need a powerful tool capable of handling clickstream analytics to reap the benefits we’ve discussed previously. But at the same time, you need to respect users’ online privacy throughout clickstream data collection.
Generally speaking, there are two ways to collect data about users’ online activity — web analytics tools and server log files.
Web analytics tools are the more commonly used solution. Specifically designed to collect and analyse website data, these tools rely on JavaScript tags that run in the browser, providing actionable insights about user behaviour. Server log files can be a gold mine of data, too — but that data is raw and unfiltered, making it much more challenging to interpret and analyse.
That brings us to one of the major clickstream challenges to keep in mind as you move forward — compliance.
While Google remains a dominant player in the web analytics market, there’s one area where Matomo has a significant advantage — user privacy.
Matomo operates according to privacy laws — including the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), making it an ethical alternative to Google Analytics.
It should go without saying, but compliance with data privacy laws — the most talked-about one being the GDPR framework introduced by the EU — isn’t something you can afford to overlook.
The GDPR was first implemented in the EU in 2018. Since then, several fines have been issued for non-compliance — including the record fine of €1.2 billion that Meta Platforms, Inc. received in 2023 for transferring personal data of EU-based users to the US.
Clickstream analytics data best practices
As valuable as it might be, processing large amounts of clickstream analytics data can be a complex — and, at times, overwhelming — process.
Here are some best practices to keep in mind when it comes to clickstream analysis:
Define your goals
It’s essential to take the time to define your goals and objectives.
Once you have a clear idea of what you want to learn from a given clickstream dataset and the outcomes you hope to see, it’ll be easier to narrow down your scope — rather than trying to tackle everything at once — before moving further down the clickstream pipeline.
Here are a few examples of goals and objectives you can set for clickstream analysis:
- Understanding and predicting users’ behavioural patterns
- Optimising marketing campaigns and ROI
- Attributing conversions to specific marketing touchpoints and channels
Analyse your data
Collecting clickstream analytics data is only part of the equation; what you do with raw data and how you analyse it matters. You can have the most comprehensive dataset at your disposal — but it’ll be practically worthless if you don’t have the skill set to analyse and interpret it.
In short, this is the stage of your clickstream pipeline where you uncover common sequences and consistent patterns in user behaviour.
Clickstream data analytics can extract actionable insights from large datasets using various approaches, models, and techniques.
Here are a few examples:
- If you’re working with clickstream e-commerce data, you should perform funnel or conversion analyses to track conversion rates as users move through your sales funnel.
- If you want to group and analyse users based on shared characteristics, you can use Matomo for cohort analysis.
- If your goal is to predict future trends and outcomes — conversion and cart abandonment prediction, for example — based on available data, prioritise predictive analytics.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Organise and visualise your data
As you reach the end of your clickstream pipeline, you need to start thinking about how you will present and communicate your data. And what better way to do that than to transform that data into easy-to-understand visualisations?
Here are a few examples of easily digestible formats that facilitate quick decision-making:
- User journey maps, which illustrate the exact sequence of interactions and user flow through your website
- Heatmaps, which serve as graphical — and typically colour-coded — representations of a website visitor’s activity
- Funnel analysis, which are broader at the top but get increasingly narrower towards the bottom as users flow through and drop off at different stages of the pipeline
Collect clickstream data with Matomo
Clickstream data is hard to beat when tracking the website visitor’s journey — from first to last interaction — and understanding user behaviour. By providing real-time insights, your clickstream pipeline can help you see the big picture, stay ahead of the curve and make informed decisions about your marketing efforts.
Matomo accurate data and compliance with GDPR and other data privacy regulations — it’s an all-in-one, ethical platform that can meet all your web analytics needs. That’s why over 1 million websites use Matomo for their web analytics.
Try Matomo free for 21 days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
-
A Beginner’s Guide to Omnichannel Analytics
14 avril, par ErinLinear customer journeys are as obsolete as dial-up internet and floppy disks. As a marketing manager, you know better than anyone that customers interact with your brand hundreds of times across dozens of channels before purchasing. That can make tracking them a nightmare unless you build an omnichannel analytics solution.
Alas, if only it were that simple.
Unfortunately, it’s not enough to collect data on your customers’ complex journeys just by buying an omnichannel platform. You need to generate actionable insights by using marketing attribution to tie channels to conversions.
This article will explain how to build a useful omnichannel analytics solution that lets you understand and improve the customer journey.
What is omnichannel analytics?
Omnichannel analytics collects and analyses customer data from every touchpoint and device. The goal is to collect all this omnichannel data in one place, creating a single, real-time, unified view of your customer’s journey.
Unfortunately, most businesses haven’t achieved this yet. As Karen Lellouche Tordjman and Marco Bertini say:
“Despite all the buzz around the concept of omnichannel, most companies still view customer journeys as a linear sequence of standardised touchpoints within a given channel. But the future of customer engagement transforms touchpoints from nodes along a predefined distribution path to full-blown portals that can serve as points of sale or pathways to many other digital and virtual interactions. They link to chatbots, kiosks, robo-advisors, and other tools that customers — especially younger ones — want to engage with.”
However, doing so is more important than ever — especially when consumers have over 300 digital touchpoints, and the average number of touchpoints in the B2B buyer journey is 27.
Not only that, but customers expect personalised experiences across every platform — that’s the kind you can only create when you have access to omnichannel data.
What might omnichannel analytics look like in practice for an e-commerce store?
An online store would integrate data from channels like its website, mobile app, social media accounts, Google Ads and customer service records. This would show how customers find its brand, how they use each channel to interact with it and which channels convert the most customers.
This would allow the e-commerce store to tailor marketing channels to customers’ needs. For instance, they could focus social media use on product discovery and customer support. Google Ads campaigns could target the best-converting products. While all this is happening, the store could also ensure every channel looks the same and delivers the same experience.
What are the benefits of omnichannel analytics?
Why go to all the trouble of creating a comprehensive view of the customer’s experience? Because you stand to gain some pretty significant benefits when implementing omnichannel analytics.
Understand the customer journey
You want to understand how your customers behave, right? No other method will allow you to fully understand your customer journey the way omnichannel analytics does.
It doesn’t matter how customers engage with your brand — whether that’s your website, app, social media profiles or physical stores — omnichannel analytics capture every interaction.
With this 360-degree view of your customers, it’s easy to understand how they move between channels, where they encounter issues and what bottlenecks prevent them from converting.
Deliver better personalisation
We don’t have to tell you that personalisation matters. But do you know just how important it is? Since 56% of customers will become repeat buyers after a personalised experience, delivering them as often as possible is critical.
Omnichannel analytics helps in your quest for personalisation by highlighting the individual preferences of customer segments. For example, e-commerce stores can use omnichannel analytics to understand how shoppers behave across different devices and tailor their offers accordingly.
Upgrade the customer experience
Omnichannel analytics gives you the insights to improve every aspect of the customer experience.
For starters, you can ensure a consistent brand experience across all your top channels by making sure they look and behave the same.
Then, you can use omnichannel insights to tailor each channel to your customers’ requirements. For example, most people interacting with your brand on social media may seek support. Knowing that you can create dedicated support accounts to assist users.
Improve marketing campaigns
Which marketing campaigns or traffic sources convert the most customers? How can you improve these campaigns? Omnichannel analytics has the answers.
When you implement omnichannel analytics you automatically track the performance of every marketing channel by attributing each conversion to one or more traffic sources. This lets you see whether Google Ads bring in more customers than your SEO efforts. Or whether social media ads are the most profitable acquisition channel.
Armed with this information, you can improve your marketing efforts — either by focusing on your profitable channels or rectifying problems that stop less profitable channels from converting.
What are the challenges of omnichannel analytics?
There are three challenges when implementing an omnichannel analytics solution:
- Complex customer journeys: Customer journeys aren’t linear and can be incredibly difficult to track.
- Regulatory and privacy issues: When you start gathering customer data, you quickly come up against consumer privacy laws.
- No underlying goal: There has to be a reason to go to all this effort, but brands don’t always have goals in mind before they start.
You can’t do anything about the first challenge.
After all, your customer journey will almost never be linear. And isn’t the point of implementing an omnichannel solution to understand these complex journeys in the first place? Once you set up omnichannel analytics, these journeys will be much easier to decipher.
As for the other two:
Using the right software that respects user privacy and complies with all major privacy laws will avoid regulatory issues. Take Matomo, for instance. Our software was designed with privacy in mind and is configured to follow the strictest privacy laws, such as GDPR.
Tying omnichannel analytics to marketing attribution will solve the final challenge by giving your omnichannel efforts a goal. When you tie omnichannel analytics to your marketing efforts, you aren’t just getting a 360-degree view of your customer journey for the sake of it. You are getting that view to improve your marketing efforts and increase sales.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
How to set up an omnichannel analytics solution
Want to set up a seamless analytical environment that incorporates data from every possible source? Follow these five steps:
Choose one or more analytics providers
You can use several tools to build an omnichannel analytics solution. These include web and app analytics tools, customer data platforms that centralise first-party data and business intelligence tools (typically used for visualisation).
Which tools you use will depend on your goals and your budget — the loftier your ambitions and the higher your budget, the more tools you can use.
Ideally, you should use as few tools as possible to capture your data. Most teams won’t need business intelligence platforms, for example. However, you may or may not need both an analytics platform and a customer data platform. Your decision will depend on how many channels your customers use and how well your analytics tool tracks everything.
If it can capture web and app usage while integrating with third-party platforms like your back-end e-commerce platform, then it’s probably enough.
Collect accurate data at every touchpoint
Your omnichannel analytics efforts hinge on the quantity and quality of data you can collect. You want to gather data from every touchpoint possible and store that data in as few places as possible. That’s why choosing as few tools as possible in the step above is so important.
So, where should you start? Common data sources include:
- Your website
- Apps (iOS and Android)
- Social media profiles
- ERPs
- PoS systems
At the same time, make sure you’re tracking all relevant metrics. Revenue, customer engagement and conversion-focused metrics like conversion rate, dwell time, cart abandonment rate and churn rate are particularly important.
Set up marketing attribution
Setting up marketing attribution (also known as multi-touch attribution) is essential to tie omnichannel data to business goals. It’s the only way to know exactly how valuable each marketing channel is and where each customer comes from.
You’ll want to use multi-touch attribution, given you have data from across the customer journey.
Multi-touch attribution models can include (but are not limited to):
- Linear: where each touchpoint is given equal weighting
- Time decay: where touchpoints are more valuable the nearer they are to conversion
- Position-based: where the first and last touch points are more valuable than all the others.
You don’t have to use just one of the models above, however. One of the benefits of using a web analytics tool like Matomo is that you can choose between different attribution models and compare them.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Create reports that help you visualise data
Dashboards are your friend here. They’ll let you see KPIs at a glance, allowing you to keep track of day-to-day changes in your customer journey. Ideally, you’ll want a platform that lets you customise dashboard widgets so only relevant KPIs are shown.
Setting up standard and custom reports is also important. Custom reports allow you to choose metrics and dimensions that align with your goals. They will also allow you to present your data most meaningfully to your team, increasing the likelihood they act upon insights.
Analyse data and take action
Now that you have customer journey data at your fingertips, it’s time to analyse it. After all, there’s no point in implementing an omnichannel analytics solution if you aren’t going to take action.
If you’re unsure where to start, re-read the benefits we listed at the start of this article. You could use your omnichannel insights to improve your marketing campaigns by doubling down on the channels that bring in the best customers.
Or you could identify (and fix) bottlenecks in the customer journey so customers are less likely to fall out of your funnel between certain channels.
Just make sure you take action based on your data alone.
Make the most of omnichannel analytics with Matomo
A comprehensive web and app analytics platform is vital to any omnichannel analytics strategy.
But not just any solution will do. When privacy regulations impede an omnichannel analytics solution, you need a platform to capture accurate data without breaking privacy laws or your users’ trust.
That’s where Matomo comes in. Our privacy-friendly web analytics platform ensures accurate tracking of web traffic while keeping you compliant with even the strictest regulations. Moreover, our range of APIs and SDKs makes it easy to track interactions from all your digital products (website, apps, e-commerce back-ends, etc.) in one place.
Try Matomo for free for 21 days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
-
7 Ecommerce Metrics to Track and Improve in 2024
12 avril, par ErinYou can invest hours into market research, create the best ads you’ve ever seen and fine-tune your budgets. But the only way to really know if your digital marketing campaigns move the needle is to track ecommerce metrics.
It’s time to put your hopes and gut feelings aside and focus on the data. Ecommerce metrics are key performance indicators that can tell you a lot about the performance of a single campaign, a traffic source or your entire marketing efforts.
That’s why it’s essential to understand what ecommerce metrics are, key metrics to track and how to improve them.
Ready to do all of the above? Then, let’s get started.
What are ecommerce metrics?
An ecommerce metric is any metric that helps you understand the effectiveness of your digital marketing efforts and the extent to which users are taking a desired action. Most ecommerce metrics focus on conversions, which could be anything from making a purchase to subscribing to your email list.
You need to track ecommerce metrics to understand how well your marketing efforts are working. They are essential to helping you run a cost-effective marketing campaign that delivers a return on investment.
For example, tracking ecommerce metrics will help you identify whether your digital marketing campaigns are generating a return on investment or whether they are actually losing money. They also help you identify your most effective campaigns and traffic sources.
Ecommerce metrics also help you spot opportunities for improvement both in terms of your marketing campaigns and your site’s UX.
For instance, you can use ecommerce metrics to track the impact on revenue of A/B tests on your marketing campaigns. Or you can use them to understand how users interact with your website and what, if anything, you can do to make it more engaging.
What’s the difference between conversion rate and conversion value?
The difference between a conversion rate and a conversion value is that the former is a percentage while the latter is a monetary value.
There can be confusion between the terms conversion rate and conversion value. Since conversions are core metrics in ecommerce, it’s worth taking a minute to clarify.
Conversion rates measure the percentage of people who take a desired action on your website compared to the total number of visitors. If you have 100 visitors and one of them converts, then your conversion rate is 1%.
Here’s the formula for calculating your conversion rate:
Conversion Rate (%) = (Number of conversions / Total number of visitors) × 100
Using the example above:
Conversion Rate = (1 / 100) × 100 = 1%
Conversion value is a monetary amount you assign to each conversion. In some cases, this is the price of the product a user purchases. In other conversion events, such as signing up for a free trial, you may wish to assign a hypothetical conversion value.
To calculate a hypothetical conversion value, let’s consider that you have estimated the average revenue generated from a paying customer is $300. If the conversion rate from free trial to paying customer is 20%, then the hypothetical conversion value for each free trial signup would be $300 multiplied by 20%, which equals $60. This takes into account the number of free trial users who eventually become paying customers.
So the formula for hypothetical conversion value looks like this:
Hypothetical conversion value = (Average revenue per paying customer) × (Conversion rate)
Using the values from our example:
Hypothetical conversion value = $300 × 20% = $60
The most important ecommerce metrics and how to track them
There are dozens of ecommerce metrics you could track, but here are seven of the most important.
Conversion rate
Conversion rate is the percentage of visitors who take a desired action. It is arguably one of the most important ecommerce metrics and a great top-level indicator of the success of your marketing efforts.
You can measure the conversion rate of anything, including newsletter signups, ebook downloads, and product purchases, using the following formula:
Conversion rate = (Number of people who took action / Total number of visitors) × 100
You usually won’t have to manually calculate your conversion rate, though. Almost every web analytics or ad platform will track the conversion rate automatically.
Matomo, for instance, automatically tracks any conversion you set in the Goals report.
As you can see in the screenshot, your site’s conversions are plotted over a period of time and the conversion rate is tracked below the graph. You can change the time period to see how your conversion rate fluctuates.
If you want to go even further, track your new visitor conversion rate to see how engaging your site is to first-time visitors.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Cost per acquisition
Cost per acquisition (CPA) is the average cost of acquiring a new user. You can calculate your overall CPA or you can break CPA down by email campaign, traffic source, or any other criteria.
Calculate CPA by dividing your total marketing cost by the number of new users you acquire.
CPA = Total marketing cost / Number of new users acquired
So if your Google Ads campaign costs €1,000 and you acquire 100 new users, your CPA is €10 (1000/100=10).
It’s important to note that CPA is not the same as customer acquisition cost. Customer acquisition cost considers the number of paying customers. CPA looks at the number of users taking a certain action, like subscribing to a newsletter, making a purchase, or signing up for a free trial.
Cost per acquisition is a direct measure of your marketing efforts’ effectiveness, especially when comparing CPA to average customer spend and return on ad spend.
If your CPA is higher than the average customer spend, your marketing campaign is profitable. If not, then you can look at ways to either increase customer spend or decrease your cost per acquisition.
Customer lifetime value
Customer lifetime value (CLV) is the average amount of money a customer will spend with your ecommerce brand over their lifetime.
Customer value is the total worth of a customer to your brand based on their purchasing behaviour. To calculate it, multiply the average purchase value by the average number of purchases. For instance, if the average purchase value is €50 and customers make 5 purchases on average, the customer value would be €250.
Use this formula to calculate customer value:
Customer value = Average purchase value × Average number of purchases
Then you can calculate customer lifetime value using the following formula:
CLV = Customer value × Average customer lifespan
In another example, let’s say you have a software company and customers pay you €500 per year for an annual subscription. If the average customer lifespan is 5 years, then the Customer Lifetime Value (CLV) would be €2,500.
Customer lifetime value = €500 × 5 = €2,500
Knowing how much potential customers are likely to spend helps you set accurate marketing budgets and optimise the price of your products.
Return on investment
Return on investment (ROI) is the amount of revenue your marketing efforts generate compared to total spend.
It’s usually calculated as a percentage using the following formula:
ROI = (Revenue / Total spend) × 100
If you spend €1,000 on a paid ad campaign and your efforts bring in €5,000, then your ROI is 500% (5,000/1,000 × 100).
With a web analytics tool like Matomo, you can quickly see the revenue generated from each traffic source and you can drill down further to compare different social media channels, search engines, referral websites and campaigns to get more granular view.
In the example above in Matomo’s Marketing Attribution feature, we can see that social networks are generating the highest amount of revenue in the year. To calculate ROI, we would need to compare the amount of investment to each channel.
Let’s say we invested $1,000 per year in search engine optimisation and content marketing, the return on investment (ROI) stands at approximately 2576%, based on a revenue of $26,763.48 per year.
Conversely, for organic social media campaigns, where $5,000 was invested and revenue amounted to $71,180.22 per year, the ROI is approximately 1323%.
Despite differences in revenue generation, both channels exhibit significant returns on investment, with SEO and content marketing demonstrating a much higher ROI compared to organic social media campaigns.
With that in mind, we might want to consider shifting our marketing budget to focus more on search engine optimisation and content marketing as it’s a greater return on investment.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Return on ad spend
Return on ad spend (ROAS) is similar to return on investment, but it measures the profitability of a specific ad or campaign.
Calculate ROAS using the following formula:
ROAS = Revenue / Ad cost
A positive ROAS means you are making money. If you generate €3 for every €1 you spend on advertising, for example, there’s no reason to turn off that campaign. If you only make €1 for every €2 you spend, however, then you need to shut down the campaign or optimise it.
Bounce rate
Bounce rate is the percentage of visitors who leave your site without taking another action. Calculate it using the following formula:
Bounce rate = (Number of visitors who bounce / Total number of visitors) × 100
Some portion of users will always leave your site immediately, but you should aim to make your bounce rate as low as possible. After all, every customer that bounces is a missed opportunity that you may never get again.
You can check the bounce rate for each one of your site’s pages using Matomo’s page analytics report. Web analytics tools like Google Analytics can track bounce rates for online stores also.
Bounce rate is calculated automatically. You can sort the list of pages by bounce rate allowing you to prioritise your optimisation efforts.
Don’t stop there, though. Explore bounce rate further by comparing your mobile bounce rate vs. desktop bounce rate by segmenting your traffic. This will highlight whether your mobile site needs improving.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Click-through rate
Your clickthrough rate (CTR) tells you the number of people who click on your ads as a percentage of total impressions. You can calculate it by dividing the number of clicks your ad gets by the total number of times people see it.
So the formula looks like this:
CTR (%) = (Number of clicks / Total impressions) × 100
If an ad gets 1,000 impressions and 10 people click on it, then the CTR will be 10/1,000 × 100 = 1%
You don’t usually need to calculate your clickthrough rate manually, however. Most ad platforms like Google Ads will automatically calculate CTR.
What is considered a good ecommerce sales conversion rate?
This question is so broad it’s almost impossible to answer. The thing is, sales conversion rates vary massively depending on the conversion event and the industry. A good conversion rate in one industry might be terrible in another.
That being said, research shows that the average website conversion rate across all industries is 2.35%. Of course, some websites convert much better than this. The same study found that the top 25% of websites across all industries have a conversion rate of 5.31% or higher.
How can you improve your conversion rate?
Ecommerce metrics don’t just let you track your campaign’s ROI, they help you identify ways to improve your campaign.
Use these five tips to start improving your marketing campaign’s conversion rates today:
Run A/B tests
The most effective way to improve almost all of the ecommerce metrics you track is to test, test, and test again.
A/B testing or multivariate testing compares two different versions of the same content, such as a landing page or blog post. Seeing which version performs better can help you squeeze as many conversions as possible from your website and ad campaigns. But only if you test as many things as possible. This should include:
- Ad placement
- Ad copy
- CTAs
- Headlines
- Straplines
- Colours
- Design
To create and analyse tests and their results effectively, you’ll need either an A/B testing platform or a web analytics solution like Matomo, which offers one out of the box.
Matomo’s A/B Testing feature makes it easy to create and track tests over time, breaking down each test’s variations by the metrics that matter. It automatically calculates statistical significance, too, meaning you can be sure you’re making a change for the better.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
