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Conversion Funnel Optimisation : 10 Ways to Convert More
24 janvier 2024, par ErinConverting leads into happy customers is the ultimate goal of any sales and marketing team. But there are many steps in between those two events, or in other words, funnel stages.
Your sales funnel includes all the steps you take to make your audience aware of your product or services and convince them to purchase. Conversion funnel optimisation strategies can help you move users through the stages of your sales funnel.
This article will show you how to optimise your conversion funnel and boost sales — no matter how your funnel looks. We’ll go over practical tips you can implement and how you can analyse and measure results.
Let’s get started.
What is conversion funnel optimisation?
Conversion funnel optimisation is the strategic and ongoing process of refining and improving the different stages of a sales or marketing funnel to increase the rate at which users complete desired actions.
A sales funnel represents the stages a potential customer goes through before purchasing.
The typical stages of a sales funnel include:
- Awareness: At the top of the funnel, potential customers become aware of your product or service.
- Consideration: In this stage, prospects evaluate the product or service against alternatives. They may compare features, prices and customer reviews to make an informed decision.
- Conversion: The prospect completes the transaction and becomes an actual customer by purchasing.
- Loyalty: You can turn one-time buyers into repeat customers and brand advocates.
It’s called a “funnel” because, similar to the shape of a funnel, the number of potential customers decreases as they progress through the various stages of the sales process — as you can see illustrated below.
Sales funnels can vary across industries and business models, but the general concept remains the same. The goal is to guide potential customers through each funnel stage, addressing their needs and concerns at each step, ultimately leading to a successful conversion.
You can create and monitor a custom funnel for your site’s user journey with a web analytics solution like Matomo.
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The importance of conversion funnel optimisation
At the heart of conversion funnel optimisation is the quest for higher conversion rates.
Refining the customer journey can increase the chances of turning visitors into customers who return repeatedly.
Specifically, here’s how conversion funnel optimisation can benefit your business:
- Increased conversions: Marketers can increase the likelihood of turning website visitors into customers by making the user journey more user-friendly and persuasive.
- Higher revenue: Improved conversion rates aren’t just numbers on a chart; they translate to tangible revenue.
- Increased ROI (return on investment): By optimising the conversion funnel, you can get more value from your marketing and sales efforts.
- Improved customer satisfaction: When customers find it easy and enjoyable to interact with a website or service, it positively influences their satisfaction and likelihood of returning.
- Data-driven decision-making: Businesses can make informed decisions on budgets and resources based on user behaviour and performance metrics by analysing and optimising conversion funnels.
Ultimately, conversion funnel optimisation efforts align the entire funnel with overarching business goals.
10 ways to optimise your conversion funnel
Here are 10 ways to optimise your conversion funnel.
1. Identify and segment your target audience
The key to a successful conversion funnel begins with a deep understanding of your target audience.
Identifying and segmenting your audience lets you speak directly to their pain points, desires and motivations.
One effective way to know your audience better is by creating detailed buyer personas. These are fictional representations of your ideal customers based on thorough market research and real data. Dive into demographics and behavioural patterns to craft personas that resonate with your audience.
Note that consumer preferences are not static. They evolve, influenced by trends, technological advancements and shifts in societal values. Staying attuned to these changes is crucial as part of optimising your conversion funnel.
Thus, you must regularly update your buyer personas and adjust your marketing strategies accordingly.
2. Create content for every stage of the funnel
Each funnel stage represents a different mindset and needs for your potential customers. Tailoring your content ensures you deliver the right message at the right time to the right audience.
Here’s how to tailor your content to fit prospective customers at every conversion funnel stage.
Awareness-stage content
Prospects here are seeking information. Your content should be educational and focused on addressing their pain points. Create blog posts, infographics and videos introducing them to your industry, product or service.
Consideration-stage content
Prospects are evaluating their options. Provide content highlighting your product’s unique selling points, such as case studies, product demonstrations and customer testimonials.
Here’s how we use a versus landing page at Matomo to persuade prospects at this funnel stage.
Conversion-stage content
This is the final push. Ensure a smooth transition to conversion with content like promotional offers, limited-time discounts and clear calls to action (CTA).
Loyalty-stage content
In this stage, you might express gratitude for the purchase through personalised thank-you emails. Follow up with additional resources, tips or exclusive offers to reinforce a positive post-purchase experience. This also positions your brand as a helpful resource beyond the initial sale.
Reward customer loyalty with exclusive offers, discounts or membership in a loyalty program.
3. Capture leads
Lead magnets are incentives offered to potential customers in exchange for their contact information, typically their email addresses.
Examples of lead magnets include:
- Ebooks and whitepapers: In-depth resources that delve into specific topics of interest to your target audience.
- Webinars and workshops: Live or recorded sessions that offer valuable insights, training or demonstrations.
- Free trials and demos: Opportunities for potential customers to experience your product or service firsthand.
- Checklists and templates: Practical tools that help your audience solve specific challenges.
- Exclusive offers and discounts: Special promotions are available to those who subscribe or provide their contact information.
For instance, here’s how HubSpot uses templates as lead magnets.
Similarly, you can incorporate your lead magnets into relevant articles or social media posts, email campaigns and other marketing channels.
4. Optimise your landing pages
Understanding how visitors interact with your landing pages is a game-changer. So, the first step in optimising your landing pages is to analyse them.
Enter Matomo’s heatmaps — the secret weapon in landing page optimisation. They visually represent how users interact with your pages, revealing where they linger, what catches their attention and where they may encounter friction.
Here are a few landing page elements you should pay attention to:
- Strategic visual elements: Integrate high-quality images, videos and graphics that support your message and guide visitors through the content.
- Compelling copy: Develop concise and persuasive copy that emphasises the benefits of your offering, addressing user pain points.
- Effective CTA: Ensure your CTA is prominently displayed, using compelling language and colours that stand out.
- Mobile responsiveness: Optimise your landing pages for various devices, especially considering the prevalence of mobile users.
- Minimal form fields: Reduce friction by keeping form fields to a minimum, requesting only essential information.
- Leverage social proof: Integrate testimonials, reviews and trust badges to build trust and credibility.
- A/B testing: Experiment with variations in design, copy and CTAs through A/B testing, allowing data to guide your decisions.
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5. Use compelling Calls to Action (CTAs)
Crafting compelling CTAs is an art that involves a careful balance of persuasion, clarity and relevance.
Here are a few tips you can implement to write CTAs that support your goals:
- Use language that compels action. Instead of generic phrases like “Click Here,” opt for more persuasive alternatives such as “Unlock Exclusive Access” or “Start Your Free Trial.”
- Make sure your CTAs are clear and straightforward. Visitors should instantly understand what action you want them to take.
- Tailor CTAs to the specific content on the page. Whether it’s a blog post, landing page or email, the CTA should seamlessly connect with the surrounding context.
- Position your CTAs strategically. They should be prominently displayed and easily noticeable, guiding visitors without intruding.
- Create a sense of urgency. Encourage immediate action by incorporating language that instils a sense of urgency. Phrases like “Limited Time Offer” or “Act Now” can prompt quicker responses.
6. Have an active social presence
Social media platforms are bustling hubs of activity where your target audience spends a significant portion of their online time. Cultivating a social media presence allows you to meet your audience where they are, fostering a direct line of communication.
Moreover, the integration of shopping features directly into social media platforms transforms them into seamless shopping experiences. Nearly half of Instagram users shop weekly through the platform.
Also, the US social commerce sales continue to grow each year and are expected to reach $79.64 billion by 2025.
7. Build a brand community
Four in five customers consider communities important to how engaged they are with a brand.
A strong community fosters a sense of belonging and loyalty among members. When customers feel connected to your brand and each other, they are more likely to remain loyal over the long term.
Also, satisfied community members often share their positive experiences with others, expanding your brand’s reach without additional marketing efforts.
For example, Nike’s community for runners is a digital space where individuals share their running journeys, accomplishments and challenges.
By strategically building and nurturing a community, you not only enhance retention and spur referrals but also create a space where your brand becomes an integral part of your customers’ lives.
8. Conduct A/B tests
A/B testing systematically compares two versions of a webpage, email or other content to determine which performs better.
Examples of elements to A/B test:
- CTAs: The language, colour, size and placement of CTAs can significantly impact user engagement. A/B testing allows you to discover which variations prompt the desired actions.
- Headlines: Crafting compelling headlines is an art. Test different versions to identify which headlines resonate best with your audience, whether they are more drawn to clarity, humour, urgency or curiosity.
- Images: Test different images to understand your audience’s visual preferences. This could include product images, lifestyle shots or graphics.
With Matomo’s A/B testing feature, you can test various elements to see which is successful in converting visitors or moving them to the next stage of the conversion funnel.
9. Leverage social proof
In an era where consumers are inundated with choices, the opinions, reviews and endorsements of others serve as beacons, guiding potential customers through the decision-making process.
Simply put — when people see that others have had positive experiences with your brand, it instils trust and confidence.
You can proactively gather social proof and display it prominently across your marketing channels. Here are some examples of social proof you can leverage:
- Customer reviews: Positive reviews and testimonials from satisfied customers serve as authentic endorsements of your products or services.
- Case studies: In-depth case studies that showcase successful collaborations or solutions provided to clients offer a detailed narrative of your brand’s capabilities. These are particularly effective in B2B scenarios or for complex products and services.
- User-generated content: Encourage customers to share their experiences. This could include photos, videos or posts on social media platforms, providing a dynamic and genuine portrayal of your brand.
- Influencer endorsements: Collaborating with influencers in your industry or niche can amplify your social proof. When influencers vouch for your products or services, their followers are more likely to take notice.
10. Measure and analyse performance
This is a continuous loop of refinement, where you should use analysis and data-driven insights to guide your conversion funnel optimisation efforts.
Here’s a systematic approach you can take:
- Identify the path users take on your site using a feature like Users Flow.
- Map the customer journey using a Funnels feature like the one in Matomo.
- Identify the metrics that align with your conversion goals at each stage of the funnel, such as website traffic, conversion rates, click-through rates and customer acquisition costs.
- Assess conversion rates at different stages of the funnel. Identify areas with significant drop-offs and investigate factors that might contribute to the decline.
- Use heatmaps and session recordings to see first-hand how users interact with your site.
- Create an experiment to test and improve a specific area within your funnel using insights from the heatmaps and session recordings.
- A/B test, analyse the results to understand which variations performed better. Use this data to refine elements within your funnel.
See how Concrete CMS 3x their leads with conversion optimisation.
Conclusion
The customer journey is not linear. However, it involves a few specific stages your audience will go through — from first learning about your product or services to considering whether to try it. The goal is to turn them into happy and loyal customers.
In this article, we went over strategies and practical tips you can use to guide customers through the conversion funnel. From segmenting your audience to capturing leads, optimising landing pages and running A/B tests, there are steps you can take to ensure your audience will move to the next stage.
And of course, you have to continuously measure and analyse your performance. That’s how you know whether you’re heading in the right direction and, if not, where to correct your course.
For that, you need a robust web analytics solution with conversion optimisation features. Try Matomo free for 21 days and start optimising your conversion funnel—no credit card required.
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Top Conversion Metrics to Track in 2024
22 janvier 2024, par Erin2023 boasts ~2.64 billion online shoppers worldwide; that’s more than a third of the global population. With these numbers on an upward trajectory in 2024, conversion metrics are more important than ever to help marketers optimise the online shopping experience.
In this article, we’ll provide predictions for the most important conversion metrics you should keep track of in 2024. We’ll also examine how social media can make or break your brand engagement strategy. Keep reading to stay ahead of the competition for 2024 and gain tips and tricks for improving conversion performance.
What are conversion metrics?
In technical terms, conversion metrics are the quantifiable measurements used to track the success of specific outcomes on a website or marketing campaign. Conversion metrics demonstrate how well your website prompts visitors to take desirable actions, like signing up for a newsletter, making a purchase, or filling out a form, for instance.
Let’s say you’re running a lemonade stand, and you want to compare the number of cups sold to the number of people who approached your stand (your conversion rate). This ratio of cups sold to the total number of people can help you reassess your sales approach. If the ratio is low, you might reconsider your approach; if it’s high, you can analyse what makes your technique successful and double down.
In 2023, we saw the average conversion rate for online shopping grow by 5.53% compared to the previous year. An increase in conversion rate typically indicates a higher percentage of website visitors converting to buyers. It can also be a good sign for marketing teams that marketing campaigns are more effective, and website experiences are more user-friendly than the previous year.
Conversion metrics are a marketers’ bread and butter. Whether it’s through measuring the efficacy of campaigns, honing in on the most effective marketing channels or understanding customer behaviour — don’t underestimate the power of conversion metrics.
Conversion rate vs. conversion value
Before we dive into the top conversion metrics to track in 2024, let’s clear up any confusion about the difference between conversion rate and conversion value. Conversion rate is a metric that measures the ratio of website visitors/users who complete a conversion action to the total number of website visitors/users. Conversion rates are communicated as percentages.
A conversion action can mean many different things depending on your product or service. Some examples of conversion actions that website visitors can take include:
- Making a purchase
- Filling out a form
- Subscribing to a newsletter
- Any other predefined goal
Conversion rate is arguably one of the most valuable conversion metrics if you want to pinpoint areas for improvement in your marketing strategy and user experience (UX).
A good conversion rate completely depends on the type of conversion being measured. Shopify has reported that the average e-commerce conversion rate will be 2.5%-3% in 2023, so if you fall anywhere in this range, you’re in good shape. Below is a visual aid for how you can calculate conversion rate depending on which conversion actions you decide to track:
Conversion value is also a quantifiable metric, but there’s a key difference: conversion value assigns a numerical value to each conversion based on the monetary value of the completed conversion action. Conversion value is not calculated with a formula but is assigned based on revenue generated from the conversion. Conversion value is important for calculating marketing efforts’ return on investment (ROI) and is often used to allocate marketing budgets better.
Both conversion rate and conversion value are vital metrics in digital marketing. When used in tandem, they can provide a holistic perspective on your marketing efforts’ financial impact and success.
9 important conversion metrics to track in 2024
Based on research and results from 2023, we have compiled this list of predictions for the most important metrics to track in 2024.
1. Conversion rate
To start things out strong, we’ve got the timeless and indispensable conversion rate. As we discussed in the previous section, conversion rate measures how successfully your website convinces visitors to take important actions, like making purchases or signing up for newsletters.
An easy-to-use web analytics solution like Matomo can help in tracking conversion rates. Matomo automatically calculates conversion rates of individual pages, overall website and on a goal-by-goal basis. So you can compare the conversion rate of your newsletter sign up goal vs a form submission goal on your site and see what is underperforming and requires improvement.
In the example above in Matomo, it’s clear that our goal of getting users to comment is not doing well, with only a 0.03% conversion rate. To improve our website’s overall conversion rate, we should focus our efforts on improving the user commenting experience.
For 2024, we predict that the conversion rate will be just as important to track as in 2023.
2. Average visit duration
This key metric tracks how long users spend on your website. A session typically starts when a user lands on your website and ends when they close the browser or have been inactive for some time (~30 minutes). Tracking the average visit duration can help you determine how well your content captures users’ attention or how engaged users are when navigating your website.
Average Visit Duration = Total Time Spent / Number of Visits
Web analytics tools like Matomo help in monitoring conversion rate metrics like average visit duration. Timestamps are assigned to each interaction within a visit, so that average visit duration can be calculated. Analysing website visit information like average visit duration allows you to evaluate the relevance of your content with your target audience.
3. Starter rate
If your business relies on getting leads through forms, paying attention to Form Analytics is crucial for improving conversion rates. The “starter rate” metric is particularly important—it indicates the number of who people start filling out the form, after seeing it.
When you’re working to increase conversion rates and capture more leads, keeping an eye on the starter rate helps you understand where users might encounter issues or lose interest early in the form-filling process. Addressing these issues can simplify the form-filling experience and increase the likelihood of successful lead captures.
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Concrete CMS tripled their leads using Form Analytics in Matomo—see how in their case study.
4. Bounce rate
Bounce rate reflects the percentage of visitors who exit your site after interacting with a single page. Bounce rate is an important metric for understanding how relevant your content is to visitors or how optimised your user experience is. A high bounce rate can indicate that visitors are having trouble navigating your website or not finding what they’re looking for.
Matomo automatically calculates bounce rate on each page and for your overall website.
Bounce Rate = (# of Single-Page Sessions / Total # of Sessions) * 100
5. Cost-per-conversion
This metric quantifies the average cost incurred for each conversion action (i.e., sale, acquired lead, sign-up, etc.). Marketers use cost-per-conversion to assess the cost efficiency of a marketing campaign. You want to aim for a lower cost-per-conversion, meaning your advertising efforts aren’t breaking the bank. A high cost-per-conversion could be acceptable in luxury industries, but it often indicates a low marketing ROI.
Cost-per-Conversion = Ad Spend / # of Conversions
By connecting your Matomo with Google Ads through Advertising Conversion Export feature in Matomo, you can keep tabs on your conversions right within the advertising platform. This feature also works with Microsoft Advertising and Yandex Ads.
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6. Average order value (AOV)
AOV is a conversion metric that calculates the average monetary value of each order. AOV is crucial for helping e-commerce businesses understand the value of their transactions. A high AOV means buyers spend more per transaction and could be more easily influenced by upselling or cross-selling. Low AOV isn’t necessarily bad — you can compensate for a low AOV by boosting transaction volume.
AOV = Total Revenue / Total # of Orders
Matomo automatically tracks important e-commerce metrics such as AOV, the percentage of visits with abandoned carts and the conversion rate for e-commerce orders.
7. Exit rate
Exit rate measures the percentage of visitors who leave a specific webpage after viewing it. Exit rate differs from bounce rate in that it focuses on the last page visitors view before leaving the site. A high exit rate should be examined to identify issues with visitors abandoning the specific page.
Exit Rate = (# of Exits from a Page / Total # of Pageviews for that Page) * 100
In the Matomo report above, it’s clear that 77% of visits to the diving page ended after viewing it (exit rate), while 23% continued exploring.
On the other hand, our products page shows a lower exit rate at 36%, suggesting that more visitors continue navigating through the site after checking out the products.
How to improve your conversion performance
If you’re curious about improving your conversion performance, this section is designed to guide you through that exact process.
Understand your target audience and their behaviour
You may need to return to the drawing board if you’re noticing high bounce rates or a lack of brand engagement. In-depth audience analysis can unveil user demographics, preferences and behaviours. This type of user data is crucial for building user personas, segmenting your visitors and targeting marketing campaigns accordingly.
You can segment your website visitors in a number of web analytics solutions, but for the example below, we’ll look at segmenting in Matomo.
In this instance, we’ve segmented visitors by mobile users. This helps us see how mobile users are doing with our newsletter signup goal and identify the countries where they convert the most. It also shows how well mobile users are doing with our conversion goal over time.
It’s clear that our mobile users are converting at a very low rate—just 0.01%. This suggests there’s room for improvement in the mobile experience on our site.
Optimise website design, landing pages, page loading speed and UX
A slow page loading speed can result in high exit rates, user dissatisfaction and lost revenue. Advanced web analytics solutions like Matomo, which provides heatmaps and session recordings, can help you find problems in your website design and understand how users interact with it.
Making a website that focuses on users and has an easy-to-follow layout will make the user experience smooth and enjoyable.
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Create compelling calls-to-action (CTA)
Research shows that a strategically placed and relevant CTA can significantly increase your revenue. CTAs guide prospects toward conversion and must have a compelling and clear message.
You can optimise CTAs by analysing how users interact with them — this helps you tailor them to better resonate with your target audience.
A/B testing
A/B testing can improve your conversion performance by allowing you to experiment with different versions of a web page. By comparing the impact of different web page elements on conversions, you can optimise your website with confidence.
Key conversion metrics takeaways
Whether understanding user behaviour to develop a more intuitive user experience or guessing which marketing channel is the most effective, conversion metrics can be a marketer’s best friend. Conversion metrics help you save time, money and headaches when making your campaigns and website as effective as possible.
Make improving conversion rates easier with Matomo, a user-friendly all-in-one solution. Matomo ensures reliable insights by delivering accurate data while prioritising compliance and privacy.
Get quality insights from your conversion metrics by trying Matomo free for 21 days. No credit card required.
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Marketing Cohort Analysis : How To Do It (With Examples)
12 janvier 2024, par ErinThe better you understand your customers, the more effective your marketing will become.
The good news is you don’t need to run expensive focus groups to learn much about how your customers behave. Instead, you can run a marketing cohort analysis using data from your website analytics.
A marketing cohort groups your users by certain traits and allows you to drill down to discover why they take the actions on your website they do.
In this article, we’ll explain what a marketing cohort analysis is, show you what you can achieve with this analytical technique and provide a step-by-step guide to pulling it off.
What is cohort analysis in marketing?
A marketing cohort analysis is a form of behavioural analytics where you analyse the behavioural patterns of users who share a similar trait to better understand their actions.
These shared traits could be anything like the date they signed up for your product, users who bought your service through a paid ad or email subscribers from the United Kingdom.
It’s a fantastic way to improve your marketing efforts, allowing you to better understand complex user behaviours, personalise campaigns accordingly and improve your ROI.
You can run marketing analysis using an analytics platform like Google Analytics or Matomo. With these platforms, you can measure how cohorts perform using traffic, engagement and conversion metrics.
There are two types of cohort analysis: acquisition-based cohort analysis and behavioural-based cohort analysis.
Acquisition-based cohort analysis
An acquisition-based cohort divides users by the date they purchased your product or service and tracks their behaviour afterward.
For example, one cohort could be all the users who signed up for your product in November. Another could be the users who signed up for your product in October.
You could then run a cohort analysis to see how the behaviour of the two cohorts differed.
Did the November cohort show higher engagement rates, increased frequency of visits post-acquisition or quicker conversions compared to the October cohort? Analysing these cohorts can help with refining marketing strategies, optimising user experiences and improving retention and conversion rates.
As you can see from the example, acquisition-based cohorts are a great way to track the initial acquisition and how user behaviour evolves post-acquisition.
Behavioural-based cohort analysis
A behavioural-based cohort divides users by their actions on your site. That could be their bounce rate, the number of actions they took on your site, their average time on site and more.
Behavioural cohort analysis gives you a much deeper understanding of user behaviour and how they interact with your website.
What can you achieve with a marketing cohort analysis?
A marketing cohort analysis is a valuable tool that can help marketers and product teams achieve the following goals:
Understand which customers churn and why
Acquisition and behavioural cohort analyses help marketing teams understand when and why customers leave. This is one of the most common goals of a marketing cohort analysis.
Learn which customers are most valuable
Want to find out which channels create the most valuable customers or what actions customers take that increase their loyalty? You can use a cohort analysis to do just that.
For example, you may find out you retain users who signed up via direct traffic better than those that signed up from an ad campaign.
Discover how to improve your product
You can even use cohort analysis to identify opportunities to improve your website and track the impact of your changes. For example, you could see how visitor behaviour changes after a website refresh or whether visitors who take a certain action make more purchases.
Find out how to improve your marketing campaign
A marketing cohort analysis makes it easy to find out which campaigns generate the best and most profitable customers. For example, you can run a cohort analysis to determine which channel (PPC ads, organic search, social media, etc.) generates customers with the lowest churn rate.
If a certain ad campaign generates the low-churn customers, you can allocate a budget accordingly. Alternatively, if customers from another ad campaign churn quickly, you can look into why that may be the case and optimise your campaigns to improve them.
Measure the impact of changes
You can use a behavioural cohort analysis to understand what impact changes to your website or product have on active users.
If you introduced a pricing page to your website, for instance, you could analyse the behaviour of visitors who interacted with that page compared to those who didn’t, using behavioural cohort analysis to gauge the impact of these website changes on engagemen or conversions.
The problem with cohort analysis in Google Analytics
Google Analytics is often the first platform marketers turn to when they want to run a cohort analysis. While it’s a free solution, it’s not the most accurate or easy to use and users often encounter various issues.
For starters, Google Analytics can’t process user visitor data if they reject cookies. This can lead to an inaccurate view of traffic and compromise the reliability of your insights.
In addition, GA is also known for sampling data, meaning it provides a subset rather than the complete dataset. Without the complete view of your website’s performance, you might make the wrong decisions, leading to less effective campaigns, missed opportunities and difficulties in reaching marketing goals.
How to analyse cohorts with Matomo
Luckily, there is an alternative to Google Analytics.
As the leading open-source web analytics solution, Matomo offers a robust option for cohort analysis. With its 100% accurate data, thanks to the absence of sampling, and its privacy-friendly tracking, users can rely on the data without resorting to guesswork. It is a premium feature included with our Matomo Cloud or available to purchase on the Matomo Marketplace for Matomo On-Premise users.
Below, we’ll show how you can run a marketing cohort analysis using Matomo.
Set a goal
Setting a goal is the first step in running a cohort analysis with any platform. Define what you want to achieve from your analysis and choose the metrics you want to measure.
For example, you may want to improve your customer retention rate over the first 90 days.
Define cohorts
Next, create cohorts by defining segmentation criteria. As we’ve discussed above, this could be acquisition-based or behavioural.
Matomo makes it easy to define cohorts and create charts.
In the sidebar menu, click Visitors > Cohorts. You’ll immediately see Matomo’s standard cohort report (something like the one below).
In the example above, we’ve created cohorts by bounce rate.
You can view cohorts by weekly, monthly or yearly periods using the date selector and change the metric using the dropdown. Other metrics you can analyse cohorts by include:
- Unique visitors
- Return visitors
- Conversion rates
- Revenue
- Actions per visit
Change the data selection to create your desired cohort, and Matomo will automatically generate the report.
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Analyse your cohort chart
Cohort charts can be intimidating initially, but they are pretty easy to understand and packed with insights.
Here’s an example of an acquisition-based cohort chart from Matomo looking at the percentage of returning visitors:
Cohorts run vertically. The oldest cohort (visitors between February 13 – 19) is at the top of the chart, with the newest cohort (April 17 – 23) at the bottom.
The period of time runs horizontally — daily in this case. The cells show the corresponding value for the metric we’re plotting (the percentage of returning visitors).
For example, 98.69% of visitors who landed on your site between February 13 – 19, returned two weeks later.
Usually, running one cohort analysis isn’t enough to identify a problem or find a solution. That’s why comparing several cohort analyses or digging deeper using segmentation is important.
Segment your cohort chart
Matomo lets you dig deeper by segmenting each cohort to examine their behaviour’s specifics. You can do this from the cohort report by clicking the segmented visitor log icon in the relevant row.
Segmenting cohorts lets you understand why users behave the way they do. For example, suppose you find that users you purchased on Black Friday don’t return to your site often. In that case, you may want to rethink your offers for next year to target an audience with potentially better customer lifetime value.
Start using Matomo for marketing cohort analysis
A marketing cohort analysis can teach you a lot about your customers and the health of your business. But you need the right tools to succeed.
Matomo provides an effective and privacy-first way to run your analysis. You can create custom customer segments based on almost anything, from demographics and geography to referral sources and user behaviour.
Our custom cohort analysis reports and colour-coded visualisations make it easy to analyse cohorts and spot patterns. Best of all, the data is 100% accurate. Unlike other web analytics solution or cohort analysis tools, we don’t sample data.
Find out how you can use Matomo to run marketing cohort analysis by trialling us free for 21 days. No credit card required.
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A Complete Guide to Metrics in Google Analytics
11 janvier 2024, par ErinThere’s no denying that Google Analytics is the most popular web analytics solution today. Many marketers choose it to understand user behaviour. But when it offers so many different types of metrics, it can be overwhelming to choose which ones to focus on. In this article, we’ll dive into how metrics work in Google Analytics 4 and how to decide which metrics may be most useful to you, depending on your analytics needs.
However, there are alternative web analytics solutions that can provide more accurate data and supplement GA’s existing features. Keep reading to learn how to overcome Google Analytics limitations so you can get the more out of your web analytics.
What is a metric in Google Analytics?
In Google Analytics, a metric is a quantitative measurement or numerical data that provides insights into specific aspects of user behaviour. Metrics represent the counts or sums of user interactions, events or other data points. You can use GA metrics to better understand how people engage with a website or mobile app.
Unlike the previous Universal Analytics (the previous version of GA), GA4 is event-centric and has automated and simplified the event tracking process. Compared to Universal Analytics, GA4 is more user-centric and lets you hone in on individual user journeys. Some examples of common key metrics in GA4 are:
- Sessions: A group of user interactions on your website that occur within a specific time period. A session concludes when there is no user activity for 30 minutes.
- Total Users: The cumulative count of individuals who accessed your site within a specified date range.
- Engagement Rate: The percentage of visits to your website or app that included engagement (e.g., one more pageview, one or more conversion, etc.), determined by dividing engaged sessions by sessions.
Metrics are invaluable when it comes to website and conversion optimisation. Whether you’re on the marketing team, creating content or designing web pages, understanding how your users interact with your digital platforms is essential.
GA4 metrics vs. dimensions
GA4 uses metrics to discuss quantitative measurements and dimensions as qualitative descriptors that provide additional context to metrics. To make things crystal clear, here are some examples of how metrics and dimensions are used together:
- “Session duration” = metric, “device type” = dimension
- In this situation, the dimension can segment the data by device type so you can optimise the user experience for different devices.
- “Bounce rate” = metric, “traffic source/medium” = dimension
- Here, the dimension helps you segment by traffic source to understand how different acquisition channels are performing.
- “Conversion rate” = metric, “Landing page” = dimension
- When the conversion rate data is segmented by landing page, you can better see the most effective landing pages.
You can get into the nitty gritty of granular analysis by combining metrics and dimensions to better understand specific user interactions.
How do Google Analytics metrics work?
Before diving into the most important metrics you should track, let’s review how metrics in GA4 work.
- Tracking code implementation
The process begins with implementing Google Analytics 4 tracking code into the HTML of web pages. This tracking code is JavaScript added to each website page — it collects data related to user interactions, events and other important tidbits.
- Data collection
As users interact with the website or app, the Google Analytics 4 tracking code captures various data points (i.e., page views, clicks, form submissions, custom events, etc.). This raw data is compiled and sent to Google Analytics servers for processing.
- Data processing algorithms
When the data reaches Google Analytics servers, data processing algorithms come into play. These algorithms analyse the incoming raw data to identify the dataset’s trends, relationships and patterns. This part of the process involves cleaning and organising the data.
- Segmentation and customisation
As discussed in the previous section, Google Analytics 4 allows for segmentation and customisation of data with dimensions. To analyse specific data groups, you can define segments based on various dimensions (e.g., traffic source, device type). Custom events and user properties can also be defined to tailor the tracking to the unique needs of your website or app.
- Report generation
Google Analytics 4 can make comprehensive reports and dashboards based on the processed and segmented data. These reports, often in the form of graphs and charts, help identify patterns and trends in the data.
What are the most important Google Analytics metrics to track?
In this section, we’ll identify and define key metrics for marketing teams to track in Google Analytics 4.
- Pageviews are the total number of times a specific page or screen on your website or app is viewed by visitors. Pageviews are calculated each time a web page is loaded or reloaded in a browser. You can use this metric to measure the popularity of certain content on your website and what users are interested in.
- Event tracking monitors user interactions with content on a website or app (i.e., clicks, downloads, video views, etc.). Event tracking provides detailed insights into user engagement so you can better understand how users interact with dynamic content.
- Retention rate can be analysed with a pre-made overview report that Google Analytics 4 provides. This user metric measures the percentage of visitors who return to your website or app after their first visit within a specific time period. Retention rate = (users with subsequent visits / total users in the initial cohort) x 100. Use this information to understand how relevant or effective your content, user experience and marketing efforts are in retaining visitors. You probably have more loyal/returning buyers if you have a high retention rate.
- Average session duration calculates the average time users spend on your website or app per session. Average session duration = total duration of all sessions / # of sessions. A high average session duration indicates how interested and engaged users are with your content.
- Site searches and search queries on your website are automatically tracked by Google Analytics 4. These metrics include search terms, number of searches and user engagement post-search. You can use site search metrics to better understand user intent and refine content based on users’ searches.
- Entrance and exit pages show where users first enter and leave your site. This metric is calculated by the percentage of sessions that start or end on a specific page. Knowing where users are entering and leaving your site can help identify places for content optimisation.
- Device and browser info includes data about which devices and browsers websites or apps visitors use. This is another metric that Google Analytics 4 automatically collects and categorises during user sessions. You can use this data to improve the user experience on relevant devices and browsers.
- Bounce rate is the percentage of single-page sessions where users leave your site or app without interacting further. Bounce rate = (# of single-page sessions / total # of sessions) x 100. Bounce rate is useful for determining how effective your landing pages are — pages with high bounce rates can be tweaked and optimised to enhance user engagement.
Examples of how Matomo can elevate your web analytics
Although Google Analytics is a powerful tool for understanding user behaviour, it also has privacy concerns, limitations and a list of issues. Another web analytics solution like Matomo can help fill those gaps so you can get the most out of your analytics.
- Cross-verify and validate your observations from Google Analytics by comparing data from Matomo’s Heatmaps and Session Recordings for the same pages. This process grants you access to these advanced features that GA4 does not offer.
- Matomo provides you with greater accuracy thanks to its privacy-friendly design. Unlike GA4, Matomo can be configured to operate without cookies. This means increased accuracy without intrusive cookie consent screens interrupting the user experience. It’s a win for you and for your users. Matomo also doesn’t apply data sampling so you can rest assured that the data you see is 100% accurate.
- Unlike GA4, Matomo offers direct access to customer support so you can save time sifting through community forum threads and online documentation. Gain personalised assistance and guidance for your analytics questions, and resolve issues efficiently.
- Matomo’s Form Analytics and Media Analytics extend your analytics capabilities beyond just pageviews and event tracking.
Tracking user interactions with forms can tell you which fields users struggle with, common drop-off points, in addition to which parts of the form successfully guide visitors towards submission.
See first-hand how Concrete CMS 3x their leads using Matomo’s Form Analytics.
Media Analytics can provide insight into how users interact with image, video, or audio content on your website. You can use this feature to assess the relevance and popularity of specific content by knowing what your audience is engaged by.
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Final thoughts
Although Google Analytics is a powerful tool on its own, Matomo can elevate your web analytics by offering advanced features, data accuracy and a privacy-friendly design. Don’t play a guessing game with your data — Matomo provides 100% accurate data so you don’t have to rely on AI or machine learning to fill in the gaps. Matomo can be configured cookieless which also provides you with more accurate data and a better user experience.
Lastly, Matomo is fully compliant with some of the world’s strictest privacy regulations like GPDR. You won’t have to sacrifice compliance for accurate, high quality data.
Start your 21-day free trial of Matomo — no credit card required.
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Unveiling GA4 Issues : 8 Questions from a Marketer That GA4 Can’t Answer
8 janvier 2024, par AlexIt’s hard to believe, but Universal Analytics had a lifespan of 11 years, from its announcement in March 2012. Despite occasional criticism, this service established standards for the entire web analytics industry. Many metrics and reports became benchmarks for a whole generation of marketers. It truly was an era.
For instance, a lot of marketers got used to starting each workday by inspecting dashboards and standard traffic reports in the Universal Analytics web interface. There were so, so many of those days. They became so accustomed to Universal Analytics that they would enter reports, manipulate numbers, and play with metrics almost on autopilot, without much thought.
However, six months have passed since the sunset of Universal Analytics – precisely on July 1, 2023, when Google stopped processing requests for resources using the previous version of Google Analytics. The time when data about visitors and their interactions with the website were more clearly structured within the UA paradigm is now in the past. GA4 has brought a plethora of opportunities to marketers, but along with those opportunities came a series of complexities.
GA4 issues
Since its initial announcement in 2020, GA4 has been plagued with errors and inconsistencies. It still has poor and sometimes illogical documentation, numerous restrictions, and peculiar interface solutions. But more importantly, the barrier to entry into web analytics has significantly increased.
If you diligently follow GA4 updates, read the documentation, and possess skills in working with data (SQL and basic statistics), you probably won’t feel any problems – you know how to set up a convenient and efficient environment for your product and marketing data. But what if you’re not that proficient? That’s when issues arise.
In this article, we try to address a series of straightforward questions that less experienced users – marketers, project managers, SEO specialists, and others – want answers to. They have no time to delve into the intricacies of GA4 but seek access to the fundamentals crucial for their functionality.
Previously, in Universal Analytics, they could quickly and conveniently address their issues. Now, the situation has become, to put it mildly, more complex. We’ve identified 8 such questions for which the current version of GA4 either fails to provide answers or implies that answers would require significant enhancements. So, let’s dive into them one by one.
Question 1: What are the most popular traffic sources on my website?
Seemingly a straightforward question. What does GA4 tell us? It responds with a question: “Which traffic source parameter are you interested in?”
Wait, what?
People just want to know which resources bring them the most traffic. Is that really an issue?
Unfortunately, yes. In GA4, there are not one, not two, but three traffic source parameters:
- Session source.
- First User Source – the source of the first session for each user.
- Just the source – determined at the event or conversion level.
If you wanted to open a report and draw conclusions quickly, we have bad news for you. Before you start ranking your traffic sources by popularity, you need to do some mental work on which parameter and in what context you will look. And even when you decide, you’ll need to make a choice in the selection of standard reports: work with the User Acquisition Report or Traffic Acquisition.
Yes, there is a difference between them: the first uses the First User Source parameter, and the second uses the session source. And you need to figure that out too.
Question 2: What is my conversion rate?
This question concerns everyone, and it should be simple, implying a straightforward answer. But no.
In GA4, there are three conversion metrics (yes, three):
- Session conversion – the percentage of sessions with a conversion.
- User conversion – the percentage of users who completed a conversion.
- First-time Purchaser Conversion – the share of active users who made their first purchase.
If the last metric doesn’t interest us much, GA4 users can still choose something from the remaining two. But what’s next? Which parameters to use for comparison? Session source or user source? What if you want to see the conversion rate for a specific event? And how do you do this in analyses rather than in standard reports?
In the end, instead of an answer to a simple question, marketers get a bunch of new questions.
Question 3. Can I trust user and session metrics?
Unfortunately, no. This may boggle the mind of those not well-versed in the mechanics of calculating user and session metrics, but it’s the plain truth: the numbers in GA4 and those in reality may and will differ.
The reason is that GA4 uses the HyperLogLog++ statistical algorithm to count unique values. Without delving into details, it’s a mechanism for approximate estimation of a metric with a certain level of error.
This error level is quite well-documented. For instance, for the Total Users metric, the error level is 1.63% (for a 95% confidence interval). In simple terms, this means that 100,000 users in the GA4 interface equate to 100,000 1.63% in reality.
Furthermore – but this is no surprise to anyone – GA4 samples data. This means that with too large a sample size or when using a large number of parameters, the application will assess your metrics based on a partial sample – let’s say 5, 10, or 30% of the entire population.
It’s a reasonable assumption, but it can (and probably will) surprise marketers – the metrics will deviate from reality. All end-users can do (excluding delving into raw data methodologies) is to take this error level into account in their conclusions.
Question 4. How do I calculate First Click attribution?
You can’t. Unfortunately, as of late, GA4 offers only three attribution models available in the Attribution tab: Last Click, Last Click For Google Ads, and Data Driven. First Click attribution is essential for understanding where and when demand is generated. In the previous version of Google Analytics (and until recently, in the current one), users could quickly apply First Click and other attribution models, compare them, and gain insights. Now, this capability is gone.
Certainly, you can look at the conversion distribution considering the First User Source parameter – this will be some proxy for First Click attribution. However, comparing it with others in the Model Comparison tab won’t be possible. In the context of the GA4 interface, it makes sense to forget about non-standard attribution models.
Question 5. How do I account for intra-session traffic?
Intra-session traffic essentially refers to a change in traffic sources within a session. Imagine a scenario where a user comes to your site organically from Google and, within a minute, comes from an email campaign. In the previous version of Google Analytics, a new session with the traffic source “e-mail” would be created in such a case. But now, the situation has changed.
A session now only ends in the case of a timeout – say, 30 minutes without interaction. This means a session will always have a source from which it started. If a user changes the source within a session (clicks on an ad, from email campaigns, and so on), you won’t know anything about it until they convert. This is a significant blow to intra-session traffic since their contribution to traffic remains virtually unnoticed.
Question 6. How can I account for users who have not consented to the use of third-party cookies?
You can’t. Google Consent Mode settings imply several options when a user rejects the use of 3rd party cookies. In GA4 and BigQuery, depersonalized cookieless pings will be sent. These pings do not contain specific client_id, session_id, or other custom dimensions. As a result, you won’t be able to consider them as users or link the actions of such users together.
Question 7. How can I compare data in explorations with the previous year?
The maximum data retention period for a free GA4 account is 14 months. This means that if the date range is wider, you can only use standard reports. You won’t be able to compare or view cohorts or funnels for periods more than 14 months ago. This makes the product functionality less rich because various report formats in explorations are very convenient for comparing specific metrics in easily digestible reports.
Of course, you always have the option to connect BigQuery and store raw data without limitations, but this process usually requires the involvement of an advanced analyst. And precisely this option is unavailable to most marketers in small teams.
Question 8. Is the data for yesterday accurate?
Unknown. Google declares that data processing in GA4 takes up to 48 hours. And although this process is faster, most users still have room for frustration. And they can be understood.
What does “data processing takes 24-48 hours” mean? When will the data in reports be complete? For yesterday? Or the day before yesterday? Or for all days that were more than two days ago? Unclear. What should marketers tell their managers when they were asked if all the data is in this report? Well, probably all of it… or maybe not… Let’s wait for 48 hours…
Undoubtedly, computational resources and time are needed for data preprocessing and aggregation. It’s okay that data for today will not be up-to-date. And probably not for yesterday either. But people just want to know when they can trust their data. Are they asking for too much: just a note that this report contains all the data sent and processed by Google Analytics?
What should you do?
Credit should be given to the Google team – they have done a lot to enable users to answer these questions in one form or another. For example, you can use data streaming in BigQuery and work with raw data. The entry threshold for this functionality has been significantly lowered. In fact, if you are dissatisfied with the GA4 interface, you can organize your export to BigQuery and create your own reports without (almost) any restrictions.
Another strong option is the widespread launch of GTM Server Side. This allows you to quite freely modify the event model and essentially enrich each hit with various parameters, doing this in a first-party context. This, of course, reduces the harmful impact of most of the limitations described in this text.
But this is not a solution.
The users in question – marketers, managers, developers – they do not want or do not have the time for a deep dive into the issue. And they want simple answers to simple (it seemed) questions. And for now, unfortunately, GA4 is more of a professional tool for analysts than a convenient instrument for generating insights for not very advanced users.
Why is this such a serious issue?
The thing is – and this is crucial – over the past 10 years, Google has managed to create a sort of GA-bubble for marketers. Many of them have become so accustomed to Google Analytics that when faced with another issue, they don’t venture to explore alternative solutions but attempt to solve it on their own. And almost always, this turns out to be expensive and inconvenient.
However, with the latest updates to GA4, it is becoming increasingly evident that this application is struggling to address even the most basic questions from users. And these questions are not fantastically complex. Much of what was described in this article is not an unsolvable mystery and is successfully addressed by other analytics services.
Let’s try to answer some of the questions described from the perspective of Matomo.
Question 1: What are the most popular traffic sources? [Solved]
In the Acquisition panel, you will find at least three easily identifiable reports – for traffic channels (All Channels), sources (Websites), and campaigns (Campaigns).
With these, you can quickly and easily answer the question about the most popular traffic sources, and if needed, delve into more detailed information, such as landing pages.
Question 2: What is my conversion rate? [Solved]
Under Goals in Matomo, you’ll easily find the overall conversion rate for your site. Below that you’ll have access to the conversion rate of each goal you’ve set in your Matomo instance.
Question 3: Can I trust user and session metrics? [Solved]
Yes. With Matomo, you’re guaranteed 100% accurate data. Matomo does not apply sampling, does not employ specific statistical algorithms, or any analogs of threshold values. Yes, it is possible, and it’s perfectly normal. If you see a metric in the visits or users field, it accurately represents reality by 100%.
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Question 4: How do I calculate First Click attribution? [Solved]
You can do this in the same section where the other 5 attribution models, available in Matomo, are calculated – in the Multi Attribution section.
You can choose a specific conversion and, in a few clicks, calculate and compare up to 3 marketing attribution models. This means you don’t have to spend several days digging through documentation trying to understand how a particular model is calculated. Have a question – get an answer.
Question 5: How do I account for intra-session traffic? [Solved]
Matomo creates a new visit when a user changes a campaign. This means that you will accurately capture all relevant traffic if it is adequately tagged. No campaigns will be lost within a visit, as they will have a new utm_campaign parameter.
This is a crucial point because when the Referrer changes, a new visit is not created, but the key lies in something else – accounting for all available traffic becomes your responsibility and depends on how you tag it.
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Question 6: How can I account for users who have not consented to the use of third-party cookies? [Solved]
Google Analytics requires users to accept a cookie consent banner with “analytics_storage=granted” to track them. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports.
Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen. This is achieved through a config_id variable (the user identifier equivalent which is updating once a day).
This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not.
Question 7: How can I compare data in explorations with the previous year? [Solved]
There is no limitation on data retention for your aggregated reports in Matomo. The essence of Matomo experience lies in the reporting data, and consequently, retaining reports indefinitely is a viable option. So you can compare data for any timeframe. 7
- Session source.
