customer journey google analytics

• Campaigns & brand activation
• Consulting & transformation
• Insights library

Analysing user journeys within Google Analytics

Richard Robertson

6th October 2020

*This article is about Universal Analytics which will sunset on 1 July 2023 and be replaced with Google Analytics 4. You can find our GA4 content  here .

In its purest form, a user journey is the journey a user takes on your website to perform an action. Understanding these journeys is critical for optimising your website as identifying them also highlights any blockers that could be causing you to lose revenue.

On larger websites, there are countless ways in which a user can navigate around and, without a way to track these routes, it can be difficult to optimise them efficiently. Thankfully, with the help of Google Analytics, these can be analysed with ease if you know the right places to look.

Google Analytics has many great features and reports, but certain pieces of analysis can be more difficult to produce from the standard reports. This post will breakdown the different methods and features that can be explored in Google Analytics to support you in discovering, mapping and troubleshooting user journeys on your website.

Segmentation

Segments allow you to group sessions or users based on specific behaviours performed. Segments enhance your ability to find insightful data on your users’ journeys when applied to reports, especially the ones I will be discussing with you today. Aside from enhancing your reports, you can also use segments themselves to analyse user journeys – we can break this down into two main functions.

The first function is to group sessions based on a specific interaction. For instance, I could create a segment for sessions that had signed up to our newsletter. Utilising the ‘All Pages’ report, I can see the exact pages users visited during converting visits. Additionally, if I had content groupings set up, I’d be able to quickly identify the types of content read before my users went on to sign-up to my newsletter. This information can be passed to the content team to prioritise the creation of articles that are likely to assist us with driving more newsletter sign-ups.

The second function is to create a segment with the sequencing rules, essentially allowing you to build a custom funnel without the ability to see drop off along the steps. One of the ways to utilise this feature is to create an open funnel with the first and last step. This way, using the ‘All Pages’ Report, you can exclude those two steps and analyse the pages viewed between these steps.

Behaviour Flow

Behaviour flow visualises the paths that users most-frequently take on your website with the ability to change the granularity to gain insights into the behaviours that are important to you. You can find out which pages users are frequently navigating between or if users are diverting journeys.

User Explorer

If you’re interested in looking at a specific user’s journey, User Explorer is the report for you. To use this feature, you’re first required to enable the User-ID feature in your property settings if you have not done so already. Once set up, you can find this report in Audience > User Explorer.

The User Explorer report stitches together the pages and events an individual user has performed on your site, displaying them as a timeline that can be analysed.

This can be harder for larger sites, due to the volume of users; however, using segments, you can filter down the list to find individuals that have done specific actions on your site. For instance, you can segment users who have completed very particular activities to discover if there’s any commonalities between similar users.

Previous Page Path

The Previous Page Path dimension is an excellent tool for analysing journeys. The primary purpose of using the Previous Page Path is for looking at how users are navigating to a specific page. This is handy for pages with multiple entrance points to a page like “Contact Us”, allowing you to analyse which pages are driving people to contact you.

This will highlight irrelevant pages and will assist you to  find pages where users are struggling to find the information they are after.

Checkout Behaviour/Shopping Behaviour

Checkout Behaviour/Shopping Behaviour are both available once you have set up enhanced ecommerce tracking on your website. Due to this, it’s one of the key ways to analyse ecommerce journeys in Google Analytics. You can find this report in Conversions > Ecommerce > Shopping Behaviour/Checkout Behaviour.

Shopping behaviour is a quick way to understand the health of your ecommerce journey. It provides a snapshot of your users’ shopping experience and gives you a breakdown of the percentage of users that have gone from viewing a product, all the way to purchasing a product on your website. You can build segments from any of the steps to help you analyse users in that funnel or even create segments from the drop-offs to understand why those users haven’t moved on to subsequent steps.

Checkout Behaviour focuses specifically on the checkout journey itself, highlighting any potential issues your users might be having once they’ve committed to purchasing a product from you by showing at which page they drop off at.

Site Search

Site Search is a custom feature of Google Analytics and uses query parameters to map internal search terms and categories. It must be enabled first which you can do in the view settings.

Though it isn’t a traditional way to analyse user journeys, it helps to analyse which terms users are searching internally. This can help you find gaps in content by looking at the keywords with low clickthrough rate, suggesting there wasn’t any content that the user wanted to read.

You can also use it to discover content that users are struggling to find whilst navigating your site. You can deep dive these by grouping users that have searched a specific term in a segment and analysing which pages they visited.

Custom Funnels

Custom funnels let you build a user journey and monitor the drop-off between steps. There are several ways you can build these in Google Analytics. As mentioned above, you can use a segment utilising the sequence feature. While this won’t allow you to monitor drop-off from your funnel, this feature can be used via the Google Analytics Reporting API and in Google Data Studio, unlike the options below. If you’re fortunate enough to have Google Analytics 360 within your organisation, then building custom funnels and analysing drop-off is easier.

Custom Reports – Funnel Report Type

Custom Funnels are one of the easiest ways to map and analyse specific user journeys within Google Analytics. This feature allows you to visualise the journey a user takes to complete an action on your site. Unlike the Behaviour Flow feature, you have to set up the journey you would like to analyse.

This feature is fully customisable, allowing you to choose whether the user must perform the actions during the same session or across multiple sessions. You can also choose if the funnel is open or closed, meaning users must perform each subsequent step or they can join further along. Furthermore, there’s the option to decide if you would like users to be able to divert between steps, or whether each step must be followed by the next.

You can even build segments based on users who have dropped off at certain points in the funnel, which helps to spot trends that have caused users to divert from their journey.

There are limitations to this feature; you can only have up to five stages in each custom funnel and each of these steps is limited to five rules.

Advanced Analysis

Advanced Analysis is another 360-exclusive feature. It was released in May 2018 and, at the time of writing this post, is still in beta. It’s Google’s answer to the workspaces available in Adobe Analytics, allowing a user to build fully customised reporting for a quick and easy way to delve into the data and derive insights.

Advanced Analysis has a few different report types. The one we’re focusing on for analysing user journeys is ‘Funnel Analysis’. It’s very similar to Custom Funnels with additional features that make this an incredibly powerful feature – one being that you can choose to analyse up to 10 steps rather than five. But the real advantage is the ability to use segments and dimensions to further breakdown your funnel.

When choosing between Custom Funnels and Advanced Analysis, it all depends on how in-depth you want to go with the analysis. Custom Funnels are fantastic as a start, but if you want to really analyse the user types that are dropping off, Advanced Analysis is the tool for you.

There are tons of features in Google Analytics and even more ways of using them to analyse your users. By understanding the limitations and features of them you’ll be able to use the right one to gather the insights you want to drive. User journeys can be complex, but by using the features above you’ll be able to improve user experience on your site and drive increased revenue for your business.

If you have any questions about this post, or want to talk more about user journeys, please leave a comment below and I’ll get back to you.

Comments are closed.

Very good analysis.

Kabza De Small

Thanks so much

You might also be interested in

Blog · Data

A guide to Cookie Consent with Tag Management Systems

The future of analytics in an opt-in world, join the inner circle.

Industry leading insights direct to your inbox every month.

Introducing the new Google Analytics

Oct 14, 2020

[[read-time]] min read

Millions of businesses, large and small, rely on Google Analytics to understand customer preferences and create better experiences for them. With more commerce moving online and businesses under increased pressure to make every marketing dollar count, insights from digital analytics tools are even more critical.

But with major shifts in consumer behavior and privacy-driven changes to longtime industry standards, current approaches to analytics aren’t keeping pace. In a survey from Forrester Consulting, marketers said that improving their use of analytics is a top priority, and that existing solutions make it difficult to get a complete view of the customer and derive insights from their data.

To help you get better ROI from your marketing for the long term, we're creating a new, more intelligent Google Analytics that builds on the foundation of the App + Web property we introduced in beta last year. It has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms. It’s privacy-centric by design, so you can rely on Analytics even as industry changes like restrictions on cookies and identifiers create gaps in your data. The new Google Analytics will give you the essential insights you need to be ready for what’s next.

Smarter insights to improve your marketing decisions and get better ROI

By applying Google’s advanced machine learning models, the new Analytics can automatically alert you to significant trends in your data - like products seeing rising demand because of new customer needs. It even helps you anticipate future actions your customers may take. For example, it calculates churn probability so you can more efficiently invest in retaining customers at a time when marketing budgets are under pressure. We’re continuing to add new predictive metrics, like the potential revenue you could earn from a particular group of customers. This allows you to create audiences to reach higher value customers and run analyses to better understand why some customers are likely to spend more than others, so you can take action to improve your results.

Churn probability in the Analysis module

With new integrations across Google’s marketing products, it’s easy to use what you learn to improve the ROI of your marketing. A deeper integration with Google Ads, for example, lets you create audiences that can reach your customers with more relevant, helpful experiences, wherever they choose to engage with your business.

The new approach also makes it possible to address longtime advertiser requests. Because the new Analytics can measure app and web interactions together, it can include conversions from YouTube engaged views that occur in-app and on the web in reports. Seeing conversions from YouTube video views alongside conversions from Google and non-Google paid channels, and organic channels like Google Search, social, and email, helps you understand the combined impact of all your marketing efforts.

YouTube Engaged-view conversions in Analytics reports

Businesses taking part in the beta are already seeing benefits. Vistaprint , responding to rapid changes in their business at the start of the pandemic, was able to quickly measure and understand the customer response to their new line of protective masks. And Jeff Kacmarek, Vice President of Domino’s Pizza of Canada, found that “linking the new Google Analytics to Google Ads enables us to optimize around the actions that matter most to our customers, regardless of how they interact with our brand.”

A more complete understanding of how customers interact with your business

The new Analytics gives you customer-centric measurement, instead of measurement fragmented by device or by platform. It uses multiple identity spaces, including marketer-provided User IDs and unique Google signals from users opted into ads personalization, to give you a more complete view of how your customers interact with your business. For example, you can see if customers first discover your business from an ad on the web, then later install your app and make purchases there.

You’ll also get a better understanding of your customers across their entire lifecycle, from acquisition to conversion and retention. This is critical when people’s needs are rapidly changing and you have to make real-time decisions in order to win - and keep - new customers. Based on your feedback, we simplified and re-organized reporting so you can intuitively find marketing insights based on the part of the customer journey you’re interested in. For example, you can see what channels are driving new customers in the user acquisition report, then use the engagement and retention reports to understand the actions these customers take, and whether they stick around, after converting.

New reporting structure organized by the user lifecycle

Built for the long term

Now is the time to invest in your digital marketing basics, like smarter analytics, so you can be ready for what comes next. This will also help you respond to rising consumer expectations, regulatory developments, and changing technology standards for user privacy. With a new approach to data controls , you can better manage how you collect, retain and use your Analytics data. More granular controls for ads personalization let you choose when to use your data to optimize your ads and when to limit your data use to measurement. And of course, we continue to offer users control over sharing their activity with Google Analytics.

Because the technology landscape continues to evolve, the new Analytics is designed to adapt to a future with or without cookies or identifiers. It uses a flexible approach to measurement, and in the future, will include modeling to fill in the gaps where the data may be incomplete. This means that you can rely on Google Analytics to help you measure your marketing results and meet customer needs now as you navigate the recovery and as you face uncertainty in the future.

The future of Google Analytics

The new Google Analytics is now the default experience for new properties and is where we’re investing in future improvements. We know there are capabilities many marketers need before fully replacing their existing Analytics setup, so we encourage you to create a new Google Analytics 4 property (previously called an App + Web property) alongside your existing properties. This will allow you to start gathering data and benefit from the latest innovations as they become available while keeping your current implementation intact. If you’re an enterprise marketer, we’re currently in beta with an Analytics 360 version that will offer SLAs and advanced integrations with tools like BigQuery, and will have more to share soon.

Related stories

Our 2023 Ads Safety Report

Evolving Google Analytics for more insightful measurement

Power the next wave of games growth with ads innovation

Empowering your team to build best-in-class mmms, gemini models are coming to performance max.

Own the world’s largest moments with YouTube Sponsorships

How To Track The Customer Journey With Google Analytics

by Madison Cassel | Jan 19, 2024

In the dynamic realm of online business, understanding and optimizing the customer journey is paramount. Google Analytics serves as a guiding light, providing businesses with the tools they need to decipher user behavior, make data-driven decisions, and continually refine their strategies. This blog will delve into the importance of tracking the customer journey and explore how Google Analytics can be leveraged to unravel valuable insights.

Why Track the Customer Journey With Google Analytics?

First, it’s important to understand why tracking the customer journey is an essential factor in achieving business goals. Comprehending the aspects of the customer journey can help you create an enhanced user experience and give insight into how to optimize your website. The customer journey can also assist in informed decision-making. Tracking the customer journey provides data-backed insights, enabling businesses to make informed decisions about content, marketing strategies, and website improvements. Additionally, from this informed decision-making, you can also determine the marketing ROI of the customer journey. By tracking user behavior, businesses can assess the effectiveness of marketing campaigns, identifying which channels and strategies yield the best results.

1. Acquisition Analysis

Delve into the “Acquisition” section of Google Analytics to understand the sources bringing users to your site. Identify which channels —be it organic search, paid advertising, or referrals—are driving traffic.

2. Behavior Flow

The “Behavior Flow” report illustrates the path users take through your site. Identify popular pages and potential drop-off points to refine the user experience.

3. Conversion Tracking

Monitor conversions through the “Goals” section in Google Analytics. Analyze which channels and campaigns contribute most to your business objectives, allowing for strategic adjustments.

4. Attribution Modeling

Dive into attribution modeling to understand the touchpoints that lead to conversions. This feature helps allocate credit to various marketing channels in the customer journey.

5. Custom Reports And Dashboards

Tailor reports and dashboards to focus on specific aspects of the customer journey. Customize your view to track metrics that directly align with your unique business goals and objectives.

In a digital era where customer interactions span various online touchpoints, tracking the customer journey is imperative for business success. Google Analytics provides a robust set of tools to unravel the mysteries of user behavior, empowering businesses to make data-driven decisions and optimize their online presence. By harnessing the power of Google Analytics, businesses can embark on a journey of continuous improvement, ensuring a seamless and satisfying experience for their customers.

In conclusion, Google Analytics emerges as an indispensable tool in the quest to understand and enhance the customer journey. By meticulously tracking how users interact with your online presence—from the first click to the final conversion—Google Analytics offers unparalleled insights into customer behavior and preferences. Businesses are better positioned to craft a user experience that not only meets but exceeds customer expectations!

Do you need help navigating Google Analytics to understand your customer journey(s)? Contact Corkboard Concepts today!

How To Claim Your Business On Apple Maps

Why your business should be using google forms, what is the adplan framework, marketing glossary, what is bing ads, by corkboard concepts, in digital marketing platforms, what is google analytics, what is google search console, what are 3rd party cookies, in common marketing terms, what are ad extensions, what are html5 ads, in common marketing acronims, what are 1st party cookies, what is google microsoft clarity, what does mfa stand for.

• Deutschland
• Asia, Australia & New Zealand
• Europe, Middle East & Africa
• United States & Canada
• Latinoamérica

Consumer Journey

Discover how people are using digital platforms to move through the customer journey on their own terms, and explore what it means for your marketing.

Share this page

Connect with customers throughout their increasingly complex journeys, the 2024 retail guide: put google ai to work to drive profitable growth for your business, how the new york times’s subscriber-first mindset unlocks opportunities for advertisers, holiday shopping insights: keep momentum with devoted shoppers, meet the canadian deal seeker: how they’re shopping this holiday season, holiday shopping insights: be ready for determined shoppers, holiday shopping insights, holiday shopping insights: keep up with deal-seeking shoppers, 3 ways to shift your marketing strategy to adapt to the consumer journey, holiday shopping insights: connect early with deliberate shoppers, more in consumer journey, you're visiting our united states & canada website..

Based on your location, we recommend you check out this version of the page instead:

What is Customer Journey Analytics

Published: June 28, 2023

A customer doesn’t just mindlessly purchase a product or service. They go through an entire journey, from discovering your brand, to purchasing your product or service, to sometimes recommending it to someone else. 

To make sense of your customer’s journey, you’ll need to leverage customer journey analytics.

Every business, startup or enterprise — in any industry — needs to understand how customers interact with their brand. Insights gathered from customer journey analytics can help, while leading to increased customer lifetime value, customer loyalty, and revenue growth. 

In this blog post, we cover the following:

What is customer journey analytics?

• Customer Journey Stages
• Customer Journey Analytics Benefits

Customer Journey Analytics Software

• Customer Journey Analytics vs. Customer Journey Mapping

Customer journey analytics is a collection of data that helps you to understand how your prospects or customers behave, engage, and convert along the customer journey. 

Customer journey analytics often begins with a customer journey map , which is a visual representation of every step the customer goes through with your business. Then, it applies data on how your customer behaves throughout different phases of that map,  to help you assess the effect your customers’ journey has on your business, or what’s holding customer’s back from completing that journey and purchasing a product

Customer Journey Analytics Steps

1. outline a customer journey map..

Create your customer journey map using HubSpot’s template

The first step to customer journey analytics is creating a customer journey map. A typical customer journey map includes the following: the buying process, user actions, emotions, pain points, and solutions. The customer journey map is the foundation for further analysis.

2. Identify the right analytics tools.

To accurately conduct customer journey analysis, you'll need the right tools. 

A good customer journey analytics tool will monitor, track, and analyze data like website data, conversion data, and detail data across multiple channels.

Customer data platforms (CDPs) also play a role in supporting customer journey analytics. The platforms assign unique IDs to your website and app to build single customer views, which can include information such as location, browser, device type, operating system, historical transactions, and visitor logs.

3. Collect your data.

A robust analytics platform should enable you to collect data on customer behavior. Data can be broken down into two main buckets: user data and interaction data. 

• User data: Provides context on a user and their traits. Data can include email, age, industry, and occupation.
• Interaction data: Gives information about how a user interacts with your product or service.

4. Analyze data.

Data in itself is not meaningful without analysis. The purpose of customer journey analytics is to make sense of the data and extract insights that can inform your business strategy. 

For example, an e-commerce company might identify, through analysis, that requiring customers to create an account to complete a purchase leads to the customer not completing the purchase — a solution could be implementing a guest checkout option.

5. Update customer journey map.

Using the insights you’ve gained, you can now update the customer journey map accordingly. For example, you might add additional pain points uncovered through data analysis, like requiring customers to create accounts to complete a purchase.

6. Use customer journey analytics to test new strategies.

The next step is to figure out how to enhance the customer journey experience. Testing new strategies like adding a guest checkout option, making the account creation process faster with fewer steps, and sending abandoned cart emails are all examples.

Benefits of Customer Journey Analytics

By leveraging customer journey analytics, you'll be able to improve your customer’s experience with actionable insights, while unlocking benefits like:

Better Understanding Customers

By gathering and synthesizing data, you will better understand what aspects of the buyer’s journey lead them to purchase a product or service, or not. For example, an e-commerce company might learn that customers that come from a specific social media platform are more likely to buy, or discover that certain audience demographics or affinities are more likely to become leads.

Pinpointing Where You’re Losing Customers

Not all customers follow through, and unless they fill out a survey, it can be difficult to figure out why they churn. By leveraging customer journey analytics, you can pinpoint where you’re losing potential customers. 

For example, a business can lose potential customers during channel or device transitions. A prospect  might start filling out a form on a mobile device but choose to complete it on a laptop. If information entered is lost, the potential customer might not take the time to complete the signup process.

Optimizing and Solving for Prospects

With a better understanding of customers’ pain points and the reasons behind them, you'll be able to figure out how to improve and strategize around an accurate customer journey.

Improve ROI

Are your investments in customer experience worth it? By using customer journey analytics, you’ll be able to measure ROI for customer experience initiatives. From there, you can streamline, remove, or cost cut initiatives that don’t benefit your bottom line, or double down on the aspects of the buyer’s journey that do.

For instance, if you run an incredibly expensive advertising campaign that doesn’t yield the same level of new customers or purchase page visits as unpaid or more in-house content, you can aim to save money on ads and focus on the more affordable strategies that actually earn you money.

1. HubSpot Marketing Hub: Advanced Marketing Reporting

Get started with customer journey analytics

HubSpot Marketing Hub is equipped with robust customer journey analytics capabilities and tools, which can map data around conversions, leads, deals, and website engagements around different stages of the customer journey. 

The Advanced Marketing Reporting tool also enables you to  attribute every customer interaction to revenue, analyze conversion rates and time between nurturing path steps, and provides further data to help you build informed strategies that can improve ROI and purchase rates.

2. Content Square

Content Square captures UX, performance and product, and content data throughout the customer journey. The platform also enables you to visualize metrics so that they are easily digestible. You will be able to get insights like bounce rate and number of lost conversions, and dig deeper to pinpoint why.

3. Google Analytics

Google Analytics is a widely used website analytics software that enables you to track user behavior on different platforms, including mobile applications. Features like daily traffic reporting give you insight into what visitors are engaging with. Plus, its Analytics Amplifier can combine Google Analytics and HubSpot data .

Customer Journey Mapping vs. Customer Journey Analytics

Customer journey analytics and customer journey mapping are often confused with each other. Although they’re complementary,  customer journey mapping visually presents customer journey stages from start to finish, while customer journey analytics offers data about a  customers’ interactions in each stage.

Customer journey maps often include the following:

• The buying process: By pulling data from places like CMS and prospecting tools, you will be able to figure out what goes into a customer’s purchasing process. 
• User actions: This part of the customer journey map details the actions the customer takes throughout their journey.
• Emotions: Emotions help color your understanding of how your customer is feeling and reacting as they go through their journey with your business.
• Pain points: Adding pain points to your customer journey map gives you a comprehensive picture of the challenges your customer may experience.
• Solutions: Figuring out solutions can help your customers experience fewer pain points. The data and insights you’ve gathered can help inform your solutions.

Customer journey analytics delves deeper. The customer journey map is the “what” and customer journey analytics is the “why” because it organizes customer or prospect data around each stage.  

Here’s an example of how customer journey analytics works in HubSpot Marketing Hub:

HubSpot’s Advanced Marketing Reporting Tool  

Customer Journey Map vs. Analytics Example: Let’s say your business offers CMS tools and your ideal customer, a graphic design firm, finds you through a targeted Instagram ad.

In the customer journey map you’ve built , your target customer considers using your CMS tools to build a new website that showcases their strengths. They schedule a demo before trying the free version and are initially excited, but become frustrated with the limited design elements offered by the free version. Their biggest pain point quickly becomes lack of versatility. They then look into purchasing the paid version or go to a cheaper competitor.

With customer journey analytics, you’ll apply real-time data to that map: From journey mapping, you’ve identified the steps your customer often takes  and their common pain points. A strong customer journey analytics tool can then collect, aggregate, synthesize, and visualize data to help you make sense of your customer’s actions and see if your mapping and journey-based strategies work. 

For example, data might show how your customer is interacting with your product. 

A good Customer Journey Analytics platform combines data like user data, survey results, and website analytics, you can gain a comprehensive view of why your customer is experiencing those pain points and consequently address their concerns.

Cultivate an Impactful Customer Journey

In order to remain competitive, it is important to understand and create strategies to enhance the customer’s journey. Customer Journey Analytics is just one component. Other key steps include creating buyer personas , mapping out the customer journey , and continuously updating strategies based on data.

To get started with improving the customer journey, learn more about HubSpot’s marketing solution Marketing Hub .

Don't forget to share this post!

Get Started with HubSpot's Analytics Software for Free

Marketing software that helps you drive revenue, save time and resources, and measure and optimize your investments — all on one easy-to-use platform

Explore Customer Journey With Advanced Analysis In Google Analytics 360

• Google Analytics
• Google Analytics 360

If you’ve made it your personal (and professional) mission to map out your company’s Customer Journey from brand awareness to conversion, you’re not alone! In fact, this ever-evolving buzzword and analytical challenge has been one of the most talked about concepts in the office over the past few months – we simply can’t get enough!

Even with increasing publicity, the Customer Journey has remained elusive to many analysts and marketers alike due to limited out-of-the-box reporting options. Sure, BigQuery, R, Python, and other advanced analysis tools are fantastic ways to get after that GA data and transform it to your heart’s content (check out my colleague’s post on the topic). But isn’t there an easier way to at least begin the process? Cue Google’s response: Advanced Analysis was launched this May for Google Analytics 360 customers.

As you may know, Customer Journey can mean different things to different people. Today, let’s focus on the user’s website/acquisition journey.

What Is Advanced Analysis?

In addition to the standard Google Analytics reporting interface, Advanced Analysis offers multiple mechanisms for deeper, sophisticated exploration of data. You can think of the tool as a cross between Data Studio , which is used primarily as a reporting and visualization platform, and the Google Analytics custom reporting feature, which has typically been used for ad-hoc analysis purposes.

Our focus for the remainder of this discussion will surround the awesome problem-solving features of Advanced Analysis as they relate to the Customer Journey. To learn more about navigating the individual reports than what I covered above, check out Google’s introduction to the tool here .

To get you started in your Customer Journey analysis, the Advanced Analysis dashboard comes with three pre-defined templates – Exploration, Segment Overlap, and Funnel Analysis, as well as the option for complete ad-hoc analysis.

Exploration

What makes the Exploration report truly exciting is the expanded scope of analysis. Unlike in traditional Google Analytics reports, the Exploration report interface is powerful enough to handle up to five dimensions and 10 metrics (values) per report. There’s even a “Columns” feature which makes the report resemble a detailed pivot table.

Moreover, the Exploration report goes beyond traditional pivot table analysis by providing visualization opportunities too, such as pie chart, line chart, bar chart, plain text, or even heat map visualizations (shown in the screenshot below). For example, now you can quickly visualize which source(s) and medium(s) result in the most transactions, export the data to Google Sheets with the touch of a button, or share the link with your fellow marketers.

Using this data, we might notice that referrals are treating us very well – specifically from googleplex.com. But how do we take action on this observation? Advanced Analysis has you covered yet again. By right-clicking on the row with “mall.googleplex.com,” we can create a segment from the selection, or even build an audience to remarket to from the data.

This feature actually extends past the exploration report – you can create segments or audiences within the entire Advanced Analysis suite of reports. Once that special segment has been identified, you can also publish the segment to Google Analytics for use across all of your platforms, including Data Studio. Additionally, these audiences can be published to Google AdWords or Display & Video 360 for remarketing or ad targeting. Finally, clicking the “View Users” option from the menu will open the user explorer report in Google Analytics, giving you the ability to drill down on the segment and identify key trends for users who converted, and especially those who did not.

One more note about Advanced Analysis (which spans all of the report types we will talk about) – by clicking on the “+” sign next to your current tab, you can create a new Exploration, Funnel, or Segment Overlap report to analyze your data side by side. The sticky navigation pane to the left will remain with you throughout the entire project!

How does this relate to the Customer Journey, you ask? These segments become increasingly useful in the preliminary stages of mapping our customer’s touchpoints. We know that each user takes a different path prior to conversion, but to wrap our arms around the massive number of entries and exits, we often need to categorize users into personas, segments, or types. Once we’ve segmented users, we can often uncover similarities and differences that are actionable from a marketing and web dev perspective.

Segment Overlap

Just like we saw with the Exploration report, the Segment Overlap tool goes above and beyond what we’ve historically been able to visualize in Google Analytics. This tool will be particularly useful once you’ve created new segments using the Exploration report, the Funnel report feature, or segments within Google Analytics.

To quickly create a new Segment Overlap report from the page that you are on, navigate to the “+” sign next to your current tab. From there,  you can create a new Exploration, Funnel, or Segment Overlap report to analyze your data side by side. The sticky navigation pane to the left will remain with you throughout the entire project!

Let’s use the Source/Medium example from our Exploration report (Source = mall.googleplex.com AND Medium = referral), and compare the segment with our other top transaction segments (Direct/None) and (sites.google.com/referral). By creating these segments within our Exploration report, Advanced Analysis places the segment in the left-hand variables column. All we have to do is drag and drop into a new Segment Overlap report.

Let’s do some analysis – what interesting details can we glean from this report? One of the first observations is that while Direct traffic seems to represent the majority of transactions, the revenue per user is actually much higher for our referral sources.

Did we run a display campaign via sites.google.com in the past that is resulting in increased purchases this month from website referrals? Perhaps referral users are becoming repeat purchasers, bumping up the ROI for our previous marketing efforts. If we didn’t run a display advertisement, maybe we should consider it, as this channel seems to provide a significant revenue opportunity!

There are many uses for the Segment Overlap report. One of the most notable ways of using this new feature includes looking at behavior or customer-focused segments to understand how your remarketing audiences may overlap. This is the first time that this kind of data has been made available to end users, so get creative! For example, you may ask yourself “What is the overlap between the “Blog Readers” segment and the “Add to Cart” segment? You may notice that exploring the commonalities and differences between segments will help your organization group behaviors and better understand the types of consumers that are visiting your site.

Additionally, be sure to check out the breakdowns and filters components of Advanced Analytics, which enable even further segmentation for slicing and dicing that data.

Funnel Analysis

Drumroll, please! It’s time for the feature we’ve all been waiting for – the Funnel Analysis reporting tool! Once we’ve explored our data, created a few segments, and analyzed our populations within the Exploration and Segment Overlap report, we may have a better idea of the starting and ending points of our Customer Journey. Getting to the hazy details during the middle of our customer’s session is where difficulty often sets in. The Funnel Analysis report is primed and ready to help you better understand customer drop-off and customer conversion, from any starting or ending point you choose.

Let’s take a look at our three top (Source / Medium) performers within the Funnel report to see where we lose some of our customers. We’ll start with a checkout process funnel, and then we can segment further.

In the Funnel report, we can see that we have a pretty great retention rate throughout from viewing a shopping cart to completing the checkout process. However, it seems as if we lose a significant amount of customers between these steps for certain segments, so let’s create a second funnel to explore. Also, notice that we have 6 steps in our funnel! Advanced Analysis is configured for up to 10 funnel steps (that’s double the standard 5 in Google Analytics)!

Let’s look specifically at Men’s Clothing to see if we can find a trend. Here, we’ve created a funnel step for Men’s Apparel, Men’s T-shirts, and shopping completions. We also swap out T-shirts for Hoodies to see if our trend is valid across products.

We can see that drop-off occurs at the Men’s Apparel landing page for many of our customers, regardless of T-shirt or Hoodie selection, and regardless of referral channel. Therefore, we may want to explore the journey around Men’s Apparel to see if we can improve the experience for our customers, resulting in additional transactions.

Moreover, since we know these referral users tend to result in repeat customers (bringing in revenue for the company,) we may decide to remarket to those who have viewed the men’s apparel page but did not convert. If you use Optimize 360, you may decide to run experiments to see if you can improve the likelihood of purchase.

Note: If it’s challenging to view the bars due to size discrepancies, simply scroll your mouse or click on the “+” sign to the right of the chart. This will create “breaks” in the outliers for an easier viewing experience, as shown above.

Back to the Customer Journey

Using the funnel tool, we could continue to create subsegments using the right click method discussed earlier. These additional segmentation opportunities would bring us closer to understanding personas and buyer types site-wide. We can also use the completion rate & abandonment rates beneath the Funnel reports to observe details about the completion and abandonment rates between each step, informing our marketing and sales positions.

Setting up robust goals in Google Analytics will also help you to arrive at the underlying revenue-generating activities for your website. Often times, the Goal Funnel reports within GA are a great way to begin the Customer Journey process. Another bonus? You can use goals within your Advanced Analysis funnels!

It is important to note that identifying journeys & funnels that you will want to use as recurring reports will most likely take some time and experimentation. Users often flip-flop between tabs, content types, and even product types before completing a transaction.

Therefore, setting realistic expectations up front about the level of detail you need to make sound business decisions is paramount. Often times, understanding the general direction of activity is all you need to start making better website design and digital marketing decisions.

A Quick Recap

While Advanced Analysis may not be a replacement for tools of the trade like Data Studio or BigQuery (Data Studio offers corporate branding/style opportunities, calculated metrics, custom date ranges, and permissions access, which are limitations within Advanced Analysis), chances are you will find the segmentation capabilities and funnel reports useful within your organization. And, most importantly, these tools are one way to get another stride closer to that elusive Customer Journey.

Find another cool feature of Advanced Analysis? Let us know in the comments below!

Recommended Perspectives

Navigating the Transition: From UA Sunset to GA4's Evolution

IP Addresses and Google Analytics 4: What You Should Know

Embrace the Benefits of Google Analytics 4

• Perspectives
• Best Practices
• Inside Amplitude
• Customer Stories
• Contributors

Customer Journey Analytics: Definition, Tools, & Examples

Learn how customer journey analytics helps you measure the ROI on your customer experience initiatives. Use it to boost revenue, reduce churn, and improve CX.

Customer journey analytics (CJA) is the process of analyzing the entire customer journey through customer data points, then strategizing ways to improve the overall customer experience (CX) . Customer journey analytics is a holistic process that makes customer journeys measurable and helps you identify insights and actions to delight and retain your customers.

Key takeaways

• Customer journey analytics is the process of examining critical data pertaining to user journeys to make informed decisions on improving the customer experience.
• Some of the benefits of customer journey analytics include the ability to measure the ROI on CX initiatives and improve the customer experience through the insights it provides, as well as reduce churn and boost revenue.
• Measuring customer journeys is a process that involves creating user journey maps, determining and collecting data pertaining to those journeys, and defining success metrics and milestones along the way.

What is customer journey analytics (CJA)?

Customer journey analytics is the gathering and analyzing of data that pertains to customer behavior to improve the customer experience. Analysis happens over multiple customer touchpoints and channels over a period of time and measures the impact of behavior on business outcomes.

While gathering customer data, you can collect all user actions in one central database with an associated timestamp. Information is collected through a unique identifier on what the user is doing and who the user is.

Using this information, it’s possible to map out customer journeys and then analyze the customer engagement levels for each journey to understand what’s going well and where customers might be getting stuck. The analysis helps to optimize these customer journeys and also measures the performance of your CX initiatives.

Example insights from customer journey analytics

Customer journey analytics provides deep insights to improve the customer experience. Some examples include:

• Customer journey analytics makes it possible to analyze the path customers take to resolve customer queries. Some insights derived from this analysis might include what types of issues can be resolved by self-service channels and which ones need human interference. This information makes it possible to optimize self-service channels, improve the operational efficiency of resolving customer queries, and enable customer support staff to focus on more complex customer issues.
• For ecommerce companies, customer journey analytics makes it possible to view the steps a customer takes while completing a purchase, which can help identify any barriers to completing the transaction. You might find, for example, that a common frustration while completing a purchase is having to create a user account. You can then use this insight to A/B test a guest checkout option and see if it removes the friction.
• Customer journey analytics can help you identify channel-specific insights to improve the customer experience. For example, you might find that users on your mobile app drop off at a higher rate than users on your website. This insight could indicate that you need to rethink parts of your mobile experience.

Benefits of customer journey analytics

There are several benefits of customer journey analytics, including:

Measuring the ROI on CX initiatives

In a CX survey, 20% of respondents said that measuring customer experience initiatives was one of the key challenges being faced by organizations in the U.S. Customer journey analytics solves this problem by making it possible to measure the ROI on CX initiatives.

Product managers and CX designers can use customer journey analytics to connect data and numbers to customer journeys. For instance, CJA can compare the revenue generated from two user journeys to figure out which user journey leads to more revenue for the business, making it possible to shift to the journey that’s most beneficial.

Customer journey analytics makes it possible to understand how the customer interacts with the product, how their behavior changes when modifications are made to the customer journey, and how your product metrics are impacted because of this changed user behavior.

Improving the customer experience

By visualizing user journeys built by customer journey analytics tools, it’s possible to identify bottlenecks people might face in your product, minimize them, and make smart product suggestions based on their past behavior.

For example, with customer journey analytics, it’s possible to diagnose that users of an ecommerce app fail to make a purchase during the last step of the transaction, especially when using the app for the second time. They might be getting stuck since they don’t remember what they bought the last time, so CJA makes it possible to autosuggest items based on what the customer purchased on their last visit. Reminding customers about their past transactions can improve the overall shopping experience by helping users purchase with ease.

Customer journey analytics tracks data in real time. This enables you to analyze customer behavior while the customer interacts with your website or product, build user journeys around that behavior, then find opportunities to make improvements to the customer experience.

Reducing customer churn

Since customer journey analytics helps predict customer behavior based on their past actions, it can also identify customers at risk of leaving the product or website, enabling you to take action to retain at-risk customers.

Upon identifying at-risk customers, it’s possible to use CJA to personalize interactions with them and help them feel more positive about the brand, so they’ll change their minds about leaving. In a CX study, 58% of respondents stated that their organization had seen significant increases in customer retention as a result of using customer analytics.

Boosting revenue

By helping you identify the customer journeys that result in a purchase, it’s possible to boost revenue using customer journey analytics. You can further optimize these journeys by reaching out to customers in real time with relevant communication like upsell and cross-sell offers.

CJA can also help identify your best-performing channels by monitoring customer behavior across different touchpoints. So if your website is performing better than your app, you can focus on optimizing the revenue from your website while making improvements to your mobile app.

Steps for measuring customer journeys

Step 1: create or capture user journey maps.

Before you start measuring a customer journey, it’s important to first create a user journey map. You can create this journey map using prototyping tools or Post-it Notes based on the actions users take. For example, if you want to measure the journey of playing a song on a music app like Spotify, you need to create the entire journey map so you can visualize it.

In this example, the user journey might consist of the following steps: going to the Spotify website, downloading the app, creating a login, searching for a song, and then playing the song. You’d need to write these steps out in the form of a “journey” or use a tool that captures these user actions and creates the journey maps for you.

The goal, in this example, is to play a song on the app. And the journey to that goal consists of several steps along the way. You need to view the journey across different channels since, at the end of the day, your user is trying to accomplish a goal and it doesn’t matter whether they do it via your mobile app or your website.

Step 2: Determine the data you need to collect at each step of the customer journey

To measure a customer journey, you need to define the critical data points you need to measure for that journey. For instance, in our Spotify example, here are some data points that might be relevant to help quantify the journey:

• Number of attempts to download the app
• Time it takes to download the Spotify app
• Time it takes to create a user login
• Number of attempts to play a song

Collecting all of the data in one centralized place makes it easy to access it and pick the relevant bits of data needed along with their timestamps. The data required will depend on the journey you decide to measure.

For every part of the customer journey, there’s an action that your brand wants the user to complete. Every journey has a goal, and there are milestones to achieving that goal. It’s important to define both the goal and the milestones along the way, so you know what to measure and what success looks like.

With the example of playing a song on Spotify, some success metrics or milestones would be:

• Downloading the Spotify app
• Creating a user login
• Playing the first song
• Subscribing to the Spotify service
• Sharing the first playlist
• Renewing the subscription

Think of milestones as critically important steps in the process of achieving a goal. Make a list of these steps, so you can have clearly defined milestones.

Step 3: Analyze the customer data

The next step is to identify your data sources and capture behavioral customer data across the customer journey. Once you’ve collected data, you can start analyzing it and measuring key metrics along critical flows of the journey. You’ll be able to gauge where customers are spending their time, what’s causing them frustration, and which behaviors lead to revenue-generating outcomes. Using this information, you’ll be able to measure the customer journey effectively and figure out how to improve it.

Customer journey analytics tools

Using the Journeys feature on Amplitude , it’s possible to discover what’s making users convert or drop off. With Journeys, you can:

• View step-by-step breakdowns of the paths taken by converted and dropped-off users.
• Uncover the paths most likely to accelerate conversion.
• Identify what your users do if they don’t convert.
• Understand the friction points in your customer experience and develop a strategy to fix them.

By defining the start and endpoints of the journey, the Journeys feature within Amplitude helps you see what percentage of paths converted and what percentage dropped off.

There is a range of other customer journey analytics tools available, including:

• Acoustic Analytics
• Adobe Analytics
• Google Analytics
• Salesforce Journey Builder
• Webex Experiment Management

Learn more about each of these customer journey analytics tools on a review site like G2 .

• What are the biggest challenges currently being faced by your organization in terms of customer experience? Statista
• Performance enhancements resulting from the use of customer analytics in the United States as of March 2018 . Statista

See what customer journey analytics looks like in our self-service demo , or get started with journeys using your own data in a free Amplitude account .

About the Author

More best practices.

Root out friction in every digital experience, super-charge conversion rates, and optimize digital self-service

Uncover insights from any interaction, deliver AI-powered agent coaching, and reduce cost to serve

Increase revenue and loyalty with real-time insights and recommendations delivered to teams on the ground

Know how your people feel and empower managers to improve employee engagement, productivity, and retention

Take action in the moments that matter most along the employee journey and drive bottom line growth

Whatever they’re are saying, wherever they’re saying it, know exactly what’s going on with your people

Get faster, richer insights with qual and quant tools that make powerful market research available to everyone

Run concept tests, pricing studies, prototyping + more with fast, powerful studies designed by UX research experts

Track your brand performance 24/7 and act quickly to respond to opportunities and challenges in your market

Explore the platform powering Experience Management

• Free Account
• For Digital
• For Customer Care
• For Human Resources
• For Researchers
• Financial Services
• All Industries

Popular Use Cases

• Customer Experience
• Employee Experience
• Employee Exit Interviews
• Net Promoter Score
• Voice of Customer
• Customer Success Hub
• Product Documentation
• Training & Certification
• XM Institute
• Popular Resources
• Customer Stories
• Market Research
• Artificial Intelligence
• Partnerships
• Marketplace

The annual gathering of the experience leaders at the world’s iconic brands building breakthrough business results, live in Salt Lake City.

• English/AU & NZ
• Español/Europa
• Español/América Latina
• Português Brasileiro
• REQUEST DEMO
• Experience Management
• Customer Journey Mapping
• Customer Journey Analytics

See how XM for Customer Frontlines works

A complete guide to customer journey analytics.

13 min read Customer journey analytics can help you to nail down exactly why your customers behave the way they do and tie your customer experience efforts to financial outcomes. Learn how to use customer journey analytics for improved CX with our ultimate guide.

What is customer journey analytics?

Customer Journey Analytics is the process of understanding the impact of every interaction a customer has with your business.

Often, customer journey analytics starts with a customer journey map , which is presented as a graph, flow chart, or other visual that documents each stage of the relationship between a customer and a brand.

However, instead of just charting their customer journey on a map, customer journey analytics takes a further step to analyze what effect each interaction has on your customers’ decisions.

Further information is overlaid to help analyze how each interaction drives customers toward the end goal.

Customer journey analytics can include analysis of:

• Customer needs
• Emotional highs and lows
• Key metrics per step in the journey
• Customer satisfaction scores , customer effort scores , and other survey results

Customer journey analytics can help you to direct your customers’ attention and resolve any pain points that stop them from taking desired actions. It helps you to augment your customer experience and develop a customer journey that not only gets customers to where you want them to go, but helps them connect to the journey itself.

Learn the analytics and ROI on customer journey management in our free course. 

Customer journey analytics vs. customer journey mapping

Many brands have a broad sense of their customer journey but haven’t optimized it by creating a comprehensive customer journey map or analyzing what affects their customers’ experience.

Customer journey analytics and customer journey mapping are complementary but different processes. Here are the main ways in which they are distinct, and how they work together.

What is customer journey mapping?

Customer journey mapping is the process of laying out the end-to-end journey in a clear way. Creating a map of every touchpoint your customer will experience means you can see what steps your customers take to reach the end goal of a purchase, signup, or other action.

Often, journey maps are documented at the process level. For example, an insurance provider would map the claims process, and a bank would document the new account process.

Some common components of customer journey maps include:

• The process being evaluated
• The stages of the journey
• Critical customer interactions and touchpoints
• Representative customer quotes
• Key customer expectations
• Metrics like satisfaction score, mention volume, NPS
• Trends in topics related to this part of the journey

Our ultimate guide to customer journey mapping can help you to draft your first customer journey map or optimize one you have already.

How do you use customer journey analytics with customer journey mapping?

As we’ve already explained, customer journey analytics is the process of gathering as much information as you can from every part of the journey and analyzing the journey for pain points and successes.

Understanding which parts of the journey function as planned and which obstacles are in the way of your customers’ progress means you can take action to ensure they complete their journey as you intend.

Benefits of customer journey analytics

There are several benefits to completing customer journey analytics. From better understanding your customers’ behavior to a better ROI for your customer experience , customer journey analytics gives you better insights and a more informed strategy for improvement.

Your brand becomes more customer-centric

Understanding the customer journey allows your company to be more customer-centric . It allows you to closely evaluate the activities, expectations, thoughts, and feelings of your customers . You learn what they like and dislike, how to move them through your buying cycle, and how to satisfy and retain them . When journey mapping is complemented with customer journey analytics it helps you understand the priority for your customer experience initiatives.

Your business becomes more unified

In addition, with the right focus, customer journey mapping and customer journey analytics break down internal silos. They empower you to streamline services across departments. Not only that, but they help to align everyone by providing a common understanding of the customer experience. Employees get greater visibility into what happens upstream and downstream of their interactions with customers, letting everybody provide a more consistent, high-quality experience.

You can find track issues as they happen

With a sophisticated customer journey analytics platform, you can pinpoint issues in real-time. You can test new approaches and see their influence on your customer experience and bottom line with analytics that update as quickly as you need them.

You see direct and indirect feedback in one place

Explicit feedback – for example, the information you gather through surveys – is easier to pinpoint to specific interactions customers have with your brand. The customer has an experience and directly after, you request input.

Implicit feedback is more complex to understand. This type of data might include operational data such as sales numbers, or it might cover social mentions, what your customers say on the phone to your care center, third-party reviews, and more.

Understanding how your audience thinks, feels, and acts in response to customer interactions without directly asking them might seem impossible, but with tools such as conversation analytics , you’re able to link your customer journey to this type of customer data.

See how Qualtrics CustomerXM enables customer journey analytics

An example of using customer journey analytics

Customer journey analytics can be used to understand the impact of sub-journeys limited to single processes – such as opening a new account – or the entire digital customer journey .

Below is an example of how you can use customer journey analytics to chart the success of each journey.

Resolving a customer satisfaction issue for a specific sub-journey

Let’s take a printer business that provides hardware to its customers. The brand has realized that the repair sub-journey is currently leading to low Net Promoter Scores (NPS) and a higher cost to serve per customer.

The journey

First, the brand needs to chart the customer journey. It looks like the below:

• A customer has an issue with their printing device
• They call the customer care center to schedule a repair
• The service agents arrive at their place of residence
• The repair is made

However, there are other ways this journey might unfold. For example:

• The service agents arrive at their place of residence but the customer is not present
• The repair cannot occur, so the customer has to call again to reschedule the repair
• The repair is made at a later date when the customer is present

The analysis

Overlaying the NPS scores on this latter journey, the company realizes that the NPS score drops when the customer has to reschedule the repair. Asking the customer to go through the same process once again to rebook their appointment is causing customers to feel less satisfied with their experience.

Using natural language processing (NLU), the team can also see that there is a more negative sentiment expressed in the open text question they have added to the NPS survey. With the additional calls to the care center, the cost to serve each customer also increases.

The resulting action  

The brand decides it’s best to provide other means to customers to book their appointments at a time to suit them. Offering customers a self-service booking system that they can access via their mobile on an app or through the website gives the customers more control over when their appointment occurs. Adding a facility to reschedule any booked appointments for a more convenient time and accentuating this with push or text notifications when the repair team is on their way can help to see if this reduces the instances of missed repairs and reduces the impact on the customer care center .

With customer journey analytics in place, the brand team can see if this improves NPS scores at the same points in the customer journey, and measure in financial terms the impact of actions taken for improved customer experience .

How to use customer journey analytics

Customer journey analytics provides the insight you need to successfully manage your customer’s journey. From lowering customer churn to helping you predict customer behavior, putting a customer journey analytics solution in place will help you to leverage your customer behavioral data for financial success.

But how do you start using customer journey analytics? Below is the outline of the actions you’ll need to take.

1. Map your customer journeys and aggregate data

First, you need to create a customer journey and aggregate the customer data that you already have. Good customer journey analytics tools will be able to do this for you, cutting down the time your team needs to spend sourcing data from third-party locations, customer service chat logs, and survey results.

Competent customer journey analytics software will also be able to track data in real-time, allowing you to build a comprehensive map that reacts to current customer behavior . It should also be able to draw data from numerous sources, helping you to break down traditional business silos and understanding customer interactions from all business angles: sales, marketing, and more.

Learn the five competencies for customer journey mapping

2. Analyze your customer behavior and data

Once you have your customer journeys mapped out and your data collected, you can link specific interactions to particular customer behavior, survey results, social media comments , and more. You’ll need a customer journey analytics solution to be able to link all of this data together in an efficient way.

3. Take action informed by data-led insights

Customer journey analytics provides you with the ability to see cause and effect, as well as providing you with concrete steps to change specific interactions or the entire customer journey. When customers react badly to specific processes or interactions, you can test how changes in your customer journeys affect their future decisions.

Not only that, but you can coordinate your teams across your business to work on customer satisfaction with their experience, based on the data you’ve analyzed. For example, if customers are led to purchase through your marketing but aren’t happy with their purchase, they will deal with your marketing , sales, and customer care teams. Understanding what specifically caused a problem for them means you can inform each team of actions they can take to improve.

How customer journey analytics can improve your customer experience

Brands often hit a wall when trying to measure customer experience . Charting your customers’ often nebulous sentiment and which actions have an impact on customer experience can be difficult without the right tools to hand.

Understanding the return on investment for specific actions taken for customer experience is difficult for a number of reasons:

• Data is siloed or overwhelming
• Business departments work separately with a lack of oversight
• Actions aren’t based on data
• There isn’t a way to track the impact of actions on customer experience

Qualtrics CustomerXM allows you to see the value of customer journeys with rich data analysis, provided through conversational analytics . With natural language understanding, Qualtrics is able to provide you unrivaled insights into customer emotions, sentiment, and more to paint a complete picture of friction points and their rationale. Powered by feedback from multiple areas of your business, you are able to create a plan of action with a tangible effect on your customer experience and business outcomes.

With a deeper understanding of customer behavior, your brand is able to not only understand the return on investment of your actions but develop a customer experience that delivers results. Extending your customer lifetime value , increasing customer satisfaction, and reducing customer churn becomes easier when you understand the triggers for the behavior.

Learn how to take action on customer journey management with our free online course

Related resources

Customer Journey

How to Create a Customer Journey Map 22 min read

B2b customer journey 13 min read, customer interactions 11 min read, consumer decision journey 14 min read, customer journey orchestration 12 min read, customer journey management 14 min read, customer journey stages 12 min read, request demo.

Ready to learn more about Qualtrics?

Customer Journey Analytics 101: Comprehensive Guide for SaaS Companies

How can product and marketing teams leverage customer journey analytics to make data-driven decisions and build delightful customer experiences?

This is the key question we discuss in our guide, so if you’re after the answer, let’s dive right in!

• Customer journey analytics is the process of tracking user interactions at all the touchpoints in their journey .
• Customer journey mapping is a part of customer journey analytics and it uses qualitative insights. Journey analytics uses quantitative data to assess what happens at different stages of the journey.
• In addition to increasing customer satisfaction and reducing customer churn , customer journey analytics helps teams boost customer lifetime value.
• The first step of customer journey analysis involves mapping out all the stages, actions, milestones, and touchpoints for each user persona.
• Next, you need to collect relevant data from various sources, like web traffic or in-app product usage.
• After that, analyze the data collected via various channels. There are different ways to do it, depending on your goals. For example, you could analyze conversion rates .
• Attribution analysis allows you to evaluate the effectiveness of your touchpoints.
• User flow analysis identifies and visualizes all actions taken by users.
• Trends analysis focuses on long-term patterns and changes in user behavior.
• How you act on the customer journey analytics insights depends on the problems you’ve identified. For example, you can improve the sign-up rates by enabling single sign-on (SSO) or delaying email confirmation.
• Both Amplitude and Google Analytics are robust analytics tools for tracking user behavior in web and mobile apps but they lack the engagement layer to act on the insights.
• Userpilot is a product growth platform with analytics , feedback, and engagement features.
• To see how to use it to analyze and optimize your customer journeys, book the demo!

What is customer journey analytics?

Customer journey analytics is the process of tracking and analyzing customer interactions with the brand and product across all touchpoints in their journey .

Customer analytics focuses not only on what the customer does inside the product. But rather, its goal is to obtain insights into engagement along the entire user journey and across all channels, starting from the moment they learn about the product to the purchase – and beyond.

Customer journey mapping vs customer journey analytics

Customer journey mapping and customer journey analytics are two related but distinct processes.

A customer journey map is a visual representation of the journey with your company, including their interactions, experiences, and emotions. It presents all the touchpoints and stages that the user goes through, from the initial awareness to post-purchase.

Customer journey mapping usually relies on qualitative data collected via interviews, surveys, and customer behavior observations.

On the other hand, customer journey analytics uses quantitative data from various sources, like website or product analytics, or customer feedback , to uncover patterns and trends in customer behaviors to optimize their journey.

The benefits of tracking customer journey analytics

Why does customer journey analytics matter in product management? Here are a few benefits:

Improves customer experience

Analyzing customer journeys enable SaaS companies to improve the customer experience by identifying stages that need optimization.

For example, tracking conversions during the sign-up process can help you identify friction points that slow users down and make the process unnecessarily challenging.

By optimizing the touchpoints, you will be able to make the experience less painful and increase the conversion rates as a result.

Reduces customer churn

Friction in the customer journey often leads to churn . Customers who struggle to complete tasks or discover important features eventually give up and go looking somewhere else.

Consequently, identifying the friction points and addressing them will help you boost the retention rate.

What’s more, by tracking your power users, you can identify which practices or behaviors contribute to their success. By making other users follow the happy paths of power users with similar objectives, you will increase their chances of success as well.

Increases the customer lifetime value

A higher retention rate goes hand in hand with a greater customer lifetime value (LTV) . The longer your customers stay with you, the more money they spend.

Additionally, analyzing customer journeys will help you take better advantage of account expansion opportunities through upsells and cross-sells.

For example, it can help you identify user behavior patterns indicating that the user may need more advanced functionality. Armed with this knowledge, you could trigger contextual messages offering them an upgrade to a higher plan.

What is an example of customer journey analytics?

Let’s imagine a SaaS product that witnessed a high churn rate during the onboarding stage.

Here’s how the onboarding process works:

• Users log into the product.
• A welcome survey pops out.
• Completing the survey triggers an onboarding checklist .
• Users complete the tasks from the checklist to familiarize themselves with the key product features.

How could the team diagnose the problem?

By looking at the conversion rates from each of the stages, the team realizes that most churned users don’t complete the checklist tasks.

Specifically, customer journey data shows users fail to complete a task involving product customization. That’s the step they need to have a closer look at.

Session recordings of the churned users trying to customize the product and surveys reveal that there are too many customization options and users find the experience overwhelming. What’s more, they don’t know exactly how each of the settings will affect their experience.

What’s the solution?

Based on the findings, the team decides to reduce the number of available options. They also design a set of tooltips to provide in-app guidance on each of them.

How to conduct a user journey analysis to improve the customer experience?

Let’s look at a step-by-step guide on how to use customer journey analytics to create outstanding customer experiences.

Step 1: Map out the entire customer journey

Start mapping out the customer journey by identifying the user personas. While all of them may use the core features of the product, they may have different goals and use them in a unique way. That’s why each of them will have a separate map.

Next, list the key stages of the customer journey.

To kick off, you could use the Pirate funnel (Awareness, Acquisition, Activation , Retention, Revenue, Referral) and adapt them to the unique characteristics of the product. For example, your CJM steps could be Discovery, Engagement, Evaluation, Purchase/Onboarding, and Account Growth/Advocacy.

For each of the stages, identify the goals that are specific to the user persona.

After that, identify all the user actions at each stage. For example, at the Discovery stage, the user could run a Google search for ‘best software for X’, read reviews, and ask peers for recommendations. Decide which of the actions are the milestones that will drive conversions to the next stage.

Finally, list all the touchpoints where the customers will interact with the product. For example, at the Discovery stage, this could be the Google SERP, your blog posts, or your YouTube channel.

Step 2: Collect customer data from multiple channels

The data that feeds into your customer journey analytics will come from various sources.

These could be web analytics, in-app product usage tracking, heat maps , customer feedback surveys , reviews, social media mentions, or calls with the customer success teams.

Each of the channels may require a dedicated tool to ensure you get a complete picture of how customers behave along the journey.

For example, you may need a tool that enables you to track feature engagement both in your web and mobile apps, or an NLP-powered feedback tool that will help you analyze qualitative responses.

Step 3: Analyze data related to customer interactions and customer behavior

Once the data starts coming, it’s time to analyze it. There’s no one way to do it as it’s very much dependent on your product or your goals . Here are examples of a few possible kinds of analysis.

Customer journey reports

Customer journey reports focus on user progress from one stage of the journey to another.

The reports contain information about conversion rates for different stages. Analyzing the data enables you to identify bottlenecks and pain points that stop users from achieving their goals.

In addition, you can use the collected data for user segmentation . For example, you could group users into power users and churned users and analyze their behavior in greater detail.

Attribution reports

Attribution reports help product teams to assess the effectiveness of different touchpoints along the customer journey and determine which of them are most influential in driving customer conversions or desired business outcomes.

With such knowledge, they can optimize the underperforming touchpoints or allocate their resources to prioritize the future development of the most successful ones.

Attribution reports also help teams evaluate the impact of new customer experience initiatives.

User flow chart reports

User flow reports provide teams with granular insights into the specific steps taken by users to complete a task. They are normally visualized in charts consisting of boxes representing each action.

User flow charts are a valuable tool for identifying the happy path for each user segment and eliminating friction or unnecessary steps from the customer experience.

Trends analysis reports

Trends analysis focuses on identifying and analyzing patterns and changes in customer behavior over time to keep track of their evolving needs and preferences.

For example, trends analysis can reveal new pain points in the customer journey.

Examining customer feedback or support tickets can help you identify recurring issues or growing dissatisfaction at different touchpoints. Such knowledge enables you to proactively address these issues before they become significant problems.

Step 4: Act on customer behavioral data analysis to improve customer satisfaction

The final step involves acting on the insights you gained by analyzing the customer journey data. What exactly you do will depend on the problems you’ve identified.

For example, to improve the conversion rates at the sign-up stage, you could enable single sign-on (SSO) or delay the email confirmation. To improve feature discovery and drive upsells , you could trigger in-app messages with contextual prompts.

The best customer journey analytics tools for SaaS

To effectively track and analyze user behavior at all touchpoints in the customer journey, you need the right tool stack .

Let’s check out a few customer journey analytics tools available to SaaS product teams.

Userpilot – The complete product growth and analytics platform

Userpilot is a digital adoption platform that offers feedback, analytics, and engagement functionalities.

In practice, this means that you can track product usage , gather customer feedback , analyze the data for insights, and then act on it to drive engagement and conversions with in-app guidance.

What customer journey analytics features does Userpilot offer?

• Event tracking, including custom events
• Goal tracking for customer journey analysis
• Funnel analysis and paths (coming soon)
• Feature usage tracking ( clicks , hovers, text infills)
• In-app surveys to gather customer feedback
• Survey, checklist, and resource center analytics
• User segmentation
• Real-time data relay for event-based message or survey triggering
• Webhooks and integrations with specialist analytics tools, including Amplitude, Heap, and Mixpanel

Userpilot offers 3 pricing plans.

The lowest one, Traction, starts from $249/month if paid annually. It gives you access to most of the analytics features above with the exception of webhooks and event-based content triggering.

To get access to the features, you’ll need either the Growth or Enterprise plan. Both of them come with custom pricing and usage limits.

Amplitude – Advanced analytics platform

Amplitude is a dedicated analytics platform with cutting-edge functionality.

Here are the top Amplitude features :

• Cohort analysis/customer segmentation
• Milestone analysis/goal tracking for customer journey analysis
• Funnel and impact analysis
• Conversion drivers for attribution analysis
• Pathfinder for user flow analysis
• Root cause analysis
• Custom dashboards
• Real-time data reporting
• Integrations with feedback and engagement tools

Amplitude offers 3 pricing plans.

The lowest one is free and it gives you access to the main customer journey analytics features.

Google Analytics – Free analytics platform to track customer journeys

Google Analytics 4, the new incarnation of the legendary Universal Analytics, allows you to track both web traffic and in-app user behavior. This makes it a comprehensive analytics platform for end-to-end journey tracking.

The main GA4 features include:

• Real-time activity tracking
• No-code event tracking
• Event filtering by category, action, and label
• Behavior reports – insights into visitor interactions with your website or product
• Audience reports
• Acquisition reports
• Goals and conversion tracking
• Funnel analysis
• Customized dashboards

All of the above features are available for free.

However, to get access to features like attribution analysis, you need the Analytics 360 subscription which is pretty expensive – it costs up to $12,500/month.

Customer journey analytics allow teams to gain a deeper understanding of user behavior at various touchpoints. As a result, they can optimize the journey by removing friction and providing users with the guidance they need to achieve their goals in less time.

If you want to see how to use Userpilot for customer journey analytics, book the demo!

Leave a comment Cancel reply

Save my name, email, and website in this browser for the next time I comment.

Get The Insights!

The fastest way to learn about Product Growth,Management & Trends.

The coolest way to learn about Product Growth, Management & Trends. Delivered fresh to your inbox, weekly.

The fastest way to learn about Product Growth, Management & Trends.

You might also be interested in ...

8 important customer satisfaction metrics to monitor sentiment, 14 best user tracking tools for saas in 2024.

Aazar Ali Shad

Top 12 Dashboard Reporting Tools For SaaS in 2024