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!

TL;DR

• 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:

1. Users log into the product.
2. A welcome survey pops out.
3. Completing the survey triggers an onboarding checklist.
4. 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)
• Heat maps
• 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.

Conclusion

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!