What if you could observe how clients navigate their journey with your brand, including the touchpoints where they spend the most time, what excites them, and what holds them back?
Customer journey analytics is the key to making this a reality. This strategy involves mapping out every interaction across channels and showing the hidden patterns that drive customer behavior.
This blog explores customer journey analytics, its importance, and effective ways to implement it to enhance the customer experience.
What is customer journey analytics?
Customer journey analytics involves gathering and analyzing data from all customer interactions with a brand across every touchpoint.
It’s more than just mapping the customer journey; it examines how each interaction influences the customer’s behavior and decisions.
When analyzing customers’ journeys, you should consider some of the key components including:
- What are your customers’ primary and secondary needs?
- How satisfied are your customers at each touchpoint?
- At which stage of their journey did they experience emotional highs and lows?
- For each touchpoint, what are the key customer metrics to measure and analyze?
By focusing on these aspects, brands can learn how to effectively direct their attention to the exact needs of their clients and resolve any pain points along the way.
Customer journey analytics vs customer journey mapping
Though customer journey analytics and customer journey mapping may seem different, they are often connected processes that give information on customer interaction at every touchpoint across their journey with the brand.
The table below outlines the main differences between customer journey analytics and customer journey mapping.
Aspect | Customer journey analytics | Customer journey mapping |
Definition | The process of gathering, analyzing, and interpreting data that relates to client interactions across touchpoints | A visual representation of the different stages in the journey of a customer towards achieving a goal with a business |
Purpose | To collect insights from customer data | To visualize and analyze the experience from the client’s perspective |
Tools | Uses data visualization and statistical analysis software | Involves brainstorming sessions, workshops, and tools for designing, like flowcharts or diagrams |
Focus area | Majors in quantitative metrics like engagement levels, conversion rates, and behavioral patterns | Concentrates on qualitative metrics like pain points, emotions, and motivations |
Timeframe | Often examines real-time or historical data to monitor ongoing performance trends | Often developed as a one-time project or regularly updated to reflect changes in customer experience |
Stakeholders involved | Primarily involves marketing teams, data analysts, and business intelligence professionals interested in decision-making | Involves cross-functional teams in marketing, UX design, and product management |
Application | Used in real-time monitoring of campaigns, performance tracking, and optimizing marketing strategies | Employed for strategic planning in improving user experience design and service improvements |
6 Simple steps to master your customer journey analytics
Utilizing customer journey analytics allows businesses to determine opportunities for improvement, allowing them to tailor marketing strategies and meet client needs. Here is how to effectively utilize analytics in your organization.
Outline goals and objectives
Every company should start by defining clear goals for its customer journey analytics, whether it’s to understand customer behavior, enhance user experience, or identify key touchpoints.
Once the purpose is set, establish measurable targets to help track progress and guide data-driven improvements.
Moreover, you should involve cross-functional teams to add diverse perspectives that ensure the customer service goals are well-rounded and focused on enhancing the customer experience.
Map the customer journey
Once your goals are set, the next step is to map the customer journey.
Research shows that 79% of companies say journey mapping has helped them become more customer-centric. To optimize the customer journey, follow these key steps:
- Identify all customer touchpoints across channels, from awareness to post-purchase, to ensure no step is missed
- Build customer personas using data from reviews, social media, and direct interactions
- Use CSAT surveys, analytics, and feedback to uncover churn drivers, purchase motivators

Finally, you need to continuously update the journey map so that it aligns with evolving customer needs and delivers a seamless experience.
Select the right analytics tools
Consider the types of data you need to collect and then select the right tools to use accordingly. You can combine web analytics for behaviorial trends and customer feedback surveys for deep insights.
Moreover, ensure the tools can handle your data and are user-friendly, with reliable support to empower your customer service team for ongoing analysis.
To make the most of your customer analytics strategy, it’s essential that you do the following:
- Ensure data compatibility with the type and volume of data you want to analyze
- Evaluate integration capabilities with existing customer service systems
- Assess the user friendliness of the tool
- Check support options such as documentation, training, and customer service
Make good use of your analytics tools to compile and analyze data and to determine customer service trends along the clients’ journey.
Collect all the necessary data and analyze
Different touchpoints tell a different story about clients’ experiences along the journey. Don’t leave any stone unturned; get data from all channels. You can:
- Practice social media monitoring and listening to know what clients have to say online.
- Retrieve conversation history from each support ticket
- Leverage website analytics tools on the general information and reports
- Check the records of purchases to know the patterns, churn or retention rates, and customer preferences
- Carry out customer satisfaction surveys

Good analysis throughout the journey gives companies a clearer picture of what their customer service experience looks like from a third-party perspective.
Identify and make improvements to the customer journey
Use the client journey insights to pinpoint customer pain points, delays, or dissatisfaction across touchpoints, whether during onboarding, support, or post-purchase.
Identify where friction occurs in the support process, then implement strategies to streamline and improve the experience.
Example
After customers upgrade their service plans, many visit the support page but don’t reach out directly. This behavior may signal confusion about new features or billing.
By analyzing this pattern, the company can proactively improve onboarding materials, clarify billing details, and reduce customer frustration, without waiting for complaints.
Test different workflows
How do you know if the final analysis information is efficient or if there are areas that need improvement?
Start by checking which customer journey analytics strategies provide accurate insights about each touchpoint.
Every workflow is different, and depending on the type of analysis carried out, one should expect varying insights.
Using A/B testing, you can examine the customers’ journey across multiple workflows. If the insights are consistent, you can rest assured that the customer journey analytics are effective.
Importance of customer journey analysis
It’s one thing to map your customers’ journey and a whole different thing to fully analyze and get useful insights. Let’s look into some of the key perks of customer journey analysis, for any business.
Customer journey analysis offers a powerful lens into these interactions, helping businesses uncover hidden patterns, optimize experiences, and make smarter decisions. Below are some of the key perks of customer journey analysis for any business.
- Provides a better understanding of customers: Customer journey analytics provide valuable insights into customer preferences, helping tailor marketing efforts more effectively.
This kind of intelligence can give you a competitive edge, especially considering that nearly 69% of businesses admit they don’t truly understand how their customers think.
- Helps improve customer journey experience: Insights derived from customer journey analytics help support teams identify friction in the customer journey, allowing businesses to improve content, navigation, and overall interaction quality.
- Empowers businesses to make data-driven decisions: Businesses can eliminate guesswork and base their decisions on the actual measurable behavior of customers just from insightful information, enabling smarter targeting, personalization, and strategic planning.
- Increases sales and ROI: Analytics help pinpoint high-performing channels and optimize resource allocation, leading to smoother purchase paths and increased revenue.
Customer journey analytics software and tools
For practical analysis of customer journeys, organizations use various tools to provide information about customer behavior, preferences, and pain points. Below is the customer journey analytics tools used by businesses:
Customer data platforms (CDPs)
Businesses can centralize customer data using CDPs, enabling real-time updates, segmentation, and personalized experiences.
Twilio Segment is one example, helping route customer data to integrated systems. It gathers first-party data from interactions across different communication channels to create a detailed customer profile.

Business intelligence (BI) tools
BI tools merge data from various sources to generate analytics and visualizations that reveal key customer insights.
BoldBI is one example, helping businesses interpret data for smarter decisions and transform it into actionable intelligence that drives smarter decisions, enhances performance, and empowers teams to identify trends, optimize strategies, and stay ahead of the competition.

Customer engagement platforms (CEPs)
Businesses can enhance customer engagement with features like live chat support and a unified omnichannel inbox.
Customer engagement platforms (CEPs) unify data from multiple channels to provide a holistic view of the customer journey, enabling personalized communication that adds more value to the customer experience.
One example is BoldDesk, which helps support teams interact seamlessly across all touchpoints. It centralizes customer queries from email, chat, and social media into a unified ticketing system, enabling faster resolution, streamlined collaboration, and consistent service delivery.

Behavioral analytics (BA) tools
Companies use behavioral analytics tools to track and analyze different user behaviors such as website visits, time spent on pages, clicks, and conversion actions (purchases and sign-ups).
An example is Hotjar, which utilizes heat maps, session recordings and surveys to analyze how users interact with a website, assisting organizations in identifying pain points and improving usability.

Leverage customer journey analytics to grow your business
Insights from customer journey analytics enable organizations to have a deeper understanding of their customers, personalize their sales and marketing efforts, and make wiser decisions.
BoldDesk helps you capture insights at every customer touchpoint to help personalize engagement and improve decision-making.
Schedule a live demo or book a 15-day free trial to experience its powerful features. For more information, contact BoldDesk support.
Do you have any additional information? Share your comments in the section below!
Related articles
- Customer Experience Analytics: Important KPIs and Use Cases
- Customer Service Analytics: Types, Uses and Benefit
Frequently asked questions
The five main stages of a customer journey are:
- Awareness: When customers first discover your brand
- Consideration: Where customers research and compare options
- Purchase: When customers decide to buy and complete the transaction
- Retention: The post-purchase experience focused on satisfaction and continued engagement
- Advocacy: When satisfied customers become loyal brand ambassadors who refer others
Each stage requires different strategies, messaging, and analytics approaches to optimize the customer experience and drive business growth.
The data used in customer journey analytics includes demographic, behavioral, transactional, psychographic, feedback, engagement metrics, and contextual data.
Artificial Intelligence transforms customer journey analytics by automatically identifying patterns humans might miss, predicting customer behavior with high accuracy, personalizing experiences in real-time, and processing vast amounts of data at scale.