Here’s how to analyze & improve your customer journey analytics

    Abstract illustration of data visualization with line graphs, bar charts, and user icons connected by dotted lines on a light pink background.

    Want to unlock hidden gems in your customer journey data?

    Many teams are drowning in data but still can’t see where customers drop off, what causes friction, or how to improve retention. 

    Customer journey analytics solves this by bringing everything together into one clear, structured view. It helps you see not just what’s happening, but why and what to do about it.

    In this TheyDo guide, we’ll help you understand customer journey analytics and how to use it to uncover insights and improve the entire customer experience. 

    But first…

    Why listen to us?

    At TheyDo, we empower enterprises to align teams around customer journeys using our AI-driven insights, structured frameworks, and seamless collaboration. With global clients like Cisco, IBM, and PostNL, we’ve helped lots of enterprises uncover hidden insights in journey data, reduce time to market, and unlock real business value.

    What is customer journey analytics?

    Customer journey analytics is the process of collecting and analyzing data across every touchpoint a customer has with your business. It helps you understand the what, when, where, and why of your customer behavior, so you can improve their experience at every stage. 

    Unlike customer journey mapping alone, this approach goes beyond visual diagrams. It connects real behavior to outcomes, helping you spot patterns and opportunities.

    With the right tool, customer journey analytics can turn raw data into actionable insights. This helps you make smarter decisions by focusing on customer needs and prioritizing important changes. 

    Customer Journey Analytics vs. Product Analytics

    Customer journey analytics and product analytics both help teams understand user behavior, but they focus on different parts of the experience.

    Customer journey analytics looks at the complete customer path across all channels. It focuses on:

    • Full lifecycle tracking from awareness to retention

    • Cross-team data from marketing, sales, support, and product

    • Friction points and team alignment around customer insights

    • Tools like TheyDo for mapping the broader experience

    Product analytics focuses on in-product user behavior:

    • Actions like clicks, feature usage, and session length

    • Product team optimization of onboarding and usability

    • Tools like Mixpanel for product-specific engagement

    Journey analytics provides the big-picture customer view while product analytics dives deep into product performance. Together, they optimize both overall experience and product functionality.

    Why customer journey analytics matters

    • Uncover friction points: Identify where customers struggle or drop off, so you can improve the experience and reduce churn.

    • Prioritize improvements: Focus on the touchpoints that have the most impact on conversion, retention, and satisfaction.

    • Align teams around customer needs: Provide a shared view of the customer journey to keep marketing, product, and support teams working toward the same goals.

    • Increase ROI across channels: Optimize spend by understanding which parts of the journey drive the most value.

    • Turn data into action: Move from scattered metrics to strategic insights that guide smarter, customer-driven decisions.

    How to implement customer journey analytics

    Step 1: Define your goals and align stakeholders

    Start by defining the business goals you want to achieve. These could include:

    • Reducing customer churn

    • Improving onboarding

    • Shortening time to value

    • Driving expansion

    Each goal requires tracking different customer journeys and metrics.

    Next, identify the most critical journeys tied to these goals, such as onboarding, support resolution, or renewals. Work with teams across the organization to pinpoint where customers face issues or drop off.

    To do this effectively:

    • Involve key stakeholders from relevant teams

    • Focus on high-impact journeys first, avoid trying to track everything at once

    • Set clear success metrics (e.g., higher NPS, lower churn, better conversion rates)

    TheyDo simplifies this process. Our structured taxonomy creates a system to categorize and align goals for each journey across the organization. So, all teams have a single, shared view of the customer journey, including what’s expected at each stage, making collaboration easier and more efficient. 

    Step 2: Gather cross-channel data

    Once your goals are clear, the next step is collecting data to understand how customers experience your product or service. This includes both digital and offline interactions.

    Start by identifying your core data sources:

    • Website and app analytics (e.g., click paths, bounce rates, conversions)

    • CRM and sales data (e.g., lead status, account activity)

    • Customer support systems (e.g., tickets, live chat, call logs)

    • Marketing platforms (e.g., email engagement, campaign performance)

    • In-store or physical experience metrics, where applicable

    • Qualitative feedback (e.g., survey responses, interviews, reviews)

    Often, this data is scattered across fragmented systems, making it hard to see the full customer journey.

    TheyDo solves this by bringing all your data into one single view. Our customer journey framework helps you centralize customer journeys into a structured system. This makes it easier to analyze and manage across the organization.

    When gathering data:

    • Focus on sources that directly reflect customer actions and outcomes

    • Ensure the data is clean, consistent, and reliable

    • Avoid tracking metrics that don’t support your goals

    Strong customer journey analytics rely on quality data to reveal customer behavior and guide smarter decisions.

    Step 3: Identify key journeys and customer segments

    Tracking every touchpoint across all journeys can be overwhelming, especially in large organizations with multiple teams, products, and audiences.

    To stay focused, start by identifying the journeys and customer segments that directly support your business goals.

    Then, map out the main stages of your customer lifecycle. This gives you a clear structure and helps you find where customers face challenges or drop off. 

    Once that’s done, focus on the specific journeys that align with your key metrics, such as retention, conversion, or onboarding success.

    Common customer journey stages include:

    • Awareness: When customers first discover your brand

    • Consideration: When they research and compare options

    • Purchase or conversion: When they decide to buy

    • Onboarding: When they start using your product or service

    • Usage and support: Ongoing use and support interactions

    • Renewal or churn: When they choose to stay or leave

    But even the best journey map is incomplete without customer segmentation. People in different segments may go through the same journey, but experience it in very different ways. 

    Segment your customers based on:

    • Industry or vertical

    • Company size or structure

    • Region, language, or location

    • Product tier or use case

    • Engagement level (e.g., frequent vs. occasional users)

    Develop buyer personas for your most important customer segments. With our persona organization feature, teams can tag, categorize, and compare personas using a customizable 2x2 matrix. 

    This helps you prioritize the journeys that matter most and tailor your strategy to specific customer needs.

    Step 4: Visualize and analyze journeys

    Visualizing the customer journey gives you a clear view of how people move through your product or service. 

    Journey visualizations bring structure and clarity. They show how touchpoints connect, where customers face friction, and what they’re thinking or expecting at each stage. This is valuable in large organizations, where teams often have an incomplete view of the customer experience.

    A complete journey visualization should include:

    • All customer touchpoints: emails, web visits, support tickets, product usage

    • Stages of the customer lifecycle, grouped to show progression

    • Customer mindset at each stage: expectations, emotions, and needs

    • Relevant data, such as drop-off rates, NPS scores, and support volume

    • Ownership and impact: who’s responsible for each step and how it affects business goals

    TheyDo supports this process with real-time customer journey mapping. Instead of working with static diagrams or fragmented tools, teams use a shared platform that updates continuously, ties each journey to business goals, and links directly to supporting systems.

    Once journeys are visualized, the next step is analysis. This helps you identify where to act and what to improve. You can:

    • Pinpoint bottlenecks or friction in critical journeys

    • See where customer expectations aren’t being met

    • Compare experiences across different segments or regions

    • Use both metrics and feedback to uncover hidden patterns

    Our Journey AI tool adds real value here. It transforms raw customer data into actionable insights by mining, enriching, and summarizing feedback across journeys. This helps you quickly identify opportunities and enhance CX. 

    With the right tools, teams stay aligned, customers get better experiences, and your strategy becomes easier to execute.

    Step 5: Turn your insights into action

    Customer journey analytics is only valuable if it leads to change. While visualizing and analyzing journeys is essential, many teams stop there, discussing insights in meetings without turning them into action.

    To make journey data useful, treat your insights as strategic input. Each drop-off, complaint, or friction point is a signal. The goal is to link those signals to real business opportunities and act on them.

    Here’s how to move from insight to execution:

    • Prioritize issues based on business value, customer impact, and the effort required

    • Use opportunity scoring to determine which problems need immediate attention

    • Assign each opportunity to a specific journey step and a clear owner

    • Track progress across teams to ensure actions are completed

    With TheyDo, teams can link needs to business opportunities and coordinate actions across journeys, so nothing gets lost between planning and execution.

    Teams can also push updates directly to tools like Slack and Jira, ensuring insights are acted on as part of everyday work, not left sitting in dashboards. This creates alignment and removes the need to re-justify priorities every quarter.

    Top metrics for analyzing your customer journey

    1. Customer Retention Rate

    This is the percentage of customers who continue doing business with your company over a specific period.

    Formula:

    Customer Retention Rate = [(E-N)/S] × 100

    Where: 

    E = Number of customers at the end of a period 

    N = Number of new customers acquired during a period of time 

    S = Number of customers at the start of the period

    2. Conversion Rate

    This is the percentage of visitors or prospects who complete a desired action (purchase, sign-up, download, etc.).

    Formula:

    Conversion Rate = (Number of Conversions / Total Visitors) × 100

    3. Customer Satisfaction Score (CSAT)

    This is a measure of customer satisfaction with a specific interaction, product, or service experience.

    Formula:

    CSAT = (Number of Satisfied Customers / Total Survey Responses) × 100

    It typically uses a 1-5 or 1-10 scale, with satisfaction being between 4-5 or 7-10.

    4. Net Promoter Score (NPS)

    This measures customer loyalty and the likelihood of recommending your business to others.

    Formula:

    NPS = % Promoters - % Detractors

    It is based on a 0-10 scale with the question "How likely are you to recommend us?"

    Response: 

    Promoters: 9-10

    Passives: 7-8 (not included in the calculation)

    Detractors: 0-6

    5. Customer Effort Score (CES)

    This measures how easy it is for customers to interact with your company and resolve their issues.

    Formula:

    CES = Sum of all effort scores / Number of responses 

    It uses a 1-7 scale with the question "How easy was it to resolve your issue?"

    Response:

    1 = Very Difficult

    7 = Very Easy

    6. Customer Lifetime Value (CLTV)

    This is the measure of the total revenue a customer generates throughout their entire relationship with your business.

    Formula:

    Simple CLTV: The total revenue expected from a customer over time.

    CLTV = Average Purchase Value × Purchase Frequency × Customer Lifespan

    Advanced CLTV: A detailed estimate that factors in profit, frequency, and customer behavior.

    CLTV = (Average Monthly Revenue per Customer × Gross Margin %) / Monthly Churn Rate

    7. Churn Rate

    This is the percentage of customers who stop doing business with your company during a specific period.

    Formula:

    Churn Rate = (Customers Lost During Period / Customers at Start of Period) × 100

    Tools for Customer Journey Analytics

    1. Customer Journey Management Platforms (CJMs)

    Customer Journey Management platforms help you map, track, and improve the full customer experience. They create a shared view of key customer journeys, making it easier to spot issues and coordinate improvements.

    Popular tools: TheyDo, Smaply, UXPressia, SuiteCX

    2. Business Intelligence (BI) Tools

    BI tools turn raw data from different sources into visual dashboards and reports. They help track key metrics, spot trends, and uncover issues across the customer journey.

    Popular tools: Tableau, Looker (Google Cloud), Power BI

    3. Behavioral Analytics Platforms

    These tools show how users interact with your product or website. They also help teams understand patterns and identify friction points in real time.

    Popular tools: Mixpanel, Heap, Indicative

    4. Attribution Tools

    Attribution tools show which channels, campaigns, or touchpoints influence customer actions like conversions or drop-offs. They’re useful for optimizing marketing spend, analyzing multi-touch journeys, and measuring full-funnel impact.

    Popular tools: Criteo, Singular, Adjust, AppsFlyer, Branch

    5. Customer Engagement Platforms (CEPs)

    Customer Engagement Platforms (CEPs) add messaging and automation on top of customer data, helping teams deliver timely, coordinated interactions across channels. They support personalized communication based on real-time behavior and manage outreach across sales, support, and marketing.

    Popular tools: Twilio, Braze, Intercom

    6. Customer Data Platforms (CDPs)

    Customer Data Platforms (CDPs) bring together customer data from different sources into one up-to-date profile. They help teams segment users, track behavior, and power personalized experiences across the journey.

    Popular tools: Segment (by Twilio), mParticle, BlueConic

    Journey Analytics vs. Product Analytics

    Customer journey analytics and product analytics both help teams understand user behavior, but they focus on different parts of the experience.

    Customer journey analytics examines the complete customer path across all channels and touchpoints. Key characteristics include:

    • Tracks the full lifecycle from awareness to retention and renewal

    • Combines data from marketing, sales, support, and product teams

    • Helps identify friction points and align teams around shared customer insights

    • Uses tools like TheyDo to map and optimize the broader experience

    Product analytics focuses specifically on in-product user behavior. Key characteristics include:

    • Tracks actions like clicks, feature usage, and session length within your app or platform

    • Helps product teams improve onboarding, usability, and feature adoption

    • Optimizes the user experience inside your product interface

    • Uses tools like Mixpanel to analyze product-specific engagement

    While journey analytics provides the big-picture view of customer relationships, product analytics dives deep into how your product performs. Used together, they help teams optimize both the overall customer experience and product functionality.

    Customer journey analytics and product analytics both help teams understand user behavior, but they focus on different parts of the experience.

    Customer journey analytics looks at the full path a customer takes across channels, from first touch to repeat engagement. It combines data from marketing, sales, support, and product to show how people move through key stages like awareness, conversion, and retention. 

    This helps teams find friction points, align around shared insights, and improve the overall customer experience. Tools like TheyDo are ideal for this.

    Product analytics focuses on what users do inside your product or app. It tracks actions like clicks, feature usage, and session length to help product teams improve onboarding, usability, and retention. Tools like Mixpanel are common here.

    While journey analytics looks at the broader customer lifecycle, product analytics focuses on in-product behavior. Together, they help teams optimize the overall experience and how the product performs.

    Streamline customer journey analytics with TheyDo

    Customer journey analytics gives you the clarity to understand what your customers experience and where they get stuck. But without the right tools, it’s hard to go from insight to action.

    That’s where TheyDo comes in. With structured mapping, real-time collaboration, and seamless integrations, we turn scattered data into clear opportunities for growth. Our enterprise-grade solution helps teams identify high-ROI initiatives faster and focus resources where they'll deliver maximum impact.

    Join the teams using TheyDo to improve customer experience with a data-driven approach.