Customer Journey Analytics: The Complete Guide

A comprehensive guide to customer journey analytics

Today’s digital-savvy consumers interact with multiple channels throughout their day — often combining more than one at the same time to get the answers they seek. To drive more business in an omnichannel environment, customer journey analytics help you understand the key touchpoints on your customer journeys so they find you more often and provide insights to improve their experiences once they get there.

Key takeaways

Ideally, your vision for your customer journeys and how they experience your brand online aligns with their actual journeys and experiences This guide will define customer journey analytics and provide a better understanding of how the data can help you:

Get the 30,000 ft view

Whether it’s your website or mobile app, social media, email or another channel, you need to know how your customers are engaging with your digital brand to deliver the right experiences that help them move forward but also support your business goals.

Keep your customers engaged

Consumers are more fickle than ever with user-friendly devices and vast resources to explore at the touch of a button. Avoid analysis/paralysis and get the insights you need to identify where your customers are struggling and why they may be leaving to guide user experience (UX) changes that keep them engaged.

ROI-focused guidance

Customer interests are fluid and constantly changing. Understand how user behavior ultimately impacts your business metrics to focus your efforts where it matters most to the bottom line and ensure your touchpoints are aligned with each stage of the customer journey: awareness, consideration, purchase, retention and advocacy.

What is customer journey analytics?

Digital experiences must continue to evolve in order to maintain alignment with the needs of current and prospective customers. Customer journey analytics help teams that manage these experiences better understand the impact each digital interaction has on a customer’s decision.

Customer experience (CX) and UX professionals use customer journey analytics tools to gather important customer engagement data at different touchpoints and channels of the customer journey over a period of time. The data tells a story of what customers like and where they struggle. This information enables teams to better optimize the customer journey and improve CX.

💡 Expert tip: Combining customer journey analytics with a digital experience intelligence (DXI) platform provides a deeper understanding of why customers behave the way they do. Digital teams can use this information to not only optimize the customer journey to improve the user experience but also to quantify the revenue impact as a result of poor experiences.

Definition of customer journey analytics

Customer journey analytics is the process of gathering and analyzing key data points of the customer experience across every touchpoint in the customer journey. This data illuminates customer behaviors and is used to guide decisions on where and how to improve the experience.

User journey analytics vs. customer journey analytics

At the heart of understanding the difference between user journey analytics and customer journey analytics are the types of channel(s) involved with the journey itself.

Specifically, a user journey is solely about a person’s interactions online. The goal of the online journey may be about finding a specific product at the best price or browsing or searching for information on a specific topic. User journey analytics are purely focused on the user’s experiences in the digital space.

Customer journeys are often more robust and complex as they include both online interactions but also offline engagements. As such, customer journey analytics look at every channel a customer goes through–whether they're visiting a website on their laptop, interacting with a mobile app or speaking to a customer service representative on the phone or in person at a physical location.

The role of customer journey analytics in customer journey mapping

To completely understand customer experiences, marketing and IT teams need to share and understand customer data to collectively make data-driven decisions. Helping customers move forward with their overall journey requires being able to see that journey in totality at a high level but also having the ability to dive into the weeds when needed to better understand what’s happening at each stage.

Customer journey maps are a great way to visualize all of the touchpoints customers are interacting with along their journey with a brand, service or product. Journey maps start at the very beginning and encompass all of the steps a customer goes through to complete an objective over a period of time.

For a potential customer, this could start with gaining initial awareness from advertising, social media or simply browsing the web on a related topic through their actual purchase, continued engagement with customer service, advocacy via a product review or social media and a repeat purchase.

Omnichannel customer journeys often include multiple opportunities to convert a potential customer by completing a desired task before completing their ultimate objective of making a purchase. These conversions could be signing up to receive free content, creating a new account or asking to speak with a company representative to answer their questions.

👉🏻 Check out the guide Digital Customer Journey Mapping in Today's World.

The importance of analyzing customer data

The ability to create more meaningful customer experiences that convert hinges on leveraging the data behind every interaction. Customer journey analytics measure key metrics and capture valuable behavioral data to provide a better understanding of where customers are spending their time and how they’re feeling at each stage of the journey.

In addition to illuminating why a particular step is converting at a high rate that can be applied to other areas, customer journey analytics help identify potential pain points and frustrations that hinder conversions or, worse, lead to abandonment. This information helps digital teams gauge where they’re winning and losing and determine where improvements need to be made to achieve desired business outcomes.

Benefits of customer journey analytics

Customer conversations are still happening at the same frequency, but the digital space facilitates these interactions in an entirely new and often disparate way. Customers want experiences that enable a continuous conversation even though they now happen through a series of separate engagements through more channels than ever before.

Leveraging customer journey analytics can help businesses gain valuable insights into what is important to their customers so they can evolve those experiences to better meet customer expectations. Companies that embrace a customer-first mentality are succeeding because they are invested in making the most of every interaction to continually move their customers forward in their journeys.

Maximizing CX investments

Today’s customers have little patience and high expectations—especially when they’re engaging digitally with a brand. If they feel like they’re starting over after previously engaging with a company online, they will likely move on to a competitor.

Access to loads of valuable data and additional context collected from customer journey analytics drives the ability to assess individual customer needs in real-time. For those entrusted with optimizing the experiences along the customer journey, data-driven insights can lead to user experience changes that improve customer engagement. More personalized interactions fueled by customer journey analytics can ultimately lead to higher conversion rates with new customers and reduce customer churn.

With the ability to predict customer behavior from previous actions, high-risk customers can be offered a different experience that help address the way they feel about the brand to improve retention. Variations on this approach combined with audience segmentation can result in more loyal customers and even generate additional purchases from existing customers.

Growing the bottom line

The days of guessing what customers want are long gone. While providing a toolset to help improve customer experiences, investment in a customer-first approach with customer journey analytics can drive powerful change throughout a company culture that results in new revenue-generating opportunities.

In addition to helping optimize digital experiences, product development leaders can gain valuable insights that can help guide and prioritize their efforts. Identifying valuable improvements to existing products that aren’t meeting sales targets will improve customer satisfaction. Customer journey analytics also inform the opportunity to develop potential new product offerings and fill gaps in the product portfolio.

How customer journey analytics work

The way modern, digitally-driven customers arrive at a purchase decision is anything but prescriptive. There is no linear path from awareness to research to purchase to advocacy. Customers might require 7-8 interactions before becoming a customer, or they may transition from initial awareness to a purchase within a few seconds. In some cases, advocacy may happen as part of initial research or social media engagement without any purchase intent at all.

Customers are expecting their experiences to be informed and personalized to their specific needs regardless of where they are on their journeys. And they certainly don’t want this type of content to only be delivered on a single channel or entice them down a path to a product they’ve already purchased or isn’t currently available.

Customer journey analytics combine a variety of data sources and contextualized visualizations to help create the right content at the right time to help businesses maintain relevant, easy experiences that build relationships and empower customers. Gathering data on customer demographics, psychographics and how they behave provides a deeper context for a better understanding of the customer journey.

This added context from the various types of data is a critical part of building out a customer journey map and guiding refinements to each stage of that journey. The customer journey map provides the foundation for this ongoing analysis process.

👉🏻 Learn how to create effective customer journey maps in this complete guide.

Customer journey analytics tools and software

There are many digital and AI-powered tools to help maximize the customer journey analytics process and optimize areas of the digital experience to better connect with your customers and move them forward on their journey. Below we take a look at a few of the most common types.

Customer data platforms (CDPs)

CDPs are becoming an increasingly popular part of the marketing communications toolset. With the ability to centralize data collection from multiple sources, CDPs help marketers refine customer profiles along with creating and managing segments to ultimately drive engagement across a variety of channels. While they are easier for non-technical people to use, finding the right solution can be challenging, given the number of options and volatility in the market. Additionally, integrating a CDPs into a company’s marcom toolset can be costly and time-consuming.

Customer engagement platforms (CEPs)

CEPs take the concept of customer relationship management (CRM) to the next level by consolidating customer data and engagement functionality typically provided by multiple systems. Marketers and other teams within the company, like sales, service and support, are using the same customer data and working within the same system to perform their individual tasks, which can help provide more personalized customer experiences.

Behavioral analytics (BA) tools

Behavioral analytics tools collect and analyze data from actions performed by users on a website or app. This data provides a foundation for businesses to understand how users interact with the different sections and touchpoints of their digital experiences. The data can inform decisions on user experience changes while providing a guidepost to show if the changes are working to improve the desired outcomes.

BA tools include:

• Traditional analytics like Google Analytics

• Session replay tools that capture user interactions, like Glassbox and Crazy Egg

• Heatmap tools that show where users are interacting the most, like Lucky Orange

• A/B testing tools that allow testing of variations to a website or app page, like AB Tasty and Adobe Target

• Voice of customer (VoC) and survey tools, like Medallia and Survey Monkey

👉🏻 Want to learn more about BA tools? Check out The Complete Guide to Behavioral Analytics.

Business intelligence (BI) tools

BI tools help guide more informed decisions by providing accurate data across a variety of business systems to better understand what’s happening throughout the entire organization. In addition to mining the data to illuminate valuable insights, BI tools also provide visualization capabilities to transform the data and insights into graphs and charts that can be incorporated into dashboards that non-technical business leaders can use to monitor and make changes to the business.

🔥Hot tip: A digital experience intelligence (DXI) solution combines all these tools into one platform so you can access advanced insights across the company in one place. These advanced insights give you the complete picture of the digital customer experience, not just bits and pieces.

Types of data used in customer journey analytics

A variety of data types are needed to help businesses ensure they are providing an exceptional customer experience at every touchpoint of the customer journey.

Basic data analytics can help set the stage by providing quantitative measurements of customer actions taken when interacting with a touchpoint—how long they stay, what pages are generating the most traffic, if they click a desired call to action, etc. Qualitative data helps fill in the details around these actions by providing the human context that helps illuminate what’s driving their pain points and successes. Combining these disparate types of data provides insights to optimize the touchpoints in the website user experience.

Quantitative data

Quantitative data is a set of touchpoint and engagement performance metrics for a digital asset (website, mobile app, etc.) that reflect how users interact with the experience. This numerical data is collected indirectly and pertains to different types of user actions. The most common quantitative data metrics involved with customer journey analytics include:

Session activity

The amount of time a user spends along with specific pages on your website or mobile app. Tracking this metric provides the ability to spot usage trends or anomalies. Significant drops in a short period might be related to a bug or other development issues, while a steady decline could identify an engagement problem related to the content or user experience.

Bounce rate

This is an indicator of when users leave your website or mobile app after viewing just a single page. The fact that users may be finding the information they were seeking when landing on the page—along with the page type and its content—should be considered when evaluating the bounce rate.

Open rate

This reflects the percentage of all emails in a particular campaign that were opened. This information is especially helpful when evaluating email subject lines and/or preheader text as part of an A/B testing initiative.

Conversion rate

This is the percentage of users who perform a desired action, such as clicking a CTA button.

Qualitative data

Quantitative data is a great way to track key customer engagement touchpoints and identify where to make necessary changes to address basic issues with a digital experience. This data can also provide a solid foundation to start implementing more strategic changes to specific parts of the customer journey, such as improving information in a shopping cart or making additional suggestions on a checkout page.

While it may be harder and take longer to acquire, qualitative data provides the valuable “color” surrounding the quantitative numerical data and illuminates a more complete picture of the customer journey. Qualitative data also helps improve the customer experience by understanding the perceptions, feelings, thoughts and preferences of your users. Qualitative data collection methods include one-on-one interviews, focus groups, surveys, observation notes and more.

👉🏻 Find out how teams can use qualitative data to improve the digital customer experience (CX).

The importance of having the right data for customer journey analytics

With today’s omnichannel customer journeys, the results of efforts to connect and build better relationships with customers along their journey will only be as good as the data that’s driving CX changes. It’s mission-critical to not only be able to see what actions customers are taking but also to understand the why behind the behavior.

Customers want more personalized experiences, and they are more likely to purchase from businesses that meet that expectation. Efficient, effective optimization of a customer journey can only occur with the right mix of data focused on key touchpoints and interactions while also providing the valuable human-centered context to understand what is driving the choices being made in those moments. The cost of making the wrong decisions couldn’t be higher as customers have plenty of options and likely won’t return after deciding to move on.

The power of custom journey data with digital experience intelligence

Customer journey data plays an important foundational role in identifying where to make changes that improve digital experiences—especially since today’s customer journey most likely starts and ends in the digital space. Yet, customer journey analytics tools provide a limited view of customer behavior. To create and refine digital experiences that ultimately lead to loyal customers, teams need to go beyond the basic information provided by typical quantifiable data.

Digital experience intelligence platforms are designed to take that data and maximize its value to help businesses build comprehensive and personalized experiences. That value is provided in the form of powerful insights that can lead to true one-to-one experiences with the right content that completes an end-to-end customer journey—from websites to apps to emails to SMS mobile messages and other messaging in social media and even digital advertising.

How to implement customer journey analytics in 4 steps

To provide the most value, there are a few key steps that align the paths of an ideal vision for a customer journey with what customers are experiencing. Taken in order, each step supports the next, along with helpful references that help provide focus during team discussions and prioritization to guide decision-making.

1. Identify goals

Successful journeys have an endpoint that is identified early on and set as a “north star” for initial planning efforts and to be referenced during critical moments of the customer journey. In addition to setting goals for particular interactions or performance metrics, every experience and related touchpoint should be aligned with supporting the goals of the business to ensure they are positively impacting the bottom line.

2. Collect and analyze data

With business and experience goals in place, establish a time parameter to collect the data. In some cases, a minimum amount of time is needed to get a sense for what is happening on a macro level. Seasonal timing, holidays and other events can create anomalies that can mislead teams if data is collected too quickly or without important context that could be influencing customer behavior. Additionally, qualitative data may take longer to secure—especially to meet a minimum threshold of customers surveyed or interviewed so the data is meaningful.

Once the data is collected, the next step is to analyze it. We’ve identified a few areas to be mindful of to ensure seamless digital experiences and anticipate customer needs to help along each step of the journey:

Points of friction

Look out for potential friction points in your digital experiences. This could be gaps in content that may not be providing what is needed to move on to the next step or a broken form. Friction points can also be technical issues or bugs, which could slow page load times down or app crashes.

Poor transitions

Successful omnichannel experiences rely on delivering the right content to customers at the right time. As they transition between a website, mobile app, email or text message, there are many potential issues that could lead to friction. If customers are challenged to perform a desired action, or they have to start over because their data gets lost, chances are they’re getting frustrated from the overall experience and are likely to abandon the website or app and never return.

Stage duration excess

Be especially critical of the time it should take a customer to complete specific tasks at each stage of the journey. Identify areas along the journey to minimize the time and effort involved—especially if the path to purchase is longer.

Replicate successes

Each interaction provides an opportunity to build (or lose) customer trust and happiness. While a lot of time and effort is spent identifying pain points and issues with the customer experience, things that are doing well and working as intended should be noted. Once identified, those learnings should be applied to other areas to optimize the customer experience for success.

3. Capture actionable insights

Along with providing the power of context, turning customer journey analytics into actionable insights enhances the ability to quickly assess customer needs and even anticipate them to make every experience more relevant and personal.

4. Implement changes based on insights surfaced

The ability to combine customer journey analytics with digital experience intelligence lets teams gain an understanding of why customers behave the way they do so you can fix any issues or optimize the journey to improve the digital user experience.

Whether it’s refined recommendations based on previous searches, a specific program that helps customers better understand a new product or a personalized email campaign and landing pages, quickly implementing these experiences helps connect with customers and let them know you value them. Combined with digital experience intelligence data, customer journey analytics can also quantify the revenue impact of the cost of poor experiences.

🤔 Did you know? There are limitations to standalone customer journey analytics tools. Customer journey analytics tools provide a limited view of customer behavior. The ability to combine customer journey analytics with digital experience intelligence lets teams gain an understanding of why customers behave the way they do so you can implement changes to fix any issues or optimize the journey to improve the digital user experience. Combined with digital experience intelligence data, customer journey analytics can also quantify the revenue impact of the cost of poor experiences. Armed with these insights, CX teams can focus on the areas that provide the most impact to optimize that experience and add the most value to the organization.