Customer Journey Analytics: Definition, Tools, & Examples

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.

References

• 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.