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The What, Why, and How of Customer Journey Analytics

According to PWC, 86% of customers are willing to pay more for a better customer experience. Despite this, nearly 80% of consumers say that brands do not understand them as individuals, resulting in a bad customer experience.

Having a clear understanding of how and through which channels your customers interact with your brand plays a huge role in improving your customer experience. That’s why an optimized customer journey is an important part of a successful company.

So how do you know if all is well in your customer journey? Are surveys sufficient, or do you need other methods to understand your users’ expectations and pain points along the customer journey? How does customer journey analytics help you solve problems in your customer journey?

With this article, you will find solutions to all these and similar questions in your mind. So, without further ado, let’s get started.

What is Customer Journey Analytics (CJA)?

Before we explain what customer journey analytics is, let’s take a look at what the customer journey is.

The customer journey is the path that a customer takes to interact with your business. It outlines the entire process from the time they discover your brand to the moment they purchase your product and even the development of the relationship afterwards.

The customer journey doesn’t just focus on your users’ actions in this process and the channels they interact with. How your users feel and what they think is just as crucial for the customer journey.

Determining what the customer journey is like with only estimates will not lead you to accurate results. To make sense of this journey and develop strategies accordingly, you must analyze each step of the process correctly.

This is where customer journey analytics comes into play.

CJA is a process that tracks and measures how your customers interact with your brand at each stage of their journey. Thus, it helps you react to your customers’ expectations in real-time and develop strategies that will create value accordingly.

Customer journey analytics includes analysis of:

  • Customer’s needs
  • Customer expectations
  • Key metrics 
  • Customer satisfaction scores 

and more.

CJA is a robust process that can help you focus your customers, understand their behaviors, and get them to take the actions you want. Thanks to it, you can make decisions that will not only guide the customer to the final goal but also connect the customers to the process. Thus, you will also improve your customer experience.

Why Do You Need CJA?

The best way to understand why you need customer journey analytics is to learn about the benefits it can bring to your company and brand. 

So let’s take a look at the four key benefits of customer journey analytics.

#1 Understand customer expectations

Combining CJA data with survey responses can give you a complete picture of your customers’ wants and expectations.

You can also tailor your offer to customer preferences and recommend products that will solve their problems.

#2 Optimize your business strategy

Let’s say you have determined a business strategy and started to implement it. With CJA, you can determine if some stages of your funnel don’t align with your customers. 


This is exactly what customer journey analytics eliminates. CJA gives you detailed insight into the performance of all your channels. This way, you can easily observe what works and what doesnโ€™t.

With CJA, you gain insights such as:

  • Which channels perform best for engagement and lead to sales
  • Which customer paths resulted in a loss
  • How different are customer segmentsโ€™ journeys

and more.

#3 Increase marketing ROI

Customer journey analytics essentially entails collecting data from all sources, online and offline, allowing you to keep track of your customers and how they behave during the purchasing process. You can see which channels play an influential role in the customer journey and gain valuable customers. This way, you can focus on channels that offer better ROI and streamline your marketing spend.

#4 Discover new micro journeys

When you understand and analyze customer journeys in depth, you have the chance to improve existing journeys and discover new paths customers take. With CJA, you can notice the customer behaviors you miss every day and optimize the process according to these behaviors.

A step-by-step guide to Customer Journey Analytics

We can summarize customer journey analytics in three main stages:

#1 Create customer journey maps

Before analyzing your customer journey, it is important to create a customer journey map so that you can examine the whole process from a broad perspective. For example, the journey map of a SaaS company whose end goal is for its users to subscribe to its service might look like this:

1. Visiting the website

2. Reading blog articles

3. Subscribe to the e-mail newsletter

4. Reviewing case studies

5. Requesting a demo

6. Subscribe

#2 Determine the data you need to collect

To analyze the customer journey, you must first have data that you can analyze. That’s why you should gather all the data you need from each user journey stage.

Continuing with the SaaS company example, here are some data you might need to analyze for CJA:

  • Blog posts that drive revenue
  • Churn by blog posts
  • Email open rates
  • Number of users who sign up for a trial

and more.

At each stage of your customer journey, there are specific actions you want your customers to complete. It is essential that you clearly define both the actions and the milestones that need to be completed so you can know what to measure, and in what situation you will achieve the success you aim for.

#3 Analyze the customer data

When you reach this step, you now have a customer journey map you can follow and the data you need to pay attention to at each stage of this journey. Now what you need to do is simple: Analyze all this customer data to generate meaningful insights.

Using metrics and KPIs is the fastest and most effective way to analyze customer data. As a result of these analyses, you can determine the channels where your customers spend the most time, what they like the most and what disappoints them. This way, you can extract the necessary marketing insights and improve your customer journey.

How Can You Make the Most of Customer Journey Analytics?

Implementing customer journey analytics is not an incredibly challenging process. But that doesn’t mean there aren’t practices that you need to pay attention to get the best results.

Here are the top considerations to get the most out of customer journey analytics:

#1 Be clear on your goal

Consider a user who hears abour your brand for the first time. What do you want this user to complete at the conversion stage? Ask for a demo, sign up for a trial, or maybe make a purchase? 

The important thing at this point is to be clear about your ultimate goal. Once you’ve decided which customers will eventually reach which point, it’s easier to improve other channels in the customer journey. 

#2 Develop maps for each customer segment

Each customer segment is unique. Their expectations, desires and pain points, of course, differ from each other. Therefore, how one segment interacts with your brand and what pushes them to make a purchase will not be similar to another. You must keep this in mind. This way, you can create a customer journey map that caters directly to each segment so you know what to expect.

#3 Perform CJA regularly

Customer journeys are highly dynamic processes. Customers’ expectations and challenges are constantly changing. Likewise, your customer segments do not stay the same for life. No matter how high your retention rates are, some customers leave and new customers fill their places. Therefore, CJA is not a “set it and forget it” kind of process. You need to review regularly to make sure everything is in order and never stop making improvements to your customer journey.

#4 Use Automation to Enhance Your Customer Journey 

It’s challenging to manually track how your customer journey is and where you need improvements. With the right analytics tool, you can easily streamline this entire process.

With a tool like HockeyStack, you can simplify CJA by creating custom dashboards where you can track and analyze your customer journey. You can also follow the process in real-time and improve the process with the right interventions at the right time.

Let’s take a closer look at the customer journey analytics dashboards you can create with HockeyStack.

Create Your Own Customer Journey Analytics Dashboard with HockeyStack

HockeyStack has features to assist you at every stage of customer journey analytics. For example, with HockeyStack you can identify and visualize each stage of your customer journey. You can see in real-time how many users passed the key milestones of the journey and how many dropped off. In this way, when things do not go well at any stage of your customer journey, you can instantly notice and take actions to solve it.

Another valuable feature of HockeyStack for CJA is that it collects the data you need to analyze at each stage of your customer journey in real-time and allows you to analyze it with metrics. All you have to do is specify all the metrics you need to track in customizable dashboards. HockeyStack takes care of everything for you, giving you more time to determine your business strategies. Exciting, isn’t it?

If all these meet your expectations and interest you, what are you waiting for? Sign up for a free trial for HockeyStack right here and start leveraging the power of customer journey analytics.

FAQs

Are customer journey mapping and customer journey analytics the same thing?

Customer journey analytics and customer journey mapping are separate but interrelated processes. A customer journey map is a process of visualizing all the key points along the customer journey. To take advantage of customer journey analytics, you must first create a journey map and define the entire process.

How to track customer journey analytics?

The best way to track customer journey analytics is to use an effective analytics tool.

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