6 insightful customer journey analytics examples and use cases

6 insightful customer journey analytics examples and use cases

CX leaders (Customer Experience leaders) embrace customer journey analytics in recent years to link consumer behavior and the KPIs used to gauge the success of organizations. By utilizing these solutions, you may collect, examine, and act on data about the customer journey to enhance customer experiences and fulfill company goals. 

In this article, we are going to talk about 6 insightful customer journey analytics to help you make the most of your marketing campaigns.

Top 6 insightful customer journey analytics examples and use cases

By Utilizing Journey Analytics, You Can save Money

A CX team at a major utility company observed the enormous financial impact of past-due payments and service disconnections, which generated profits of around $850 million.

The team’s analysis of the journey from past-due payments to service disconnect begins with the problem. Customers whose payments are 33 days past due are the first to be considered. A technician is then dispatched to the home to do a truck roll, which involves disconnecting the service.

Then, the team identifies that a significant portion of consumers who phone the service center after their service is disconnected pledge to pay their bill as soon as their next paycheck is deposited by merging rich data from their call center platform.

6 insightful customer journey analytics examples and use cases

So thanks to the use of journey analytics to discover that there is a roughly 70% decrease in the need to disconnect (and then rejoin) service in the test group. They argue that offering this option to every client in every location might prevent needless truck rolls that would cost close to a billion dollars.

Reduce the Number of Support Calls and Associated Costs with Customer Journey Analytics

Customer journey analytics are used by a retail bank to identify the root of new client service requests and improve operational effectiveness.

The group is trying to figure out how well its self-service options work when clients have trouble making a mortgage payment. The ‘Payment Message Sent’ Event, which reveals that 12.5M clients received a Payment Request notice, marks the beginning of their journey.

Then, they built distinct routes for clients who proceeded to utilize each of their three self-service channels: mobile, IVR, and web—in turn. 

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The team discovers that the IVR is the least efficient self-service channel for clients who are having issues with bill payment after reflecting on the Service Agent call. The IVR channel leakage of 81% is approximately twice as high as that of mobile and the web. 

Additionally, they observe that 60% of customers abandon the transaction at the previous stage and ask to talk with a service agent rather than attempting to make a payment through the IVR system. At this particular stage of the journey, the team takes action on this knowledge and examines the language to better comprehend the problem.

More clients pay through the IVR when the language of this particular IVR node is changed, which reduces IVR leakage, call volume, and call center costs.

Utilize Journey Analytics to Gain Insight Into What Influences Customer Effort Scores

A health insurance provider wants to know why its newly joined members’ attempts to set up automated premium payments result in such high customer effort scores (CES).

Therefore, the CX team employs customer journey analytics to examine the journeys of customers who set up automated payments using the website, mobile app, and call center to identify the root of the issue.

According to their data, 21% of members who set up payments on the mobile app ran into a problem that required a support call and increased CES. However, members who start the payment setting process over the phone or online report greater success and a lower CES.

The CX team uses this information to prioritize a project that will enhance the usability of their mobile app. To enhance their experiences in the interim, the team might direct newly recruited individuals toward lower-effort excursions.

6 insightful customer journey analytics examples and use cases

A Major Retail Bank’s Use of Customer Journey Analytics Helps Boost Credit Card Conversions

The goal of the credit card department at a significant retail bank is to increase millennials’ use of credit cards. The bank employs customer journey analytics to comprehend the part that various channels play in credit card offers and their individual efficiency.

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They identify numerous consumer journeys that take place both online and offline, including branch visits, website surfing, smartphone data, email data, and in-app interactions, that result in customers viewing credit card offers.

Within minutes, they learn how many clients accept or disregard the offer, as opposed to how many go on to apply for a card online. They can observe how many clients advance at each stage, how many abandon the process, and how many are still present with only one click.

The bank finds that the offer converts higher for customers who receive it as an email than for those who see it as a text message or inside the bank’s mobile app using trip analytics. They decide to send a tailored email offer to people who saw the credit card offer and subsequently give up their travel based on this information.

Utilizing Customer Journey Analytics, Locate Clients at Risk of Soft Churn

Customer journey analytics are used by a retail bank to recognize high-risk customers and comprehend customer behaviors that are indicative of soft churn.

First, the team establishes a rolling 12-month baseline of customer behavior, such as usage of mobile apps, direct deposits, bill-pay activities, and branch visits, that may be indicative of soft churn. 

A rolling 12-month baseline of consumer behavior is created by the team. Then they compare each customer’s most recent conduct with their behavior over the previous 12 months by evaluating the identical behaviors during the previous 30 days.

It should come as no surprise that each behavior is, on average, quite consistent throughout the whole consumer base. However, the consumers whose current activity has considerably decreased when compared to their prior conduct are what the bank is truly looking for.

6 insightful customer journey analytics examples and use cases

By doing this, they give employees access to these insights so that they may act quickly to stop clients from soft churning and stop significant revenue loss.

Utilize Customer Journey Analytics to Evaluate the Effect of New CX Initiatives

Using customer journey analytics, a top cable, wireless, and internet provider evaluates the performance of a new self-service appointment system designed to enhance customer experience while lowering the cost of service.

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The CX team must comprehend the reason why the existing service repair micro-journey lowers NPS. The baseline NPS of a consumer who calls the service center to arrange a repair visit is 14.7. When the service vehicle comes, some clients are not home. NPS falls to 14 for these “No Shows.”

The team concludes that making consumers call the care center to reschedule service appointments contributes to a worse experience, as measured by a decline in NPS, based on the high No Show rate.

Moreover, they estimate that in addition to a bad experience, service visits (also known as truck rolls) to customers who are not at home are losing the business $21M.

The business introduces a self-service appointment system that is used on the web, mobile devices, and set-top boxes to enhance this procedure. Customers can reschedule existing appointments through the new system, add themselves to a waitlist with automated messaging when a spot becomes available, and receive automated messages that shorten their time frame as they approach the appointment. The team evaluates the test’s effects on customer experience to calculate the investment’s return on investment and decide whether to make it available to all customers.

According to a roughly 6-point gain in NPS, they discover that consumers who use the new self-service system have a far better overall experience than those who use the present method.

Conclusion

The customer journey is a powerful metric that can provide valuable insights into how your customers interact with your brand. By understanding the customer journey, you can optimize the user experience and make sure that your customers are having a positive interaction with your brand at every touchpoint. If you want to learn more about how to use customer journey analytics to improve your business, contact SmartOSC DX today. Our team of data experts will work with you to understand your customer’s journey and help you make improvements that drive real results.




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