Customer journey refers to the customer’s experience with a brand throughout their relationship. Customer journey analytics help businesses understand and predict customer journey in order to improve their experience. In Gartner customer experience innovation survey (2019), customer journey analytics were cited as top customer analytics by 47%. Yet, it remains difficult to detect the moments customers change their mind. Process mining allows businesses to tackle this challenge by discovering and visualizing processes in the customer journey.
In this article, we provide the ways process mining improves customer journey analytics, its benefits, use cases and challenges.
Improve customer journey mapping
Customer journey map is an overall view of this journey based on the customer’s point of view. The map is generated by extracting data from any IT system that customer data is integrated into (e.g. CRM, ticket systems, application databases, log files, audit tables, excel docs). Process mining leverages the event logs of these systems to understand the points where employees and customers interact. These insights enable users to track customer journey processes, parties involved in these processes, and challenges faced within these workflows.
For example, a business wants to understand customer journey by analyzing the visits to their website. The data they use includes:
Click-throughs (where they’re clicking from to reach their website)
The customer navigation of the application process
The customer calls to the Sales department on process
Type of contacting support (Chat, phone, email and contact form)
Customer’s back-and-forth between these contact supports
Time of customer’s set up of their portal
Sticking points in given process (e.g., subsequent calls to support)
Improve marketing strategies
Process mining provides insights driven from real-time data to marketing teams which enables the team to improve their marketing strategies. For example, Melon, an online music streaming service in South Korea, leveraged process mining to analyze new users journey who signed up through a free mobile instant messaging application (KakaoTalk). The company clustered new users considering the reasons why they signed up and their behavioral patterns. Such cluster information served for establishing a targeted marketing campaign to increase conversion rate for each segments.
Enhance user experience in the website
Process mining can be useful to evaluate the user experience on a given website by detecting the most influencing pages (e.g. the pages that customers like or abandon). In a case study, researchers leverage process mining to measure how long it takes to complete purchase for customers, and understand which websites provide easy experience for the customers.
Facilitate website sign up
Many websites require signing up and logging in to allow users to benefit from their website. One example is job market sites where people look for jobs. However, users who scroll down and keep searching for job opportunities avoid entering their data. By leveraging process mining, companies can understand at which point the user decided to sign up or drop.
Analyze customer channels
Process mining provides insights on the channels (e.g. WhatsApp or calls) customers prefer the most or which channels lead to loss of customers. Also, process mining can help clarify customer journey paths that happen in multiple channels. For example, customers who purchase mortgage at banks get information from bank’s channels (e.g. customer service email or call) and online sources (e.g. social media, website). Banks can leverage process mining to analyze these multiple customer channels to compare whether the channel difference generate distinct outcomes.