9 min read There’s no dearth of options in the market today, and companies providing the best customer service will undoubtedly win.
As businesses race to meet rising customer expectations, CIOs are turning to advanced technologies that can add value to processes, for example, streamlining operations and enhancing service delivery.
One technology making waves across the IT industry is process mining, particularly when combined with artificial intelligence (AI). And, its application in customer service is very fascinating.
This powerful duo helps organizations gain deeper visibility into workflows, uncover inefficiencies, and optimize customer touchpoints for better outcomes.
In this blog, we will dive into process mining from a customer service lens and how AI can double the potential and benefits of the technology.
Table of Contents
What is process mining?
Businesses looking to understand the effectiveness of their operations can leverage the data-driven technique called process mining to assess how well their systems are functioning or otherwise.
Companies have a set of expectations and goals while setting operational processes. But the reality is quite different and there’s only so much that analytics can tell them – what’s going wrong. Data mining can help them understand where and why things are going wrong.
Data mining extracts and analyzes event logs such as CRM, ERP, or help desk software to provide a visual representation of business processes as they occur.
Companies can compare what they expect from the processes with the processes put into practice to find inefficiencies and potential areas of optimization.
Why process mining matter in customer service?
According to a recent study by EY, enterprises embracing process mining for end-to-end continuous improvement are projected to be 20% more profitable compared to their counterparts.
Process mining allows CIOs to keep track of their customer service operational systems in real time and check if the systems are actually functioning in the manner they were designed, configured, and intended to.
CIOs can get data insights on the bottlenecks facing their teams and the inefficiencies in customer service workflows, like long customer wait times between calls, manual entry-borne data errors, misrouted calls, and so on.
Furthermore, data mining can pick from traces of deviations from standard procedures, like agents skipping a verification step in financial transactions, unapproved discounts used by the sales team, agents bypassing a critical approval stage, and more.
Other ways in which data mining can help customer service are improving compliance and regulatory aspects like monitoring and adhering to necessary protocols, and suggesting the deployment of tools like chatbots to reduce response times and improve first-call resolution rates
The role of AI in enhancing process mining
Here are the 5 most important roles of AI in process mining, among many other areas:
1. Advanced pattern recognition
AI algorithms are pro at recognizing complex patterns even in large datasets. AI can apply its capability in process mining and help identify hidden inefficiencies, bottlenecks, or deviations from standard workflows that humans or traditional tools might overlook.
For example, AI can detect that certain approval steps consistently cause delays in a procurement process and suggest ways to streamline them.
2. Predictive analytics
With the help of historical data, AI models can forecast potential outcomes like delays, compliance breaches, or resource constraints. This predictive capability, coupled with data mining, allows businesses to intervene proactively before problems escalate.
For instance, in supply chain management, AI can predict delivery delays based on past performance, weather data, or current logistics bottlenecks, and flag them for future evaluation or suggest a solution.
3. Automated process discovery
Process discovery that’s spearheaded by AI can automate the mapping of business workflows by analyzing event logs and system data. This eliminates the need for manual mapping and speeds up the identification of inefficiencies or deviations.
Large organizations with complex, undocumented, or rapidly changing processes benefit the most from an automated process discovery system, and AI can drive it ahead with data mining.
4. Intelligent automation (hyperautomation)
AI enhances Robotic Process Automation (RPA) by identifying repetitive tasks that can be automated and continuously optimizing them.
For example, AI can monitor finance workflows and suggest automating invoice approvals or payment processing, which does not just improve efficiency, but also reduces human errors and frees up staff for more strategic tasks.
5. Anomaly detection & root cause analysis
AI process mining can detect anomalies and flag any suspected deviations from standard processes like unusual transaction times, skipped steps, or unauthorized changes.
Beyond just flagging issues, AI can also analyze event logs to pinpoint the root cause of these anomalies, which enables businesses to take corrective steps according to the underlying problems instead of just treating symptoms.
Steps for CIOs to get started with AI-powered process mining
CIOs need a strategic approach to deploy AI-powered process mining into business operations and make the most of this technology. These steps can help you get started:
Step 1 – Define clear objectives
Clearly define your objective of using this technology and pin down specific, measurable goals that align with your organization’s broader strategy.
Even if your focus is on reducing costs, improving customer satisfaction, enhancing compliance, or ramping up response times, clear objectives help guide the implementation process and measure success effectively.
Step 2 – Select the right tools
Now you need to find the tools that best complement your defined objectives. Choose process mining and AI platforms that integrate smoothly with your existing technology stack.
Some of the key features you would want to check are real-time analytics, customizable dashboards, and automation capabilities that maximize efficiency and ensure minimal disruption during integration.
Step 3 – Ensure data quality
Clean, consistent, and accurate data is critical for effective process mining. Standardize data from various sources, remove duplicates, and ensure consistency across systems so that AI models can generate reliable insights and identify inefficiencies accurately.
Step 4 – Start small, scale fast
Launch pilot projects in specific areas or workflows to test the technology’s effectiveness and demonstrate value early on. Once the pilot is successful, scale the solution across the department for broader impact.
Step 5 – Monitor and optimize
Continuously track key performance indicators (KPIs) and use real-time insights to refine workflows. Regularly adjust and optimize processes to ensure continued improvements, and keep adapting the strategy with any changes in business needs.
How process mining can optimize customer service?
Here’s how you can optimize your customer service function with process mining for the best results:
Identifying bottlenecks and delays
You can read through all your customer service processes with process mining to identify bottlenecks like long call wait times, slow ticket resolution, or delays in transferring issues to the appropriate department.
The technology takes it a step ahead to lay down where exactly the gaps in the process exist, practically, and break it down for you to redesign workflows that accelerate service delivery.
Streamlining issue resolution
You can also improve your first-contact resolution rates with AI process mining. Process mining can reveal patterns and explain why multiple interactions are required to solve a single problem.
It can flag where the problem exists, like agent incapability, weak knowledge bases, or broken escalation processes, giving you everything needed to solve the problem.
Ensuring compliance and consistency
Some industries demand adherence to standardized processes like financial organization and process mining can help with the degree of adherence.
Be it customer service agents skipping a mandatory verification step, or an outdated security system that falls short in updated regulations, AI process mining can automatically flag deviations, helping businesses stay compliant and consistent across all customer interactions.
Optimizing workflows with data-driven insights
Once bottlenecks and inefficiencies are identified, businesses can optimize workflows through automation, intelligent routing, or process reengineering.
For example, smart routing systems can direct customers to the most suitable agent based on their issue type and the agent’s expertise, reducing response time and increasing the likelihood of first-contact resolution.
Enhancing training and support for agents
Process mining doesn’t just optimize systems, it also improves the performance of customer service teams.
By analyzing patterns of inefficiency or error, businesses can develop targeted training programs that address the underlying weaknesses. This ensures that every agent is equipped to handle customer inquiries effectively and consistently.
Standardizing customer service processes
Process mining helps organizations establish clear, standardized workflows that every agent can follow, regardless of experience or location. This consistency ensures customers receive the same level of service across all channels, boosting satisfaction and brand loyalty.
Driving continuous improvement
The benefits of process mining don’t stop after initial optimization. Process mining can continuously monitor customer service operations over time.
It continues to provide insights on new bottlenecks, and shifts in customer expectations and helps companies be up to date with the customer and market demand.
Conclusion
AI-powered process mining is the perfect aid for CIOs looking to level up and optimize customer service operations.
This technology, with its vast set of applications and benefits, helps businesses eliminate bottlenecks, streamline workflows, and ensure consistent, high-quality interactions.
Companies can leverage their data-driven insights to enhance customer satisfaction, improve efficiency, and stay ahead of the competition, and Auralis AI can help you take the lead with its advanced process mining capabilities. Book a demo of Auralis AI today.
