Research Pain Points and Prioritize Your Goals
- Prioritize opportunities to improve your customers’ experiences.
- Engage specialists who can help reveal customer pain points.
- Explain how task automation and system integration can improve customer and customer-facing employee experiences.
Drive Your Data Architecture Using a Customer Journey
In the previous unit, our technical architect at Northern Trail Outfitters (NTO), Pia Larson, learned the value of mapping a customer journey. Specifically, she learned how it can give her a comprehensive story of the customer experience with the NTO brand.
With help from key stakeholders, Pia mapped a certain customer’s experience to better understand the obstacles that all NTO customers can encounter. Pia can use those obstacles to drive her data strategy. Now, she wants to figure out where in the journey—which obstacles—to turn her attention to first.
Start at the Beginning of the Journey, Right?
One of the great things about using a customer journey to plan your data architecture is that you can start anywhere you want. Again, let’s look at the journey that Pia and her stakeholders created.
Pia knows that her architecture strategy doesn't have to start at the beginning of the customer journey. Instead, she and her stakeholders Felix, Ruthanne, and E.J. can evaluate and prioritize the opportunities for improvement.
After a good discussion, they decide to prioritize the call center. Customer feedback and satisfaction on the NTO call center is lower than at other touchpoints in the journey, and call times are higher than industry norms. Pia and Co. figure that making improvements to call center efficiency can be a big win for NTO and its customers.
Use Research to Guide You
Now that they've determined the project's focus, Pia and her stakeholders do some research, but not research in terms of technical implementation needs. Being customer-centric, they start by evaluating the current experience in the call center. So they observe and interview service agents to:
- Understand the case resolution process.
- Identify inefficiencies in task completion.
- Document data and infrastructure gaps.
Service agents help Pia and her stakeholders understand the most common service scenarios and resolution processes. They even talk about some of their more difficult calls and the ways in which they struggle to find data and deal with their technology while on a call.
During their research, the team observes agents doing several repetitive tasks, especially when searching for customer and order information. Agents swivel back and forth between their case management system and their ecommerce system to find customer records, access the data they need for answering customer questions, and resolve customer issues.
After observing the call center experience, Pia and her team dig deeper into the data side of things. She works with IT to conduct an audit of the data and customer profiles in their service system.
Pia’s research uncovers challenges that all add to the average call time, which directly impacts service queue wait times. We can see why Carla experienced the long wait time!
She’d like to start on these challenges, because resolving them can make a big impact quickly.
- Record duplication
- Context-switching between applications
- Data quality inconsistencies across the NTO ecommerce and service center systems
Pia’s research and the service agents’ feedback provide a holistic view of NTO’s business and customer service problems. Armed with this concrete information, Pia’s confident that she’s on the right path to solving these problems through NTO’s architecture. Now Pia can assess NTO’s data and automate some of the service agents’ repetitive tasks to reduce call wait times.
Puttin’ It All Together
As we’ve seen, starting with the customer experience helps an organization take a holistic approach to IT projects. You can create and use the customer journey to help identify problems that require IT solutions and then prioritize them.
Conducting research helps the team understand the why behind the what. For example:
- Why are call times long?
- How do data quality gaps impact customers and employees?
Knowing the answers to these questions helps you strategize when deciding how to approach your project.
Being customer-centric in your planning is a great way to identify areas of improvement for your data architecture. That way, you prioritize big wins for your customers. You also reduce the likelihood of wasting your efforts on things that don’t improve the relationship between your company and your customers.