How To Deepen Insight Into Customer Needs And Improve Citizen Experience

 Customer Journey Management

While best practice suggests that installing customer feedback systems can help government agencies gain better insight into citizen experience, post-service survey systems in isolation don't provide sufficient insight into the customer experience.

According to a recent article in Government Executive, customer feedback systems are limiting in that they give feedback on what customers say, and not how they behave. Which is limiting, because understanding how customers act is key to gaining in-depth knowledge of their wants and needs.

Learn how to: Reduce wait times, enhance customer experiences and improve efficiencies.

Fortunately, the ability to measure customer experience has moved beyond post-service feedback. Nowadays, customer behavior; their actions and non-actions, are measurable at every touch-point in their journey. Giving you the opportunity to analyze their behavior, identify friction points and adjust your processes to improve their experience.

 Main Street DMV Analytics

By integrating business intelligence (BI) tools, and even artificial intelligence (AI), into every step of the customer journey, you can collect journey management data, which you and your team can dissect, analyze and visualize. Deepening your agencies insight into behavioral trends, essential service metrics, and process exceptions.

Implementing BI at DMVs, Tax Collection offices and other federal agencies may seem excessive. However, the effort is worthwhile. A McKinsey customer satisfaction survey shows a direct correlation between customer journey quality and the bottom line; specifically, a 20% reduction in the cost of serving customers. Savings that could go toward improving citizen and staff experiences at your authority. 

@@There is a direct correlation between customer journey quality and the bottom line@@

AI tools take improving citizen experience a step further. Removing the need to continuously glance into the rear-view mirror, then gather, aggregate and dissect data before being able to make informed decisions. Instead, AI analyzes data and predicts outcomes based on machine learning. For example, advising branch management that at a particular time of the day, month or year, service points are overstaffed 45% of the time and that reallocating those resources will reduce bottlenecks in other parts of the agency or branch.

Do you know all there is to know about how well your agency is performing for your staff and customers? ACF can help you take a closer look.