Use Data-Driven Insights for Service
Learning Objectives
After completing this unit, you’ll be able to:
- Explain the customer effort score.
- Justify the frequency of customer surveys.
- Explain how surveys impact capacity planning.
Einstein Analytics provides a dynamic dashboard that gives us insights without logging a ticket and waiting for an IT request to be fulfilled. In this unit, you learn how Einstein provides contact centers with things like insights into your current CSAT, the number of open cases, and your average number of days to close a case.
Get Everyone on the Same Page
With Einstein Analytics, we utilize one source of truth. The same data is used across the organization so there is clarity for each and every team. For example, if we see fewer case resolutions in a day than usual, managers can determine the cause with help from Einstein. They can see at a glance if there was a technical glitch or a spike in call volume that day. Einstein Analytics help managers easily explain anomalies when they occur. Everybody's looking at the same dashboard—from front line management all the way up to our executive leadership—so everyone’s always on the same page.
Knowing how we’re doing as an organization is key to continuous improvement. By utilizing Einstein Analytics and adjusting our processes, our KPIs continue to grow year over year. We’ve been exceeding our CSAT goal for the last 48 months, so we know that using AI is helping us improve customer satisfaction.
Measure Customer Effort
We want every service interaction to be as simple and easy as possible. To find out how we’re doing, we calculate the customer effort on each case. A customer effort score is calculated using a 5-point scale that classifies interactions from “very difficult” to “very easy.” We survey customers after each case is closed to get their responses. Years ago, we sent surveys once every 30 days, then we reduced it to once every 15 days to get a more up-to-date picture. Now, we're sending out surveys on every single closed case.
Sending surveys often helps us understand what our customer's needs are every day so we’re able to continuously adjust to changing expectations. Surveys help us pinpoint specific issues so we know what we can do better. Whether the issue was related to a product, an agent, or something missing from our knowledge base, we want to be able to fix it quickly. With this approach, we've reduced our days to resolve cases by 50% over the last 4 years.
Plan for the Future
We often ask ourselves this question: 10 years from now, what does our success center look like? Thinking this way helps guide our plans for future growth. We're always looking for new ways to leverage advances in technology and our own tools to shape our processes and become smarter and more predictive. Doing this helps us reduce customer effort and increase customer satisfaction, without big increases in staff. Currently, case volume is around 25% of our customer growth while headcount growth is trending relatively flat.
Conclusion
Every organization has struggles and challenges. At Salesforce, data analytics helps us learn from those challenges and our tools help us solve them. However, data and tools are only part of the big picture. People are still the most important component. In the next unit, you learn how we train agents and retain agents in our success center.