Prerequisites

Definitions

It is important to define, for your environment, what will be included in your Service Engagement Measures Spreadsheet. We have provided good, better, and best formulas for calculations in the spreadsheet and an extensive glossary of terms, but judgment is required in terms of what makes sense for your environment! You may start out with whatever set of data you can get your hands on. Define it, and trend it over time, but the intent should be widening your scope to more thoroughly and accurately reflect the full customer experience.

For example, what you do or do not count as a self-service engagement will depend on your business and may change over time.

Data

Recommended formulas in the Service Engagement Measures Spreadsheet include multiple data sources. While some of these things can be mined from tools directly, you may need to do some detective work to find out where they live. Some Members discovered that they needed to enable the capturing of the data first - and all Members recommend using your organization's existing data models wherever possible. Don't reinvent the wheel!

Engagements

• Self-Service: user sessions for self-service mechanisms (usually web-based)
• Community: user sessions and threads
• Assisted: cases, tickets, or service requests

Cost Per Engagement

• Self-Service: Total associated costs (may include salary, systems, overhead - based on how your company organizes their cost structure) / /number of successful self-service engagements
• Community: Total associated costs (may include salary, systems, overhead-based on how your company organizes their cost structure)/number of successful self-service engagements
• Assisted: Time spent on tasks and the volume of demand (again, based on how your company calculates cost per case)

Survey Data

• Session surveys: self-service success
• Customer Satisfaction
• Customer Effort
• Net Promoter Score (NPS)

Time

Due to data limitations, the most useful strategy is to trend against yourself. Filling out the measures spreadsheet one time will provide limited insight. Track the data over time (weekly, monthly, quarterly) against optimization efforts to assess what changes lead to meaningful positive change. We propose measuring monthly and presenting quarterly.  Year-over-year analysis can account for seasonal behavior.