Examples of customer engagement outcomes
As discussed in the business outcomes overview, several potential business outcomes can serve as the foundation for any transformation journey conversation with the business. This article focuses on a common business measure: customer engagement. Understanding the needs of customers, and the ecosystem around customers, helps you to articulate the business outcomes that are the target of a business's transformation journey.
During cloud-enabled data innovation efforts, you can assume that customers are engaged. The following functions are potentially disruptive and require a high degree of customer engagement:
- Aggregating data
- Testing theories
- Advancing insights
- Informing cultural change
Customer engagement outcomes are about meeting and exceeding customer expectations. As a baseline for customer engagements, customers assume that products and services perform and are reliable. When they're not, it's easy for an executive to understand the business value of performance and reliability outcomes. For more advanced companies, the speed of integrating learnings and observations from this process is a fundamental business outcome.
Descartes chose Microsoft Azure as its preferred platform, and successfully migrated its Descartes MacroPoint solution to Azure SQL Database to provide greater flexibility for customers, and focus internal resources on extending product value.
Cycle time
During customer-obsessed transformations such as a cloud-enabled application innovation effort, customers respond from direct engagement. They also appreciate seeing their needs met quickly by the development team. Cycle time is a Six Sigma term that refers to the duration from the start to the finish of a function. For business leaders who invest heavily in improving customer engagement, cycle time can be a strong business outcome.
Example:
A services company that provides business-to-business (B2B) services is trying to retain market share in a competitive market. Customers who have left for a competing service provider found that their overly complex technical solution interferes with their business processes, and is the primary reason for leaving. In this case, cycle time is imperative.
It currently takes 12 months for a feature to progress from request to release. If it's prioritized by the executive team, this cycle can shorten from nine to six months. The team can cut cycle time down to one month through a cloud-enabled application innovation effort, cloud-native application models, and Azure DevOps integration. This frees business and application development teams to interact more directly with customers.
Intelligent contact center
Customer satisfaction and experience are at the core of successful organizations. Freeing your employees to focus on superior customer service can strongly affect customer loyalty and retention. With the AI technology available today, many steps during a customer call can be automated, enabling the contact center agent more time to focus on delivering superior customer service.
Example:
An insurance company has implemented digital agents to respond rapidly to customer requests. These digital agents are available through the company website and mobile app, by building an Azure Bot Service solution. Extending an enhanced customer service experience to their contact center, the insurance company implemented live call transcription, sentiment analysis, and key phrase detection. These help the contact center agent with recommended next steps and form processing. This led to reduced repetition from the customer calling the contact center, and enabled the contact center agent to focus more on providing a great customer experience.
Next steps
Learn more about performance outcomes.