In this blog we welcome guest blogger Maureen Fleming, a Vice President at IDC, focused on middle tier technologies that enable new initiatives.
By 2018, 71% of respondents to an IDC 2016 digital experience survey plan to increase their budget for creating and delivering digital experiences. And 82% of respondents to a survey looking at document-centric process disconnects believe they can improve their customer experience by removing the friction between back-office and front-office business processes.These surveys show an awareness and intent to invest in solutions that improve processes involving customer experiences.
These investments will significantly impact the types of solutions that can be built for customer experience design and automation as well as the need to rapidly improve decision support.
Customer Experience Design and Process Automation
Customer experience used to be the result of generally uncoordinated touchpoints that, in aggregate, left a good or bad impression with the customer. Today, businesses are increasingly designing, coordinating and automating workflows optimized for dynamic customer experiences across all touchpoints.
Because customers send and receive communications via multiple channels, including stores, phone calls, text, emails, and social networks, content is treated as a consistent and managed asset and integrated across all of the customer-oriented workflows.
By automating the customer experience, businesses are able to realize both revenue and cost impacts as they:
- Improve the standardization and efficiency of communications to one customer across touchpoints
- Manage the content assets that support the experience
- Increase the consistency in how all customers are treated
- Identify and prevent problems to avoid negative customer experiences
At IDC, we assume customer communications platforms will become a core solution used to help customers evolve to be able to send relevant messages in the appropriate format and channel based on the customer’s current situation. Customers recognize the importance of content working in tandem with process. In the regulated industries survey, 45% of respondents already integrate enterprise content management into their customer communications systems but that number will grow to 83% by 2018.
Analytics-Driven Processes Require Redesign to Support Higher Volumes of Decisions
Businesses traditionally have invested very little on end-to-end process visibility aimed at preventing problems. That is changing rapidly as predictive analytics and proactive intelligence become cornerstones of digital transformation. In fact, the top feature priorities of customer communications platforms involve the ability to manage and perform analytics on big data.
Use cases of analytics-based solutions are broad but include the shift to real-time or near-real-time offer management, cross-channel marketing or customer social relationship management. On the industrial side, IoT initiatives predict and prevent problems with machines or connected devices and deliver new types of digital services to customers.
The shift to analytics-triggered processes has an enormous impact on the workload of customer contact centers and the adequacy of self-service support. Analytics systems predict conditions that require manual follow-up or an automated response. Other than high volume, low risk transactions, the lion’s share of follow-up over the next few years will involve the initiation of a task or case assigned to a worker, who must then decide what to do next.
Initially, the volume of decision obligations may swamp existing resources. That typically requires a solution re-design to offer greater situational awareness, by integrating content and back-office applications into case management solutions aimed at speeding up processes involving decisions, while also improving the quality of decisions.
About Maureen Fleming
Maureen Fleming is a Vice President at IDC, focused on middle tier technologies that enable new initiatives, such as sensor-based computing and API monetization.
She is the lead analyst of IDC’s IoT analytics and information management practice and IDC’s research covering process automation, API management and continuous analytics.