In general, it makes economic sense for companies to pursue an SRM strategy, since in the all-too-common scenario of using disparate KM, CRM, and search applications, despite all of the resources at hand, the customer is hardly ever provided with any resolution, except to take a look at the competitive offering (in disgust). Conversely, the scenarios in which an SRM approach is taken should enable the contact center agent to satisfy the customer's needs and increase the economic value of that customer to the organization.
By using advanced KM technologies, users can create a cross-channel approach to help automate service resolution in the enterprise, so that all of the valuable information in all of those disparate systems is tied together in one common knowledge platform, which is then made available to the agents, customers, and the enterprise. Indeed, it should not matter if a customer query comes in at the call center or at the help desk, or via e-mail, phone, or the web site, since the correct answer to the query should be accurate and consistent across all channels, and it should reflect the outcome that the selling company desires.
However, while the potential for self-service and SRM to reduce costs and improve service quality is indisputable, it is an extremely complex model to deliver, since self-service capabilities usually require multiple layers of technology across each service channel. Companies do best when implementing it in a step-wise fashion, starting with something as simple as providing answers to FAQs, and moving up to allowing customers to execute complex transactions (like changing preferences for a service) on their own.
Standardizing on a set of packaged CRM applications helps when integrating self-service and SRM across channels. Yet most companies will still need to buy best-of-breed "e-service" products to provide live chat, e-mail response management, customer search, and other key features needed for self-service over the Web. User companies must be prepared to make a reasonable investment in their transaction architecture in order to facilitate self-service and to handle the higher volume of interactions with customers.
Companies must also identify the metrics they will need to measure their self-service efforts. Though a service center is still largely viewed as a cost center, many traditional metrics are not appropriate any longer. A multitude of factors can impact a call center's key performance indicators (KPIs), and this is before any attempt is made to implement and deploy the multichannel call center agent concept.
Therefore, KPIs, such as average wait-time, first call closure rates, cost per call, and average call duration, must be closely monitored as the program is rolled out. These should all drop as the call center agents begin to successfully and uniformly manage multiple channels. For Internet-based systems, the proper KPI might be the number of transactions completed without a customer having to pick up the phone, while for an IVR system, it could be the number of customer calls completed without human assistance.
Ultimately, companies need to know if customers have found what they needed and if they have gone away happy. But answering these simple questions can often mean wading through a disparate mix of click stream data, e-service usage logs, CRM analytics, analytic reporting, and more.
Well-designed applications that are consistent with other self-service channels and that are integrated with assisted-service channels as required, such as the telephone or a live chat feature, are critical, not only for self-service adoption, but also for overall customer satisfaction marks. Self-service fails when it tries to anticipate as many calls as possible but ends up delivering hundreds of nuanced responses to the customer, none of which is quite right.
By using advanced KM technologies, users can create a cross-channel approach to help automate service resolution in the enterprise, so that all of the valuable information in all of those disparate systems is tied together in one common knowledge platform, which is then made available to the agents, customers, and the enterprise. Indeed, it should not matter if a customer query comes in at the call center or at the help desk, or via e-mail, phone, or the web site, since the correct answer to the query should be accurate and consistent across all channels, and it should reflect the outcome that the selling company desires.
However, while the potential for self-service and SRM to reduce costs and improve service quality is indisputable, it is an extremely complex model to deliver, since self-service capabilities usually require multiple layers of technology across each service channel. Companies do best when implementing it in a step-wise fashion, starting with something as simple as providing answers to FAQs, and moving up to allowing customers to execute complex transactions (like changing preferences for a service) on their own.
Standardizing on a set of packaged CRM applications helps when integrating self-service and SRM across channels. Yet most companies will still need to buy best-of-breed "e-service" products to provide live chat, e-mail response management, customer search, and other key features needed for self-service over the Web. User companies must be prepared to make a reasonable investment in their transaction architecture in order to facilitate self-service and to handle the higher volume of interactions with customers.
Companies must also identify the metrics they will need to measure their self-service efforts. Though a service center is still largely viewed as a cost center, many traditional metrics are not appropriate any longer. A multitude of factors can impact a call center's key performance indicators (KPIs), and this is before any attempt is made to implement and deploy the multichannel call center agent concept.
Therefore, KPIs, such as average wait-time, first call closure rates, cost per call, and average call duration, must be closely monitored as the program is rolled out. These should all drop as the call center agents begin to successfully and uniformly manage multiple channels. For Internet-based systems, the proper KPI might be the number of transactions completed without a customer having to pick up the phone, while for an IVR system, it could be the number of customer calls completed without human assistance.
Ultimately, companies need to know if customers have found what they needed and if they have gone away happy. But answering these simple questions can often mean wading through a disparate mix of click stream data, e-service usage logs, CRM analytics, analytic reporting, and more.
Well-designed applications that are consistent with other self-service channels and that are integrated with assisted-service channels as required, such as the telephone or a live chat feature, are critical, not only for self-service adoption, but also for overall customer satisfaction marks. Self-service fails when it tries to anticipate as many calls as possible but ends up delivering hundreds of nuanced responses to the customer, none of which is quite right.
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