How to Achieve Best in Class CRM for Customer Service

Customer Service CRM Optimization

Highlights

  • The right use of technology is less about software features and functions and more about how the application will facilitate customer service strategies and objectives.
  • Basic Call Center CRM software is used where the support organization is a cost center and goals are based primarily on cost and efficiency. This level of technology may be sufficient for small, simple and reactive customer support processes.
  • Advanced Contact Center CRM software expands the use of technology to achieve more significant business impact. Evolving to this level requires technology to support more strategic objectives such as the shift from cost center to profit center, call center to contact center, and product-centric to customer-centric focus. Advanced technology is needed if the company is to deliver a performance advantage.
  • Best in Class Contact Center CRM performance is needed to deliver differentiation and competitive advantage. These support centers are social, proactive and proficient at converting their budgets into company profits. Their business impact is measured by increases to customer purchases, customer share, customer lifetime value and customer retention. They align their goals with company priorities and adopt customer strategies such as Customer Experience Management. These operators achieve the highest customer satisfaction scores and lowest cost to serve.
Johnny Grow Revenue Growth Consulting

Customer Service CRM Optimization

Customer Relationship Management software is the customer system of record and the central location for customer information. It manages demand generation (marketing), customer acquisition (sales) and customer service (support) in an integrated and holistic application.

Call center CRM software, often called customer support or a service cloud, is the portion of the application stack used to engage customers, solve their problems and deliver rewarding customer experiences.

While the customer support application should be integrated with marketing and sales to support the end to end customer journey, there are many things that make the service component unique. For example, compared to other user roles such as marketers or salespeople, agents create far more records (i.e., cases) and incur more data entry.

That means ease of use, streamlined processes, auto populated forms and the user experience heavily impact staff productivity and support costs. Contact centers also incur higher staff turnover which increases onboarding and system training, and further bolsters the case for an easy to use application.

Agents also navigate among more fragmented systems than their marketing and sales counterparts. That means an underlying customer support platform or system integration are essential to avoid manual rekeying, duplicate data and data siloes.

Differences in goals and challenges require varying levels of contact center CRM technology. Here's how they are generally depicted in ascending order.

Customer Service CRM Performance Levels
Customer Service CRM Optimization
1

Basic Technology for Customer Service

Basic call center software is used where the helpdesk or support organization is a cost center, customer support processes are simple and company goals are based primarily on cost and efficiency.

Customer support is reactive, so when a customer calls in with a problem, agents need immediate access to customer information and an automated process that leads to quick resolution. Delays, missing information or forced transfers lower customer satisfaction and increase service cost.

Fortunately, call center CRM systems display account information such as authorized contacts, customer support privileges such as entitlements or Service Level Agreements (SLA) and customer history, including case, activity and transaction (product purchases, warranty renewals, payments) history.

Basic features and capabilities include the following:

  • A basic out of the box (OOB) application user interface (UI).
  • Call routing is generally based on simple IVR menus and includes Computer Telephony Integration (CTI) that delivers inbound screen pops to show much but not all of the 360-degree customer view.
  • Case management process automation to support the steps (receive, route, resolve, review) to solve customer issues or problems.
  • Basic agent scripts for screening, qualification or diagnosis.
  • A knowledgebase of articles that describes how to resolve different issues.
  • If the call center also performs sales, the system will include an integrated sales order entry app with some additional features such as static (unintelligent or non-contextual) up-sell and cross-sale recommendations.
  • At this level, business intelligence is limited to OOB dashboards and standard reports. Reports are limited to historical, descriptive and some but not much diagnostic reporting.
  • Performance metrics are limited to the most common activity measures, such as Average Handle Time (AHT), Speed of Answer (SoA), First Call Resolution (FCR) and Customer Effort Score (CES). Customer Satisfaction (CSAT) is measured with surveys to assess call quality or follow-up with shortcomings, but the process is only semi-automated, and the data doesn't easily roll up for aggregate analysis and trends.

This level of basic application performance should not necessarily be thought of as weak or incomplete as it may be enough for helpdesks with low volumes and simple processes.

2

Advanced Technology for Customer Service

Getting to the next level is not just a technology shift. It's more of a service evolution or transformation to achieve a strategic advantage, build on new or improved services and methods, and needs advanced technology to enable those capabilities.

At this level, the contact center delivers a performance advantage, but not true differentiation.

Customer support has shifted from a cost center to a profit center so the company goal for this organization has shifted from cost minimalization to revenue maximization.

The operation has also evolved from a call center to a contact center whereby agents support several communication channels and customers have access to highly efficient self-service tools such as virtual agents, chatbots and online knowledgebases. However, challenges such as delivering consistent service in each channel and maintaining conversation fidelity as customers change channels midstream still pose problems.

At this level, support organizations are customer-centric and have redefined their work from doing things right to doing the right things. They have a clear-eyed recognition that if processes do not create value that customers care about or are willing to pay for, they are not worth doing. Their processes are refined and optimized, but they never stop improving.

At this level, CRM optimization includes the following:

  • The application UI evolves to deliver a more rewarding user experience (UX) built on social technologies and based on user-centered design. The UX lowers training time and improves agent productivity.
  • Call routing places incoming calls and digital inquiries into queues and forwards them to customer support representatives (CSR) based on rules-based decision engines or algorithms that define the best path and CSR to resolve the inquiries. The CTI delivers screen pops that show a complete 360-degree customer view.
  • At this level business process automation is more pervasive. There are more defined workflow processes, such as automated case escalation rules for high priority cases, VIP customers or SLAs at risk.
  • There is an increase in agent collaboration using tools such as enterprise social networks (i.e., Salesforce Chatter or Slack, or Microsoft Teams).
  • Agent scripts evolve from static to dynamic and include more flexible decision trees, conditional logic and if/then/else statements. Scripts also link to informational support such as online tips, knowledgebase articles or an agent playbook.
  • Omnichannel evolves to optimize channels that offer case concurrency such as webchat and social support, so unlike voice calls, agents can handle multiple cases at the same time.
  • Artificial Intelligence (AI) is used to improve agent productivity and case resolution response. The most typical example is AI that delivers guided support with agent-assisted next steps and contextual recommendations.
  • If CSRs also performs sales, AI technology will deliver intelligent next-best-offers as well as up-sell, cross-sale and bundle recommendations. The system will calculate sales conversion rates, revenue per call, upsell and cross-sale rates.
  • Performance metrics advance from agent-based activities to more meaningful customer measures such as CSAT, NPS and CES. Some will go further and track customer insights and customer sentiment. These customer measures are analyzed by customer segment and other dimensions.
  • Role-based dashboards focus on the most essential key performance indicators (KPI) and prioritize KPIs based on importance or timing. They are supplemented with benchmarks for industry context and permit data manipulation such as What-If analysis.
  • Business intelligence advances to include predictive analytics. Information reporting changes from hindsight to foresight and shows the financial impact of both action and inaction.

Compared to the prior level, support organizations with this level of advanced technology achieve on average 8-12 percent higher CSAT scores and 10-12 percent lower contact center cost to serve.

Contact Centers with optimized CRM software achieve on average 8-12 percent higher CSAT scores and 10-12 percent lower cost to serve.

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3

Best-in-Class Customer Service CRM Performance

Customer service CRM optimization now delivers differentiation and competitive advantage. This often occurs when the company adopts a customer strategy such as Customer Experience Management (CXM). With this type of strategy, the mission shifts from customer support to the delivery of differentiated customer experiences.

Contact centers at this level are profit centers and adept at converting their budgets into company profits. They align their goals with company priorities, are in a constant state of improvement, and regularly create innovative customer services.

They are recognized by their customer advocacy, customer loyalty and increasing revenue contribution. Their ability to not just predict, but prevent customer churn, results in the highest customer retention rates, furthering bolstering increased annual revenues.

They are social, proactive and deliver a unified omnichannel customer experience in the customers preferred channels and devices. They have achieved Best-in-Class customer service performance as the result of a planned evolution.

Capabilities at this level include the following:

  • The agent experience is a top goal so the UX shifts from a generic OOB appearance to a tailored design that better supports the customer journey and the three top agent goals of increased staff productivity, performance and personal objectives.
  • Call routing advances from forwarding callers to agents based on sequence or availability to using more advanced call routing methods such as priority-based, skills-based, account-based or round robin. It's almost always a combination of a few methods that get the right caller to the right agent more quickly and accurately, reduce abandonment rate, transfers and AHT, and improve customer satisfaction.
  • CTI screen pops automatically populate customer data in context, so agents spend less time collecting and entering data and more time engaging the customer.
  • Workflow is created by business analysts and power users (not programmers) and is maximized so that everything that gets repeated gets automated.
  • Tools such as speech and text analytics are used to increase call review coverage and thereby improve quality of service.
  • The application now delivers case answers and prescriptive AI recommendations with confidence levels. It's capable of delivering the best answer when there is no right answer due to incomplete information or competing answers.
  • Self-service channels are optimized and absorbing the bulk of repetitive inquiries.
  • Omnichannel achieves conversation fidelity when customers switch channels. Agents routinely use more advanced tools such as video and co-browse support.
  • Performance metrics advance from agent and customer measures to business outcomes such as customer purchases, customer share, customer lifetime value, customer referrals and customer retention.
  • There is a defined and working data transformation process to convert and use customer data to deliver differentiated customer experiences. Data has become the support organizations most valuable asset.
  • Artificial intelligence built into the application platform is used to deliver proactive customer support that predicts or identifies customer challenges and implements steps to resolve them before the customer recognizes or raises the challenges.
  • If CSRs perform sales, the CTI includes queued lists, one click dials or automated predictive dialing for outbound campaigns.
  • Performance metrics now include what's most important to the company. That means visibility and predictability to revenue, profit and ROI.
  • Business Intelligence is now mostly exception-based and uses tools such as an early warning system and notification alerts for variances. It refines predictive analytics and steps up to prescriptive reporting. It can now advance from delivering bad news after it occurs, to delivering the foresight that prevents bad news.

At this level, the support organization is essential to the company's financial health and business growth. The company could not achieve its revenue or business growth objectives without the contact center's direct contribution.

Customer service optimized CRM software achieves what can mistakenly seem like opposing goals of delivering the highest customer satisfaction and the lowest cost to serve. That's because when technology delivers relevant, personalized and contextual information and automates end to end processes, agents spend less time entering data and more time solving for customers.