Using Analytics to Improve Your Interactions with Customers

Transcription

1 Consulting Using Analytics to Improve Your Interactions with Customers By Mike McGuirk, Consulting Services

2 Using Analytics to Improve Your Interactions with Customers The use of customer analytics across all facets of the business enterprise has begun, and companies are realizing new ways to cut costs and improve relationships with their customers. The success that analytic solutions have provided for sales and marketing functions has caused forward-thinking executives to search for opportunities to leverage customer analytics in other parts of the organization. They think that data and analytics can be leveraged by providing insights to employees in other departments such as: human capital, customer support and product development. They re right. Also fueling the momentum to identify new innovative ways to integrate customer analytics is the heightened emphasis on improving and personalizing the customer experience. The reality is that customers now expect companies to create shopping, purchase and customer support experiences that cater to their individual needs. Customer analytics is often underleveraged in the customer support functions of businesses and therefore represents significant untapped potential for companies. This paper focuses on the use of analytics to help reduce operational costs while improving the customer service and product support interactions you have with your customers. These same principles apply with the delivery of customer support. Not all customers have the same service and support needs. Customers will call for different reasons and require different levels of support, and customer analytics can help companies become better prepared to quickly and accurately address customers unique support needs. In addition, companies that can fully leverage the benefits of technology-enabled analytics will be more successful turning customer support moments-of-truth into brand- and loyalty-building experiences. Successful integration of customer analytics inside an organization is largely dependent on certain factors: Commitment from leadership to adopt a customercentric approach to managing their business units Development of an operational environment that can support large scale data collection, data mining and analytically-driven differentiated customer treatments Incorporating best practices in customer data collection and analytics Customer support operational systems that are capable of acting on real-time insights and decisionmaking rules Differentiated Customer Support Not all customers are the same. If you believe this axiom, then it is easy to understand why marketers have been using customer analytics for years to tailor value propositions and product offers to the unique preferences and needs of different customer segments. The results of this analytically-driven marketing approach have been improved brand and product relevance and significantly better return on marketing expenditures. 2

3 Figure 1 Key Elements of a Customer-Centric Support Operation Data Integration Analytics Integration Differentiated Treatments Data management systems that provide a comprehensive view of the customer (e.g., contact history, account details, customer value, needs and preferences, demographics). Analytic tools and techniques capable of real-time, continuous learning from both structured and unstructured voice of the customer interaction data. Integrated orchestration tools that utilize real-time analytic results and seamlessly deliver highly differentiated, personalized customer support treatments. Figure 1 illustrates several key operational components that enable a customer-focused, analytically-driven customer support environment. Data Integration It all starts with robust data collection. Far too often customer support systems focus almost entirely on collecting information about the reason for the customer inquiry or contact. Although this is extremely important, the data management systems also need to capture, and make easily accessible, critical information about the customer. The combined call reason and customer profile data can be quickly analyzed and delivered to execute customer support treatments that are tailored to the unique characteristics and needs of each customer. Analytics Integration Today, customer support analytics is often performed in an episodic, off-line manner with the goal of identifying process improvements. Analytics has the potential to play a far bigger role. With the right data management strategy and enabling technology in place, analytics becomes an in-line function; supporting continuous learning and informing real-time decisions that can drive superior customer experiences. Differentiated Treatments Once the right data management and analytic tools are in place, it is incumbent upon customer care leadership to utilize the customerlevel insights to develop tailored, impactful service experiences. This will require a mindset shift from process improvements aimed at the masses to process improvements specifically developed for targeted segments of your customer base. Also, as is the case in top performing marketing units, success will require a commitment to a rigorous test and learn mentality, seeking to improve customer service experiences each and every day. 3

4 Putting the Customer Insights to Work There are many opportunities to incorporate analytics for reducing your costs and improving the service experience for your customers. Figure 2 illustrates four distinct areas where customer analytics can be applied. When effectively implemented, these applications of analytics can have a profound impact on both operational (e.g., first call resolution, average handle time, etc.) and customer relationship building (e.g., customer satisfaction, brand loyalty, etc.) business objectives. 1. Proactive Customer Education Use analytics to target product education communications. 2. Intelligent Inbound Contact Routing Select best agent based on real-time analysis of customer profile and call reason Figure 2 Multiple Opportunities to Leverage Customer Support Analytics 4. Personalized Outbound Support Utilize analytics to trigger impactful customer care follow-up communications. Customer-centric analytics can inform the development of personalized customer care interactions 3. Intelligent Agent Enabler Provide agent with actionable insights about customers historical and predicted support needs. 1. Proactive Customer Education By studying the interactions that different types of customers have at different points in their lifecycle, we can accurately predict customer support needs and deliver proactive, targeted communications that improve both your customer service experiences as well as your company s operational effectiveness. Through the use of analytics, these proactive communications can be further fine-tuned to be delivered at the right time and through your customers channel of preference. 2. Intelligent Inbound Contact Routing Analytics are now being used to help match the inbound caller with the right customer support agent. Traditionally, call routing has been driven by agent availability and matching call reasons with agent skills. Analytics has the ability to play a much bigger role in call routing. By capturing and leveraging additional information about the caller such as: age, gender, ethnicity, prior contact history and self-reported or predicted interaction preferences, we can do a much better job pairing callers with the best agent. Intelligent, analytics-assisted routing helps create better customer experiences and more productive outcomes. 3. Intelligent Agent Enabler One of the top goals of customer support organizations is the resolution of customer issues on the first contact first call resolution (FCR). Organizations that can successfully and consistently do this have dramatically lower operating 4

5 costs and significantly higher customer satisfaction scores. Real-time predictive analytics can be used to drive higher FCR rates. By quickly gathering analytically-driven insight about the customer and the reason for the call, information can be retrieved and delivered to the agents desktop to help them more completely resolve customers issues, thus reducing the number of repeat calls. In addition, the customer interaction data can be mined to predict other reported issues and questions that are often associated with the primary reason for the customer contact. The result can be a rank-ordered list of related issues and topics that can be displayed on the desktop and used by the agent to further educate the customer and reduce the likelihood of repeat calls in the near future. 4. Personalized Outbound Support Marketers have been relying on the use of automated, analytically-triggered outbound communications for over two decades. These practices have been proven to significantly increase marketing effectiveness and produce exceptional return on investments. Similar types of outbound, analytically-driven communications can also produce powerful results in customer support organizations. Analytic models can be developed to comprehend the interaction data, predict customer behaviors and trigger targeted outbound treatments. For example, in cases where customers do not complete post-interaction satisfaction surveys, a model can be developed to predict each customer s net promoter scores (NPS). Customers predicted to have low NPS scores (i.e., detractors) can be sent offers or service treatments aimed at building goodwill. In addition, speech analytics can be performed on call recordings to identify top reasons for negative customer sentiment so that remedial actions can be deployed. Summary Customer analytics has been widely adopted by marketing professionals for many years and has become a crucial component of customer relationship marketing practices. As business executives become increasingly focused on differentiating their brands by improving the experiences their customers have across all sales and non-sales touchpoints, customer analytics will be more heavily relied upon across a broader cross-section of the business. Customer support is one of the business functions that has a tremendous amount to gain by exploring new innovative ways to integrate customer analytics. The integration of analytics in customer support operations will require data management systems and technology platforms that enable real-time analysis of structured and unstructured customer interaction data. The resulting analytics will make it possible to develop and deliver game-changing, personalized service treatments that significantly improve the customer experience and help to reduce service costs. Customer support is a complex, multi-faceted process and analytics can be applied in many different areas of this process to improve the interactions you have with your customers. Analytics is the engine that can deliver more targeted customer support communications, execute more intelligent call routing and provide invaluable insights and issue resolution recommendations to the agent. The end-result of deeper analytic integration is more efficient processing of customer support incidents, better equipped agents and more satisfied customers. That is a win for the business, a win for the employees and most importantly, a win for your customers. 5

6 About TeleTech: TeleTech, founded in 1982, is a leading global provider of analytics-driven, technology-enabled services that puts customer engagement at the core of business success. The Company offers an integrated platform that combines analytics, strategy, process, systems integration, technology and operations to simplify the delivery of the customer experience for Global 1000 clients and their customers. This holistic multichannel approach improves customer satisfaction, increases customer loyalty and drives long-term profitability and growth. From strategic consulting to operational execution, TeleTech s over 40,000 employees speaking over 50 languages deliver results for clients in the automotive, communications and media, financial services, government, healthcare, technology, transportation and retail industries. Contact TeleTech: TELETECH (outside the U.S.) teletech.com /14