Technology-Enabled Analytics: The Key to Improving Operational Effectiveness and Customer Experience in Today s Contact Center

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1 Technology-Enabled Analytics: The Key to Improving Operational Effectiveness and Customer Experience in Niren Sirohi, Ph.D. Vice President, Predictive Analytics

2 PAGE 2 Have you ever felt that you are usually quite upset when you pick up the phone to call customer service because you have tried everything else to solve your issue but in vain? Have you ever tried to find an empty check-in kiosk at the airport even when there is no line at the check-in counter? If your answer to these questions was a resounding YES, you are not alone. Today customers have multiple options available to interact with a company beyond a voice call and IVR, online self-service, chat, click to call, online forums, mobile apps, and social media, to name a few. Channel usage rates for customer service in the past 3 years 1 have been quickly changing there has been a 12% rise in web self-service usage, a 24% rise in chat usage, and a 25% increase in community usage. Also, prior research 2 has found that companies tend to mistakenly think that their customers value live service more than twice as much as they value self-service. In fact, the same research shows that customers today are statistically indifferent about this and value selfservice just as much as live service, and this holds true irrespective of age, issue type, urgency, and demographic. The reality is that today by the time a customer picks up the phone to call customer service they are quite upset. A staggering 57% of inbound calls come from customers who first attempted to resolve their issue on the website and over 30% of callers are on the website at the same time they are talking to a rep on the phone. 2 As the number of interaction channels have exploded, it has become even harder to maintain a consistent customer experience across interaction touch-points. Only 15 percent of CIO s say their companies do very well in maintaining a consistent user experience across all communication channels. 3 Since most interaction channels are siloed in today s contact center, and channels do not share information with each other, most customer experience breakdowns occur at the boundaries between interaction channels. How many times do you have to repeatedly provide the same information about yourself and your issue not only across interaction channels but also when transferred from one touch-point to another within the same channel? Not only do customers switch brands when faced with a poor customer experience (62% of US consumers have switched brands in the past year due to poor customer service and one in four cite being shuffled from rep to rep with no issue resolution as their top reason for switching brands 4 ). In today s socially interconnected world, customers broadcast their bad experiences, leading to negative word-of-mouth. Combine the above challenges with the fact that today s contact centers are cost centers with high demands. They are expected to do more with what they have and are expected to perform miracles by increasing productivity, lowering costs, and improving customer service levels. This combination creates an insurmountable challenge in the contact center suite. In today s complex and challenging contact center world which is seemingly rife with contradictions, we believe that a few key principles driven by technology enabled analytics should guide organizational decision making: All Interactions Are Information Rich: Every customer contact, even for the most mundane reasons, is a

3 PAGE 3 very valuable source of information about your business and operations. Most contact centers desire deflection of such contacts to low cost channels or self-service and do not necessarily pay attention to root causes. However, root cause analytics can highlight fundamental solutions that if implemented, will not only reduce overall interaction volume, but also significantly improve customer experience. Interactions generate a lot of unstructured data (speech, text, machine logs etc.) and analysis requires appropriate tools and skills. For example interaction root cause analytics may highlight the need to coordinate marketing communications across channels, re-design bill layout, make web self-service intelligent, and issue proactive alerts. Self-Service Can and Should Be Intelligent: Both companies and customers desire self-service in various channels: web, social, mobile etc. However, a lot of self-service options today are dumb, do not provide the right answers, provide too many possible answers, and frustrate customers. Advances in text and speech analytics, and machine learning allow companies to provide highly accurate self-service responses. These are highly automated systems that are self-learning (accuracy improves over time). The one prerequisite for these systems is a rich knowledgebase. An analogy for intelligent self-service is spam detection. Have you noticed how accurate your is in self-classifying spam so you never see it? This is enabled through text analytics combined with machine learning. Empower and Transform Your Frontline: Too often frontline contact center employees are under-paid and plagued with high attrition. They work in a high stress environment and are treated as a cost center by companies. This has its roots in the past when a call center was the only way for customers to get in touch with a firm. However, today the frontline should be viewed as employees who can earn the trust and loyalty of customers during critical moments of truth when customers expend a lot of emotional energy. Success during these key moments can drive significant positive business outcomes for the firm. Some examples of these moments could include events like a missed flight to attend an important meeting, a lost credit card when traveling overseas, or a stalled vehicle in the middle of nowhere late at night in an unfamiliar locale etc. During these moments, smart technological solutions alone won t cut it, both because complex solutions are required, and because technology alone cannot create an emotional bond. However, an emotionally intelligent frontline employee, enabled with the appropriate technology and analytics can excel in these situations and create sustainable differentiation. Right Channel Customer Interactions: In order to right channel interactions (assigning specific interactions to specific channels), it is instructive to look at four factors: customer channel preference, customer profile and behaviors (commonly available in transactional and other data), interaction complexity (e.g. interactions that require significant diagnostics to solve), and moments of truth criticality (e.g. is this interaction happening during a critical moment of truth, the outcome of which will have significant implications for customer loyalty and trust). Only very high complexity interactions that occur

4 PAGE 4 during extremely critical moments of truth should be handled by frontline live employees, with the rest being relegated to other low cost channels like self-service, and/or chat/sms. Follow and Inform the Customer Journey, Intelligently, Across Channels: Today s contact center world is siloed by channels, sometimes even within each channel across touch-points. This leads to data NOT being shared and leveraged along the customer journey, and results in an inconsistent, frustrating customer experience. Is there a solution that does not involve ripping out the existing channel based contact center infrastructure which firms have already invested in? YES, the answer lies in enabling a scalable, massively parallel processing, cloud-based analytic solution that has three critical features: a) Real-time and batch data ingestion (both structured and unstructured) from multiple channels, touch-points, and enterprise systems like CRM. This will enable a live customer profile and context as the customer moves along their journey with the company. b) Analytics enabled recommenders that implement a multitude of analytic engines (e.g. interaction reason prediction, interaction sense and respond, next interaction predictor, interaction response optimizer, next best offer optimizer) designed to provide the best response in the best channel that takes into account context, customer behavior and history, customer preference, and issue complexity. c) Channel connectors that seamlessly connect via open API s/custom integration with various channels to orchestrate response. Note that channels include not only self-service but also live channels like chat and phone where the actions may be orchestrated in the IVR or at the agent s desktop. Pre-empt Interactions with Analytics: Traditionally customer interactions are considered to be inbound. What if we were able to pre-empt them and solve the issue before the customer reaches out to interact? This would not only reduce interaction volume, but also delight customers. As outlined before, Predictive analytics can help. They can be used to predict interaction reasons even before the interaction happened. For example, if the real-time solution described earlier sensed that a customer was not able to resolve an issue with web based self-service, it could respond via SMS with a solution, even before the customer reached out. Similarly, if analytics showed that customers who had Problem X (e.g. install issues with internet service) also tended to have Problem Y (e.g. wireless network setup issues), then a customer who reached out with Problem X would be prompted to check and solve for Problem Y during the same interaction, thereby reducing repeat call incidence, improving first call resolution (FCR), and improving customer satisfaction.

5 PAGE 5 Recently, a large telecommunications provider had identified as strategic goals, significant call deflection and improvement of FCR. We analyzed their call volume over the last year to uncover opportunity areas for call deflection and cost reduction (see Exhibit 1). Exhibit 1 The analysis was performed taking into account both where the customer was in their lifecycle with the firm as well as their value to the company as determined by product mix owned. This analysis led to several recommendations that would lead to a reduction in total interaction volume, a deflection of interactions to low or no cost channels like self-service and chat, and an overall estimated annual cost reduction by 50%. In addition, an analytic engine designed to predict likelihood of a repeat call was developed to pinpoint calls that were likely to lead to a repeat. This intervention would lead to a reduction in repeat calls, thereby enabling an improvement in FCR. Similarly, for a large automotive OEM, the call center was exhibiting deteriorating performance on NPS scores which had been identified as the key metric to influence. Data collected from the NPS surveys conducted by

6 PAGE 6 the call center was analyzed to determine customer experience improvements that would lead to a significant improvement in NPS. Predictive analytics identified prioritized improvements that would lead to an NPS improvement from -29 to +70 (see Exhibit 2). Exhibit 2 As contact center executives prepare for the future it is imperative to keep the following in mind to ensure success: 1. It is critical to stay nimble and not over-invest in expensive software solutions that promise the world. SaaS solutions that leverage the cloud and rely on open source technologies will afford the most flexibility.

7 PAGE 7 2. You don t have to always rip-out existing siloed infrastructure to deliver a consistent, intelligent customer experience. 3. Make self-learning, real-time analytic engines a key part of your decision toolset. 4. In a multi-channel world, what s important is to right channel interactions, making the channels work together seamlessly, and enabling a consistent customer experience across them. 5. Don t over invest in self-service or pure technology solutions at the expense of your frontline We believe that contact centers today are ready to lead a paradigm shift and drive transformative customer experiences for companies and customers. Customer experience is going to be the sustainable differentiator of tomorrow that differentiates the winners from the losers. Successful contact centers of the future will transform from the cost centers they have been to creators of delightful customer experiences Fwww.adobe.com%2Fcontent%2Fdam%2FAdobe%2Fen%2Findustryinsights%2Fsolutions%2Fpdfs%2Fcio2_compelling_customer_intreractions.p df&ei=ywrkuc6igbi14aphoogqdq&usg=afqjcne-0hinvo_agcen56lf4sjupr1tha&sig2=kvjodlcfwwo4clntxzw5ya 4.

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