The 6 Universal Truths Jeopardizing Customer Service
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The 6 Universal Truths Jeopardizing Customer Service

Bo Young
Exec. Director, Customer Analytics

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The top three uses of customer analytics are to identify customer service improvements, create customer service strategy and improve customer experiences, as found in a survey conducted by Ventana Research, The Next Generation of Customer Analytics. In this “Age of the Customer” it’s evident that customer service improvements driving effective experiences should be a top priority, and the Ventana survey results identify this as an area of need for brands. Half of the survey participants indicated that they are not satisfied with their current processes regarding the creation and use of analytics. Also, that only 22 percent say they receive training for creating and using analytics indicates that discovering insights from data is still a work in progress for many companies.

According to the 2016 Temkin Survey©, most companies have a long way to go in reaching their desired customer experience goals. It is possible to reach those goals but long-term success will require that companies develop and sustain the following four customer experience competencies:

  • Purposeful leadership
    Leaders operate consistently with a clear set of values.
  • Employee engagement
    Employees are aligned with the goals of the organization.
  • Compelling brand values
    Brand promises drive how the organization treats customers.
  • Customer connectedness
    Customer insights are infused across the organization

As a digital-marketing customer support and technical support partner, we have developed an analytics process that helps our clients overcome the limitations and learning curves associated with managing analytics on their own. This measures, predicts and defines the overall customer experiences that directly impact effectiveness, profitability and satisfaction.

To achieve these outcomes, you need insights that are gathered from actively listening to the voice of the customer — identifying patterns from call and transaction data that are indicative of customer needs and opportunities.

Many companies today are aggressively pursuing customer insights through analytics to make customer service process improvements that achieve customer loyalty and greater lifetime value. What strikes us as most fascinating is that our analytics work has enabled us to isolate universal “truths” that are found again and again — at different contact center sites, for different institutions, in different geographies and with different products.

These “truths” have been tracked for nearly four years. We’ve returned to them every 60 days to apply the data and look for differences across client work, but each of the four has held true over time. As we’ve helped clients address these “truths,” we’ve developed some theories about why they occur, what their predictive indicators are and how to manage them proactively. We suspect that at least a few may be lurking within your customer service program.

The Universal Truths Impact

  • Quality of customer experience due to a focus on business compliance
  • Overall support costs as availability and effectiveness of self-service resources decrease the need for phone agents
  • Call volume as a result of lack of promotion and adoption of alternate-channel support
  • First call resolution (FCR) rates
  • Customer satisfaction (CSAT) ratings
  • Agent adaptability for personalized experiences


Quality-monitoring forms are designed to check for the business compliance of the agent, and are not aligned with providing great customer experiences.

Quality assurance (QA) teams listen to an average of about two calls per agent, per week. Our analytics program dives deeper, listening to a larger set of calls within a specific time period. QA isn’t designed to calibrate the interaction between the customer and the agent. Rather, they focus primarily on the agent’s accuracy and adherence to workflows and processes.

Our analysis has discovered that fatal errors — what we call “auto fails” — are nearly always related to business process items. This is often due to a focus on ensuring that agents meet the minimum clientappointed standards for each call. Agents are often graded on a pass or fail score for these regulatory requirements. The lack of nuance in scoring these calls hinders a company’s ability to identify potential improvements that could raise CSAT, because the offset would be a lower score in relation to quality monitoring.

Example: Redesigning QA forms can bring big benefits. A client had two auto-fail questions on their QA form, but also tied 35 of the 100 available points to attributes related to those questions. Our study determined that achieving a great customer experience hinged on three key agent attributes: empathy, understanding the customer’s needs and call control. By reallocating 20 of the 35 points on the QA form, we created a learned behavior within the agent population to focus on those three key attributes. Over the course of six months, average customer-experience scores improved by 12 percent, due to redirecting agents’ attention on these vital attributes.

If your customer service program is reflecting high quality-monitoring scores and low CSAT scores, this could be a symptom that universal truth #1 exists in your contact center. If the reverse is true, and qualitymonitoring scores are lower, but CSAT is higher, the symptom remains but indicates that agents are trying to organically overcome limitations to provide a better experience.

In our work to correct this “truth,” we’ve found that it’s best to create a scorecard that aligns business goals with customer experience goals. By assigning points to agents based on matching caller types, empathy, and other attributes displayed during calls, you can identify the behaviors that should be coached for improved outcomes. Agents with fatal errors can be retrained and quality forms can be redesigned.

Questions to ask if this “truth” exists in your support program:

  • Can we identify the behaviors that drive great customer experiences?
  • How will we redesign the quality-monitoring process to enable this?
  • How can we modify coaching to correct fatal process errors in a way that still improves CSAT?


IVRs are a simple means of providing access to information without involving a live agent.

When customers call the contact center for service and support, the first thing that greets them is your IVR. The system presents a menu of options they can select to resolve their issue on their own. By analyzing which functions (menu options) in the IVR are used most while also considering call-volume drivers, the IVR can be reorganized to present the most common reasons people call in the most efficient order. This reorganization shortens the time customers must listen to IVR instructions before making a selection and gets them to a resolution sooner.

Another common driver of increased AHT is an inefficient customer verification process. Due to certain regulations, the verification process is rather in-depth, requiring personal information for authentication.

Our analysis has discovered that customers commonly don’t have all the necessary information handy, resulting in customer-initiated hold time while they retrieve it. This “dead air time” lengthens AHT and increases customer anxiety as they search for the information. One effective solution we’ve found is creating a dialogue early in the IVR that informs customers what information they’ll need to have ready while they are in the queue.

Example: Following an analytics study and readout for a strategic client, we redesigned the IVR tree to mirror the frequency of the main call drivers. The reorganization resulted in a more than 6 percent decrease of average handle time (AHT), and a more than 14 percent increase in Customer Experience scores.

Questions to ask if this “truth” exists in your support program:

  • Can our IVR process be reorganized to shorten the time it takes customers to make the correct selection?
  • Can we add information about verification requirements to the resources where customers find the number to call customer service? (Website, mobile app, application help instructions, etc.)
  • Are the self-service options presented by the IVR resolving issues — does it effectively prevent live-service interactions, or are customers more often returning to wait for a live agent because self-service was unsuccessful?


Some call volume can be deflected to alternate support channels.

As new channels have become available, customers have adopted them and many companies have embraced the advancement. Examples of this “knowledge-centric support” include self-help on websites, community forums, chat and social media. All these channels are less expensive than traditional voice or email support provided by agents. Developing the ability to prevent calls presents a huge opportunity for cost improvement.

Example: An analytics project identified two key opportunities — the client’s website could resolve 43 percent of support-call issues, and dead air occurred an average of twice per call, each instance averaging longer than 30 seconds.

The dead air was caused by tool latency as agents switched between screens. We designed and implemented a job aide to strike the right balance between helpfulness and clutter — agents leverage dead-air instances to explain how the customer can find online resources for future issues. They may also offer the customer an opportunity to receive an email with detailed instructions and a link to help them solve problems on their own.

Two years ago, we started an analysis project where we tagged every call on a project by answering these questions:

  • Should this issue be redirected to selfservice?
  • Could this issue be redirected to self-service?
  • Will this issue always need to be addressed by a live agent?

Once we determined the call drivers that supported deflection to alternate channels, the team created a process that trained customers to use those channels. For example, if dead air occurs because the agent is researching a resolution, they may say: “Did you know you could do ‘X’ on the website? Would you like me to send you a link?”

An additional opportunity is to allow agents working with customers who are less tech-savvy to take the customers to an alternative channel and “shadow” them through resolving the issue themselves. What may result in longer AHT at the beginning will ultimately decrease call volume over time by not only teaching these customers what to do if the issue reoccurs, but also showing them how to access and use available resources beyond live technical support for any future issues.

Questions to ask if this “truth” exists in your support program:

  • For which call drivers would it be appropriate to implement a “guided walk-through” so agents can help customers discover alternative support channels?
  • Based on call drivers, which alternate channels are the best options for deflecting calls?
  • How can we best educate our customers about alternate channels for technical support?


Current business processes are not designed for a one-touch customer experience.

Our analytics show a recurring pattern indicating that call workflows are designed to create an in-process solution rather than actually solve the problem. In all instances of analysis, we have found that there is a large set of interactions in which customers are being transferred across departments and support channels without their issues being satisfactorily resolved.

The symptoms of this “truth” include customer frustration, repeat calls and a high number of open customer support tickets. These all negatively impact support effectiveness, customer satisfaction and operational costs.

Client orientation plays a role in sustaining this universal truth. While the conversation preaches customer service, the directives to contact center providers are focused on cost reduction. Cost and customer satisfaction are the two levers pulled most in contact center operations. The fact that they conflict is often regarded as a tradeoff that clients accept without considering potential alternatives.

When our teams examined the calls more deeply, we assessed that nearly half of them could (and should) be resolved during the first call. One reason processes enabling first call resolution (FCR) aren’t developed is that departments end up at odds due to silos of responsibility. Additionally, contact centers place the next step of issue ownership in the customer’s hands, which may reduce costs on an individual basis, but ultimately increases overall cost in the aggregate to solve the problem.

Example: Designing a more complete one-touch experience is possible. One client wanted all escalations, regardless of issue severity, to go to their internal support team. After analyzing the work, we determined that, if given the opportunity, 40 percent of the calls transferred could be effectively handled by the agents on our team, and at lower cost. Ultimately, customer experience scores on the retained calls increased by 32 percent.

Questions to ask if this “truth” exists in your support program:

  • Given the call drivers, could “next steps” be performed during the first call? How can agents facilitate that outcome?
  • What skill sets do other departments exhibit that the support team could develop that would allow them to close more customer service tickets on the first call?


Enhancing targeted critical agent skills will increase CSAT.

Customer support for a service “reads” differently to customers than support sought for a product issue. When customers call in about an issue, they feel as though the institution has done them wrong or inconvenienced them. Customers expect simple needs to be met as part of their regular course of business, but this is not always the case. This is often due to regulations, which are an “invisible” hindrance to the customer’s experience. Analysis identifies two critical agent skills that, when executed properly, can increase CSAT even when the customer is in this mindset of being “inconvenienced”:

  • Confidence: Agents who are “sure of themselves” during their calls consistently earn higher CSAT scores. However, presenting over-confidence can have the opposite effect on the customer’s sentiment toward the company, so this characteristic must be carefully balanced.
  • Empathy: Agents who show an appropriate level of empathy toward upset customers during their calls will have lower dissatisfaction (DSAT) scores. As long as the agent doesn’t come off as robotic and insincere by overapologizing or excessively using the customer’s name, empathy is key to a positive customer experience. Our analysis has found that empathy is only 10 percent innate. The other 90 percent must be accounted for in training.

Additionally, there are two types of conversation styles that customers use: transactional and conversational. If the customer is intent on communicating in a transactional manner, empathy will mean less to them. Efficiency and issue resolution are the key factors in a positive customer experience of this type of communication. Customers who communicate in a conversational manner still expect issue resolution, but also focus on whether the conversation was friendly and comfortable. To these customers, empathy and resolution are the key factors in a positive experience.

Example: Analysts determined that 65 percent of customers from one study spoke to agents in a conversational manner, but the agents only matched the customers’ styles half the time. We coached agents to identify customers’ preferred conversation styles early in the call and tailor their response accordingly throughout the conversation. AHT increased slightly, (less than two percent), but customer experience scores increased by more than 18 percent — a tradeoff the client was more than happy to accept.

Across all industries, the ability of the agent to match the caller’s preferred conversation style has resulted in an increased CSAT score, proving that this agent skill is critical to the customer.

Questions to ask if this “truth” exists in your support program:

  • How can we best help our agents exhibit the appropriate level of confidence?
  • How can we coach our agents to keep from becoming robotic when empathizing with upset customers?
  • What words and phrases used in calls are indicative of the caller type that will help agents match the customer’s intent?


Agent adaptability improves customer experience and resolution rates.

Customers don’t all approach support in the same way. More and more, we see that customers who are confident with the product are taking care of issues themselves through self-service. The customers who call us now are not at that level and genuinely need our help. When an agent can personalize the conversation according to the customer’s communication style and level of understanding, a much smoother call transaction is achieved.

Indicators of this “truth” existing within your support program will be agents that hit their AHT without actually resolving the problem — they’re unable to align with the customer’s perspective of the problem or their level of knowledge. This results in repeat calls.

Correcting this issue and coaching agents for adaptability requires teaching them how to pick out details in the customer’s description of the problem to understand the appropriate communication style and level of technical knowledge. A customer who indicates that he or she has tried to self-serve a resolution allows the agent to start the conversation at a different point than with a customer who doesn’t realize that self-service options are available. Agents should learn to listen for identifying statements like, “I went online and learned I needed to do a hardrestart on my phone, but I don’t understand how to do that.”

Questions to ask if this “truth” exists in your support program:

  • How can we improve our agents’ ability to identify and adapt to customer communication styles to reach a higher rate of FCR?
  • What words and phrases used in calls are indicative of the customer’s level of technical proficiency?
  • How can we help our agents achieve higher efficiencies while maintaining a smooth call flow that creates a great customer experience?


The discoveries consistently made by our analytics team reveal universal truths that are present — in some form — for our clients, regardless of contact center sites, geographies, locations or technology products. Analytics puts data to work for the continuous improvement of client support programs, helping them achieve a level of performance that secures a competitive advantage in their respective industries. Identifying and removing limitations that prevent the achievement of FCR and AHT goals — irrespective of the conflicts between the two — as well as helping customers adopt alternate channels, should be seen as a windfall opportunity. Personalizing the customer experience is one of the last remaining opportunities to create true differentiation.

A contact center provider that can execute against the data findings which illuminate the path to better decisions will ultimately help you create great customer experiences. Don’t jeopardize the success of your support programs by choosing the status quo when presented with universal truths. Your customers’ expectations are rising each and every day. Providing consistently great experiences through improved support can result in sustainably higher levels of CSAT and encourage business growth.


About the Author

Bo Young leads the Analytics and Customer Experience efforts for SYKES, focusing on creating an environment that constructs the optimal experience for each customer engagement. With more than 20 years of senior leadership experience in marketing, branding and market research, Bo leads a global team that performs customer experience studies. These studies combine advanced call-listening strategies and a proprietary data-collection tool, allowing for industry-leading work in customer experience enhancement.

For questions or collaboration, email me at

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