5 Universal Truths Jeopardizing Your Technical Support Success
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5 Universal Truths Jeopardizing Your Technical Support Success


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 the Age of the Customer, it’s become evident that customer service improvements that drive effective experiences should be a top priority. However, there is room for improvement. Half of the respondents to the survey are not satisfied with the processes in use to create analytics. That only 22% say they receive training for creating and using analytics indicates that discovering insights from data is still a work in progress for many companies.

When it comes to technical support provided by the contact center, analytics is critical for creating continuous improvement that results in the delivery of service experiences that customers value. Understanding how your customers think and interact with your products and brand must be a top priority for analytics to direct decisions that drive value for both your customers and the business

As a technical support provider, we developed an analytics service that helps our clients overcome the limitations and learning curve of doing it all themselves. The program helps to effectively measure, predict, and shed light on trends in customer experiences that directly impact overall effectiveness, profitability, and satisfaction.

To achieve these outcomes you need insights that are culled from actively listening to the voice of the customer, to identify patterns from call and transaction data that are indicative of customer needs and opportunities. This process, of course, sounds easier than it is to execute in practice.

Technology companies are aggressively pursuing customer insights through analytics to make better decisions about technical support 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 five universal “truths” that are found again and again—at different contact center sites, for different technology companies, in different geographies and with different products.

These “truths” –as we have labeled them—have been tracked for over three years. We’ve returned to them every 60 days to apply the data and look for differences across client work, but each of the five has held true over time. As we’ve helped clients address these “truths,” we’ve developed some theories about why they happen, what their indicators are, and how to resolve them. We suspect that at least a few of them may be lurking within your technical support program.

The Five Universal Truths Impact:

  • First call resolution (FCR) rates
  • The quality of the customer’s experience as related to CSAT
  • Average handle time (AHT)
  • Alternate channel adoption
  • Agent adaptability for personalized experiences


Universal Truth #1: Current business processes are not designed for a one-touch customer experience

In our observation of calls through active listening projects, we see a recurring pattern that provides clear indication that call workflows are designed to create an in-process solution— and not set up to actually solve the problem. The processes employed for technical support issues almost always require next steps and transfers to other departments. In all instances of analysis, we have found that there are a large set of calls where customers are being transacted with across departments, and across different support channels, but whose issues are not being satisfactorily resolved.

The symptoms of this “truth” include customer frustration, repeat calls and a high number of open customer service tickets. Those outcomes lower effectiveness and customer satisfaction, as well as increase operational costs.

The orientation of the client plays a role in sustaining this universal truth. While the conversation preaches customer service, the directives to contact center providers are based on cost reduction. Cost and customer satisfaction are the two levers most pulled in contact center operations. The fact that they conflict is often approached 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 be (and should be) resolved during the first call. One of the reasons why processes that could enable FCR aren’t developed is due to departments that end up at odds due to silos of responsibility. Additionally, contact centers place the next step of ownership of the problem in the customer’s hands – reducing costs initially, but increasing the overall cost in the aggregate to solve the problem.

Questions to ask if this “truth” exists for your technical support program include:

  • Given the call drivers, could the “next steps” be done during the first call? What would need to happen to facilitate that outcome?
  • What skillsets do the other departments have that we could develop on the support team to allow them to close more customer service tickets on the first call?

Example: Designing a more complete one touch experience is possible. One client wanted all escalations to go to their internal support team, regardless of the severity of the problem. After analyzing the work, we determined that 40% of the calls transferred could be handled by the agents on our team – they were just not given the opportunity to resolve the customer’s problem. As well as handling these calls at lower cost than the internal team, Customer Experience scores on the retained calls increased by 32%.


Universal Truth #2: Quality monitoring forms are designed to measure the technical correctness of the agent, not to provide great customer experiences

As a standard, quality assurance (QA) teams listen to an average of two calls per agent, per week. Our analytics program dives deeper and listens to a very large set of calls within a specific time period. A limitation of standard processes is that the QAs aren’t designed to calibrate the interaction between the customer and the agent. Rather they focus only on the agent’s correctness and adherence to workflows and processes. Our analysis has discovered that fatal errors—what we term auto fails—are nearly always related to business process items. This is often due to a focus on ensuring that agents meet the minimum standards for the call related to mandatory client “musthaves.” Agents are often graded on a pass or fail score. The lack of nuance considered does not help companies to identify potential improvements that could raise CSAT, because the offset would be a lower score in relation to quality monitoring.

If your technical support program is reflecting high quality monitoring scores and low CSAT scores, this could be a symptom that universal truth #2 exists in your contact center. If the reverse is true, and quality monitoring scores are lower, but CSAT is higher, the symptom remains, but it is an indication that agents are trying to organically overcome limitations that constrain them to provide the customer with 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 product knowledge, probing skills, empathy, and other attributes displayed during calls, our team identifies the best behaviors that should be coached and encouraged to achieve the client’s goals. Agents with fatal errors can be retrained and quality forms can be redesigned.

Questions to ask if this “truth” exists for your technical support program include:

  • Can we identify the behaviors that drive great customer experiences?
  • How will we redesign the quality monitoring process to enable this?
  • What needs to be modified in our coaching to correct fatal process errors in a way that still improves CSAT?

Example: Redesigning QA forms can bring big benefits. A client had 2 auto-fail questions on their QA form, but also tied 35 of the 100 points available in the form to attributes related to the auto fail questions. Our study determined that achieving a great customer experience hinged on 3 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 3 key attributes. Over the course of 6 months, average Customer Experience scores improved by 12% by focusing attention on these.


Universal Truth #3: Two common drivers for increasing AHT

Efficient AHT is the Holy Grail for technical support interactions—at least from the company’s perspective. It’s about cost containment. However, our analysis finds that achieving this nirvana doesn’t need to reduce the quality of the customers’ experience.

The first common driver we identified for increased AHT is the failure of the agent to effectively understand and isolate the customer’s issue early in the call. In practice, we’ve proven that spending a few quality moments at the beginning of the call to correctly identify the problem(s) reduces the overall time spent on resolving the issue.

An additional 15 seconds spent probing effectively early in a call can shave two minutes off the overall handle time. The essence of resolving the impact of identifying the problem quickly is to teach agents to probe deep enough to identify root cause—ask the extra question, then make sure they understand any subsequent underlying problems.

Indications that this “truth” exists in your technical support program can be evidenced by the agent trying multiple solutions before the actual problem is resolved to the customer’s satisfaction. Another indicator is seen in calls where the customer is put on hold multiple times while the agent searches for a solution.

Questions to ask if this “truth” exists for your technical support program include:

  •  What are the most common call drivers that our agents should probe for first, and what are the most common follow-up questions?
  • How can we create a more effective triage process?

The second common driver of increased AHT is an inefficient customer verification process. Depending on the company or product, the customer could be required to provide a ticket number, serial number, or product ID or model number. Our analysis has discovered that it’s common for customers not to have this verification at hand, resulting in customer initiated hold time while they try to retrieve it. This results in “dead air” time that unnecessarily lengthens AHT.

One solution we’ve found effective is to create a step in the IVR so that customers are told what information they need to have ready while they are in the queue. Another is ordering the reasons people call by the highest volumes first, thereby shortening the time that customers must listen to the instructions in the IVR before they can make a selection.

Questions to ask if this “truth” exists for your technical support program include:

  • Can our IVR process be re-organized to shorten the time it takes customers to make a selection?
  • Can we add verification information to the places where our customers will access the number to call for technical support? (website, mobile app, application help instructions, etc.)

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. This also involved creating a 2nd stage within the IVR to ensure that customers had key product information available once troubleshooting the problem began. The result of these changes was an AHT decrease of over 6%, and Customer Experience scores increased by over 14%.


Universal Truth #4: Some call volume can be deflected to alternate support channels

As new channels have become available, customers have adopted them, and companies have risen to the challenge. Examples of this “Knowledge Centric Support” include selfhelp on websites, community forums, chat and social media. All of these channels are less expensive than traditional technical support provided by agents over the phone or by email. Developing the ability to deflect calls presents a huge opportunity for cost improvement.

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

  •  Should this call driver be led away from phone support?
  • Can it be led away?
  • Will it never go away?

Once we determined the call drivers that supported a deflection to alternate channels, the team created a process to train customers to use those channels. For example, during “dead air” time while 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?”

In a real-world use case, an electronics company discovered a problem with a product that was irritating its customers. Even though the company couldn’t determine the best way to tell customers how to disable the feature, a customer had figured it out and posted a video in the community forum. Agents were then able to direct customers to the video to resolve the issue.

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 how to resolve the issue themselves. What may result in longer AHT at the beginning will result in lower call volume over time as customers become informed about and adept at using resources beyond live technical support to resolve their issues.

Questions to ask if this “truth” exists for your technical support program include:

  • Which call drivers can we create “guided walk-throughs” for agents to help customers learn to use alternative channels for issue resolution?
  • Which alternate channels are the best options for deflecting calls based on call drivers?
  • How can we best educate our customers about alternate channels for technical support?

Example: An Analytics project identified two key opportunities:

  • 43% of all calls could be handled through the Client’s website
  • Dead air occurred an average of twice on calls, and each occurrence averaged over 30 seconds

The dead air was caused by tool latency as agents switched between screens. We designed and implemented a Job Aide that agents used during dead air instances, to explain how the problem could be solved online. This offered the customer an opportunity to receive an email with detailed instructions and a link to help them solve problems on their own.


Universal Truth #5: Agent adaptability improves customer experience and resolution rates

The reality is that customers don’t all approach technical support in the same way, or with the same level of technical acumen. We see that, more and more, technically savvy customers are taking care of themselves through self-service. The customers who call us now are not at that level and genuinely need our help. The ability of an agent to personalize the conversation based on the customer’s technical level and communication style leads to a much smoother call transaction.

Agent adaptability is the true test of product knowledge in application. An agent must be able to explain what the customer needs to know in a way that the customer can understand. To do so effectively, an agent must apply active listening to evaluate how well the customer understands what he or she is saying to them.

There is a big difference in a conversation that will be effective with a customer who says, “my device won’t turn on,” and a customer who says, “when I turn my device on I see this error…”

Indications that this “truth” exists for your technical support program will be agents that hit their AHT, but are not resolving the problem because they can’t align with the customer’s perspective about the problem or their level of knowledge. This results in repeat calls.

Correcting this issue and coaching agents for adaptability includes 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 so that they can guide the call to a smooth flow. As an example, a customer who indicates that he or she has tried to self-serve their resolution to the issue allows the agent to start the conversation at a different point than if the conversation is with a customer who has not. This can be identified with statements from the customer like, “I went online and learned I needed to do a hard-restart on my phone, but I don’t understand how to do that.”

Questions to ask if this “truth” exists for your technical support program include:

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

Example: Analysts determined that 65% of customers on one study spoke to agents in a conversational manner, but the agents only matched the customers’ style half the time. We coached Agents to identify the customer’s preferred conversation style early in the call, and tailor their own style to the customer during the conversation. AHT increased slightly, by less than 2%, but Customer Experience scores increased by over 18% – a tradeoff our Client was more than happy to accept.


In Conclusion

The discoveries that our analytics team consistently makes reveal universal truths that are present in some form for our clients, irrespective of contact center sites, geographies, locations and technology products. Analytics has been proven to put data to work for the continuous improvement of technical support programs that can achieve a level of performance as a competitive advantage for technology companies. The ability to identify and remove limitations that prevent the achievement of FCR and AHT goals—irrespective of the conflicts between the two—as well as to help 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.

The challenge is in whether or not your contact center provider can execute against the findings in the data that illuminate the path to better decisions, which lead to great customer experiences. Don’t jeopardize the success of your technical 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 technical support can result in sustainably higher levels of CSAT that will bring about 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.