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TTEC - Blog

Beyond the Bot Buzz: Balance Humans and Automation

There are plenty of buzz-worthy discussions happening in the customer experience space around automation, artificial intelligence (AI), bots, and the like. But just because you can automate something, doesn’t necessarily mean you should.
By putting the customer experience at the center of the discussion, companies can balance humans with automation to optimize interactions.
Customer interactions are becoming more digitally driven and automated to enable faster, convenient, precise interactions. People want a different way to interact with the companies they do business with, and bots are one way to achieve this.
Customers don’t want call centers anymore. At least not the way they exist today. And companies continue to digitize interactions to reduce costs.

  • Nearly half (42%) of global consumers predict that the call center will cease to exist by 2025.
  • 36% of call center interactions are a direct result of digital channels failing to provide answers.
  • Cost reduction and efficiency are top priorities among contact center leaders.
  • 44% of U.S. customers said they’d prefer AI chatbots for customer relationship management.

(Source: Conduent, Call Center IQ, Aspect)
Automated services are here to stay. So instead of "if," answer "how" to use automation in your business. As a guide, we recommend thinking in terms of "Big E" and "small e" experiences:

  • Automate repeatable small “e” experiences that reduce friction, improve convenience and speed.
  • Use humans for big “E” experiences that benefit from emotional, personal connections. 

Bots can’t replace the human value of empathy, cross-selling, or up-selling during an interaction. They won’t know be able to read emotional signals to stave off customer defection. They don’t themselves build a brand. And they won’t know when to take the conversation in a different direction when things diverge from the norm or get complicated. When in doubt, people will prevail.
Read more best practices in automation from both the customer experience and operational perspectives, along with vertical-focused recommendations in the TeleTech Quarterly Insights e-book, "To Bot or Not to Bot."

Like this post? Subscribe to our customer experience blog.

Also, check out the most recent issue of our monthly customer experience eNewsletter, Dialogue.


Publish Date: June 2, 2017

3 Steps to Harness the Power of Advanced Contact Center Analytics

Today, the proliferation of data from more and more sources is setting the stage for new, advanced decision making and therefore thrusting analytics to the fore. Organizations are increasingly leveraging analytical insights to deliver more personalized customer experiences at scale.
Contact center leaders are aware of these changes and are trying to determine how to use the available data assets to do a better job in serving customers quickly and efficiently. As such, forward-looking companies are implementing more advanced analytics tools, along with richer data sets to better understand their customers’ needs and make faster decisions. To make sure your company doesn’t get left behind, we’ve outlined a strategy to begin transforming contact centers into a modern insights center.
Identify your objective
The value of information is the cost of making the wrong decision. In this context, any analytics that can improve decision making, and produce better business results (e.g., increase revenue, reduce costs, higher NPS scores), is worth doing. 
The challenge is to identify the right analytics tools to best help your team meet its goals. The key stakeholders must therefore agree on what the primary objective is that they are focused on. For example, is the goal to increase operational efficiency or customer satisfaction? Answering this question will help determine the scope and direction of your team’s analytics strategy.
Aim for actionable insights
Analytical insights are important provided they affect decision making.  This implies the analytics are “actionable” and sufficiently timely (perhaps even in the moment) to make a difference.
For instance, journey analytics are uncovering insights regarding how customers interact with brands and where there may be opportunities to reduce unwanted friction.  Not surprisingly, there are often key differences in these journeys depending on what the care issue is and who the customer is.
Contact centers are also using new speech and text analytics tools to understand emerging customer care issues, identify potentially explosive legal issues, and assess customer sentiment, all in the name of improving customer satisfaction. These same tools can also be used to evaluate agent performance and assorted processes that are integral to operational efficiency goals. Other analytics are being used to assess, evaluate, and streamline operational processes, as well as measure agent performance, knowledge management systems, and learning programs.
Regardless of the type of analytics your team chooses to implement, contact center analytic efforts should be aimed at understanding three questions:

  1. What is happening with respect to activities within a customer case? 
  2. Which customers (e.g, first-time, returning, etc.) are impacted? 
  3. How do customers and agents feel about their experiences? 

Create a closed-loop” insights process
It is also important to create a sustainable system for collecting data, analyzing it, testing it, and deriving actionable insights from the data. There are several critical steps to creating a closed-loop process for doing this. 

Step 1: Map the existing data flows into and out of the contact center, and, based on preferred, pre-defined customer experience journeys, identify gaps in customer knowledge that could be filled by integrating data from other internal or external sources. 

Step 2: Build processes to export the contact center data to a centralized customer data repository on an ongoing basis so that everything that is known about customers’ attributes, attitudes, behaviors, and value can be leveraged from one location. 

Step 3: Analyze and model the consolidated data, and orchestrate specialized actions aimed, say, to maximize customer satisfaction while also achieving designated SLAs (service level agreements).  These orchestrated actions can (and should) include a wide assortment of champion/challenger tests to support continuous improvements. 

Step 4: Develop automated reports and dashboards that will display key metrics pertaining to the various interactions customers have with the brand, as well as the downstream behaviors that will determine the impacts on the business.  These downstream metrics could include customer satisfaction and Net Promoter Scores, customer retention rates, product purchase rates, revenue, and profitability.

Think of the steps as part of a continuous cycle in which data flows into a centralized customer data repository where it can be analyzed and tested to provide insights that further enrich the contact center and the rest of the organization’s understanding of its customers.

If you would like more information on how to harness the power of analytics in the contact center, check out our eBook, "Making the Grade: How to Convert a Contact Center into an Insight Center."

Like this post? Subscribe to our customer experience blog.

Also, check out the most recent issue of our monthly customer experience eNewsletter, Dialogue.


Publish Date: February 13, 2017

Is it Time to Toss Average Handle Time?

When it comes to managing Average Handle Time (AHT) in any contact center, there are countless articles on how to reduce, optimize, and measure the time spent engaging with a current or prospective customer champion. However, companies that focus primarily on reducing AHT are wasting time and valuable resources; not to mention most likely negatively impacting the experience with the person with whom they are engaged.
Strategies that prioritize AHT rates fail to address the actual issue, which is how to properly incentivize teammates (employees) to ensure that customer’s needs and expectations are being met. Here’s how companies can modernize their AHT strategies and better align them with customer behaviors to deliver a more satisfying experience.
Average handle time is a widely used contact center metric that measures the total length of time it takes a representative to engage with a customer, across any channel. Having a low AHT suggests representatives who are assisting customers are highly productive. The belief is that when your brand ambassadors are encouraged to handle an issue as efficiently as possible, they are able to help more customers. And fast customer service means fewer customers are waiting and becoming irritated.

An obvious pitfall, though, to focusing on AHT is that it detracts from and overshadows other factors, such as quality. The more attention contact center managers (your customer experience stewards) and representatives give to low AHT rates, the less time they have for other concerns, such as examining the quality of their service.

Furthermore, AHT hails from an era when the telephone was the primary customer service channel. It was also a time when customers had few options in which to complain of receiving poor or rushed service.
But times have changed.

In a world that is increasingly digital-first, customers reach out to voice channels only when they have a complex issue or can’t find the answer themselves. Additionally, more and more simple inquiries are being handled by automated systems, intuitive self-service strategies tied to an optimized knowledgebase strategy, integrated mobile app support, and more. Essentially, we are headed to a place where Tier 1 support—handled mostly by human interactions today—is replaced with advanced technologies and more efficient customer engagement design principles.  Machines, bots, optimized process, and automation will essentially make “obsolete” the need for Tier 1 human interactions as we know them today, but more on this in an upcoming article.
As innovative organizations continue to “teach” their customers how to self-service their way through automated and efficient Tier 1 support, it becomes critically important to have a team of expertly skilled, customer-first brand advocates to support the more complex, nuanced interactions that become difficult to resolve.

Contact center representatives can answer questions that require more time to properly resolve and build a “customer for life” relationship. In other words, a model that prioritizes AHT rates is likely out of touch with the needs of today’s customers. And in an age of empowered, hyper-connected customers, companies can’t afford to be tone-deaf about the customer experience.

By the same token, AHT still has a role to play in the modern contact center—the challenge is balancing the value of the AHT metric with other metrics. For example, instead of prioritizing the number of answered calls or closed tickets, make sure associates understand that their performance also includes outcomes like customer satisfaction, minimal customer effort, superior teammate NPS results, or renewal rates. 
And when setting AHT metrics, look to contact center representatives who receive high marks in customer satisfaction as models. Gamifying the results your teammates achieve and presenting them to your team in real time builds teammate confidence, accelerates their performance, and challenges them to over achieve, while also bringing an element of fun and personal passion.  Doing so also helps align the AHT rate more closely with customer-centric behavior and practices. Additionally, consider setting a range of acceptable rates rather than just one rate. Armed with a range, managers can still track their team’s performance and identify outliers without employees scrambling to meet an artificial goal.
The bottom line is that to remain competitive, companies must be flexible and nimble enough to adjust their performance metrics according to the needs of their customers. And just because something worked well in the past, that doesn’t necessarily mean it will work today. Low AHT rates may have been the ideal goal several years ago, but customers—and the issues they inquire about—have changed. It is up to companies to respond to those changes and deliver better customer experiences before their competitors do. 

Like this post? Subscribe to our customer experience blog.

Also, check out the most recent issue of our monthly customer experience eNewsletter, Dialogue.


Publish Date: November 10, 2016

Greet, Love, Engage: Three Paths to a Stress-Free Live Chat Experience

When today’s customers seek help from a company, they want stress-free experiences. Navigating IVRs, repeating information, and being placed on hold can turn a frustrated customer into an irate one, which can ultimately lead to customer defection.

A common solution to these growing service woes is live chat. Live chat provides faster resolution times and quicker responses—overall, customers are viewing this as the most efficient way to get their issues resolved. Studies even show that live chat has the highest satisfaction levels for any customer service channel and it often leads to an increase in conversions.

In fact, Forrester views live chat as an increasingly profitable channel in which to engage customers. In a recent survey, 44 percent of respondents said that having a live person answer questions while they were in the middle of an online purchase was one of the most important features a website could offer. 

In addition to using chat to seek out help during purchases, customers choose chat for various reasons: when they can’t talk privately but they can type, when they need to multi-task, or when they can’t stop what they are doing.

Although chat technology is maturing and spurring consumer adoption, companies must approach the channel from their customers’ perspective. Therefore, they must think about their customers and build their solutions in the way that customers will want to use it.
At TeleTech, we believe these three best practices are critical to delivering the chat experience that customers want.

1. Don’t blast them with invitations to connect.  

When customers visit a company’s website and immediately get presented with an automatic invitation to chat even before they have a chance to browse merchandise, they’re likely to click off the invitation and the window to chat with them will be missed. 

Smart utilization of automated prompts intended to engage customers in a chat session at the right time can be much more successful. Prompts based on time spent on page, first-time visitors, if they arrived from a specific page, or based on words typed in the search box can serve as useful triggers for when to accurately serve up chat invitations. But ultimately, they should be used to understand the customers’ needs and help resolve their issue faster (and maybe even anticipate their next issue).

2. Provide associates with visitor behavior analysis. 

Companies can no longer just make chat available when their agents are available. Customers should receive chat offers when they’re stuck on a page or when they abandon their shopping carts. To chat smartly and at the right time in the customer journey requires associates to be aware of visitors’ online behavior before the chat session even begins so they can accurately understand what the customer might be looking for. Also applying breadcrumb data that details devices used, searches made, and other page views, as well as authentication details will help assemble accurate customer journey paths. Finally, by pulling in social, demographic, time zone, and geographic data, companies can match customers to the appropriate associates. Such information will also help the associate route the chat session to another associate who may be better equipped with the knowledge about a specific product the customer is inquiring about.   

Having this breadth of data will enable associates to act on customer needs in real time and in personalized ways by solving their issues, upselling them, and anticipating their next issue. Ultimately, the idea is to keep customers engaged in chat sessions and returning to the site for higher customer satisfaction and NPS.

3. Promote chat/text merging crossover.

Often times after chat sessions end, the customers may find that the steps or advice the associate offered didn’t actually work and their issue remains unresolved. To prevent this from happening and to promote first contact resolution, associates should habitually send customers texts messages following their chat sessions to confirm that their issues were resolved or give them the option to text back the same associate if they have follow-up questions or concerns.

As more customers begin using self-service functionality and relying on mobile to engage with brands, the more important it will become for companies to ensure live chat is always-on 24/7 and working to keep customers engaged and not the opposite. And as more and more customers experience live chat—and enjoy the convenience it offers—the more likely it will be for revenue and customer loyalty to also increase.

Like this? Subscribe to our customer experience blog here.

Also, check out the most recent issue of our monthly customer experience eNewsletter, Dialogue.


Publish Date: August 12, 2016

Getting the Most From Customer Surveys

One of the most obvious outcomes of social media has been the willingness of people to share their opinions—both good and bad. According to a February 2016 study published by Ipsos Loyalty, 52 percent of consumers who had a bad experience with a brand told their family, friends, or colleagues about it while an even higher percentage (56 percent) of consumers shared positive experiences.

The number of social channels has grown so much recently that most everyone looks for some feedback, criticism, advice, or praise before every purchase. It’s amazing that even a customer’s experience eating a hamburger at a fast food restaurant can get someone to share what they thought of it. 

So, what does that mean for companies that have made sizable investments in collecting feedback from their customers? Traditional channels such as IVR, email, chat, and websites collect ratings based on questions about a customer’s interaction or purchase. Newer channels are using mobile devices to collect information through SMS and mobile apps, along with social media sites such as Facebook, Yelp, and TripAdvisor. 

As the variety of channels used for surveys continues to grow, so does the complexity to collect and understand what is being said about a company’s brand. Companies need to define how they will gather feedback, decide how to close the loop with a customer, and determine a data collection strategy that can help define business changes that can be leveraged to improve experiences.

Another interesting component when surveying customers is the type of feedback that’s provided. This is especially true when engaging customers about rating an interaction completed by an employee. Customers recognize many attributes about an interaction and an employee that can be fairly predictable. For instance, the question “Did the resolution of the interaction meet or exceed the customer expectation?” can result in feedback that is both positive and negative based on the context of the answer and how the message was delivered. 

The expectation of each customer is to fully resolve whatever issue he or she reached out to a company to solve. Consequently, the outcomes from these interactions are primarily dictated by process and procedures set up by the company. This is often shaped by whether employees are empowered to resolve a customer’s issue on their own. Meanwhile, how the message is delivered and the tone that’s used is also very important to customers. Along with being courteous, employees must exhibit behaviors that portray expertise and efficiency. If a customer questions what is shared with them, the customers will also question the integrity of the resolution, even the right one.

Survey strategies need to be built on pre-defined goals and anticipated outcomes. The purpose of a customer survey is not only to collect feedback but also to act on the feedback to improve the customer experience. A principal goal of survey design is to determine whether customer expectations are being met and how to get to the root cause if they aren’t. 

The outcomes are specific actions that are meant to address customer needs and to deliver better experiences. Here are a few tips to help improve your survey strategy and improve the impact from polling customers:

  1. Set up a data collection strategy that tracks the root cause over time. 
  2. Separate the process root causes from the employee delivery.
  3. Use survey feedback to enhance employee coaching and development.
  4. Quantify improvements with the associated ROI. Not just in terms of improvements to customer satisfaction ratings, but also in monetary amounts.

TeleTech is creating and managing VoC surveys for its clients and has a proven methodology for data analytics, survey deployment and governance, closed-loop techniques, and improving ROI. The outcome-based methodology takes an extremely complex environment of customer feedback and makes it easy for decision-makers to visualize customer impacts and improvements.

Like this? Subscribe to our customer experience blog here.

Also, check out the most recent issue of our monthly eNewsletter, Dialogue.



Publish Date: July 21, 2016

5 Customer Experience Metrics to Track

A successful customer experience means different things across departments, which is why organizations need a standardized set of metrics to ensure they're meeting their goals. Customer experience metrics can help companies identify unsatisfied customers, lower churn, increase retention and loyalty, and reduce friction across the enterprise.

Despite the fact that measurement is deeply embedded in business functions like finance and IT, many companies still struggle with measurement when it comes to customer experience.

TeleTech recommends five key metrics when gauging the effectiveness of a company’s customer experience strategy.

1. First Contact Resolution

First Contact Resolution (FCR) sounds like it should be easy to measure, but many organizations find it difficult to even define the metric given how customers use myriad channels when engaging with an organization.

FCR metrics are necessary for root cause analysis and process streamlining. Call quality FCR determinations and FCR call stats are great for identifying training and coaching needs for associates and process improvement opportunities. FCR can be measured by QA call monitoring, IVR survey, or post-call or Web survey. Measuring First Contact Resolution is the first step toward customer experience improvement.
2. Average Handle Time

Average Handle Time (AHT) is a key measure for any contact center. In essence, it tells organizations the total time their associates spend with a contact.

Usually, a lower AHT implies that contact center associates are being efficient and quickly handling customer concerns. However, just because a call is shorter doesn’t necessarily mean it’s more effective.

There’s been a long-running debate over which metrics to use as an organization’s primary ones: AHT or FCR. The problem with AHT is that it tends to focus associates on speed of service rather than quality of service and omits the details about the outcome of the call. This often leads to associates rushing customers off the phone which ultimately leads to a poor customer experience. Oftentimes, a company will remove AHT as a performance metric only to find that FCR rates improve.
3. Net Promoter Score

Net Promoter Score (NPS) was first introduced in 2003 in Harvard Business Review by Frederick Reichelds’ article, “One Number You Need to Grow,” and relies on a single question, “Would you recommend our organization to a friend?” to understand customer loyalty.

Asking the ultimate question allows companies to track promoters (enthusiasts) and detractors (unhappy customers). Customers can be categorized based on their answer to the ultimate question. Although there are numerous pros and cons to relying on NPS to measure customer satisfaction, studies have shown a correlation between higher customer spend and improved NPS.

4. Customer Effort Score

The biggest cause of excessive customer effort is the need to call back multiple times to get an issue resolved. Companies can reduce this type of effort and measure the effects with a Customer Effort Score (CES).

Many companies believe they’re performing well in this regard, because they have strong FCR scores, but oftentimes they’re not addressing the effort that customers made beforehand to get their problem resolved through other channels.

By looking at customer interactions across the enterprise as a whole rather than examining individual interactions, companies can more easily identify areas where customers make increased effort to get issues resolved and fix the root cause or create a solution. 

5. Customer Satisfaction Score

The benefit of measuring satisfaction after each engagement is that companies can quickly see whether associates have resolved the problem and how happy the customer was with the customer experience that was delivered.

While this type of analysis is important, it’s critical not to focus solely on individual interactions. A great customer experience is made up of multiple interactions so organizations must measure overall satisfaction. Measuring the overall customer satisfaction is a better predictor of the likelihood of a customer churning.

Measuring customer experience has thus become one of the biggest challenges that businesses face. Considering the myriad interactions a customer makes across a company’s touchpoints, defining the right set of metrics to gauge customer experience success requires mapping all points of contact, applying a number of customer experience metrics, and integrating customer interactions. Only then will companies begin to gauge if they’re effectively delivering on the customer experience.



Publish Date: June 1, 2016

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