For many years, interactive voice response (IVR) (news - alert) technology has been used as a solution to resolve routine customer service tasks.  By saving significant dollars for these tasks, IVR systems siphon the more complex customer service calls to live agents.  In the late 1990s, many companies began to take advantage of a newer technology �the Internet�to provide an additional self-service option to their customers.  Although the number of online users will continue to grow rapidly, the number of cell phone users will increase at an even faster rate.

Though many companies have deployed self-service Web applications, Gartner states that 92 percent of all customer transactions still take place over the telephone.  Customers are three times more likely to call a toll-free number than use self-service Web applications.  Further, using new technologies such as speech recognition, today�s IVR systems have the potential to allow organizations to automate a wide variety of complex customer interaction tasks at a much lower cost than an agent-handled transaction.  Despite these advantages, IVR systems have been largely ignored in favor of the Internet and outsourced call centers.

Overall, IVR/Speech trails all other interactive channels in customer satisfaction levels.  This phenomenon is a by-product of many factors, including the fact that users� experiences within the IVR/Speech system are virtually invisible and often poorly understood.  Additionally, IVR systems must balance ease-of-use with the economic need to allow users to accomplish increasingly complex tasks.  To further complicate the situation, there is a greater risk of errors that can result in costly consequences.

This is because when an IVR/Speech system does not meet a customer�s expectations, they become frustrated and hang up or �zero out� to a live agent.  Currently, companies must rely on �predictors of behavior� (e.g. customer demographics, psychographics, purchasing histories) in order to design tasks and experiences that are aligned with user needs.  In addition, companies use �indicators of behavior� (e.g. sales reports, transaction logs, call logs) to make the best guess as to why the IVR/Speech is not meeting customers� expectations.  Companies are not using an actual methodology or technology to pinpoint what part of the system needs to be modified in what way and why.

The key to IVR/Speech success is to measure how customers use the system and to align these usage patterns with the business objectives for the system.  This information can be used to continuously modify and evolve the IVR/Speech system to maximize cost savings, revenue and customer satisfaction.  When customers complete tasks quickly and successfully without having to wait in a queue, they are happier and require the assistance of a live agent less often.  The result�if customers are successful in an automated, interactive channel, the company can quickly realize substantial cost savings as well as improve customer satisfaction.

The Problem

According to Forrester Research, customer satisfaction levels with IVR systems fall in the 10 percent range, compared with a satisfaction rate of approximately 80 percent for face-to-face interactions.  This is not just a customer relations issue � it�s a financial problem.

Consider this conservative example:

A company receives 50,000 customer calls each day

• 20 percent zero out to live agents because IVR isn�t meeting their needs

• Each live agent call costs $10

The company is spending $100,000 each day to have live agents unnecessarily complete simple customer transactions.

In many instances, customers are unable to accomplish their task via IVR systems.  This could be for one of two reasons.  First, they call the IVR with a particular task in mind and the system is not set up to handle that task.  Second, the IVR is set up to handle the task, but the customer finds the system difficult to use, confusing or incomplete.  The customer then chooses to zero out to a live agent�or worse�hangs up and ceases to engage with the company altogether.

The reason why so many customers do not find their task options available in the IVR system, or have a difficult time using the system even if the task is there is because companies often fail to take into account three factors when designing an IVR/Speech system�business objectives, user objectives and business environment dynamics.

• Business Objectives: A business objective is what the organization wants to accomplish via the IVR/Speech system and must be articulated as a user outcome.

• User objectives: User objectives are what the customers hope to accomplish via the IVR/Speech system.  These may overlap with the business objectives, but often the user has goals that the IVR/Speech designers did not take into account, or chose not to put into the IVR/Speech system for business reasons.

• Business environment dynamics: Business environment factors include the competition, market conditions and awareness of market desires.

In a recent Forrester study of 15 large IVR systems in airline, credit card and wireless industries, not one IVR received a passing grade in terms of value, navigation, presentation and their ability to engender trust and repeat usage.  What factors can explain such widespread failure? These companies have invested millions of dollars in designing and building these systems�a critical element must be missing.

The Solution: Understanding User Behavior

Understanding user behavior is the missing link.  Businesses need but seldom have visibility into the �black box� of what customers want to accomplish in the IVR/Speech system and how they want to accomplish it.  Thus, translating user behavior into new design strategies is nearly impossible, and making system improvements becomes a game of guesswork.

Today, many IVR/Speech systems are modified on gut feelings, subjective guesses or anecdotal, random information about what customers want�not using hard data about the users� behavior and desires.  Companies then spend millions of dollars on new technology to improve the IVR system, such as speech recognition, in an attempt to �fix� the problem.  However, since they do not have a way of factoring in actual users� behavior systematically, the new technology falls short of its potential.

A new approach to IVR/Speech design and modification is necessary to enable companies to manage IVR business performance.  Understanding user behavior is critical in order to match business objectives to those of the users.  For example, if 50,000 people call the IVR/Speech system each day, but 10,000 of them leave the system without doing anything, companies need to know why. 

The best way to align these factors is by focusing on user behavior�understanding how customers are acting once inside your IVR/Speech system, incorporating that with existing customer and transactional knowledge and using that information to drive IVR/Speech improvements that directly impact value-driving behaviors.

Customer Behavior Intelligence

A Customer Behavior Intelligence solution will assess customer usage of the IVR/Speech system and determine how it aligns with the company�s business objectives and user goals, resulting in cost savings and increasing the company�s bottom line. Customer Behavior Intelligence solutions will help organizations measure user behavior, analyze user behavior measurements and decide on how to change the system and implementing those changes.

Step One: Measure User Behavior

User behavior should be measured in two phases � discovery and addressing business objectives.  In the discovery phase, analytics can be used to find specific functions in the IVR/Speech system that are causing users to zero out to live agents or hang up the phone altogether.  Many times, these functions within the IVR/Speech system are not operating as intended, indicating the user�s behavior could suggest some adjustments for improvement.

The second phase addresses specific business objectives.  Business objectives should be translating into expected user behavior, so IVR/Speech designers can determine if the customers are using the system in the intended fashion.

Step Two: Analyze User Behavior Measurements

The next step is to analyze user behavior data and pinpoint areas that are causing potential problems as well as function areas that represent opportunities for leveraging existing successes.

Step Three: Decide on Change

In most cases, decisions to modify the IVR/Speech system will fall into three main categories:

• Modify experiences that are causing confusion or frustration

• Extend the capabilities or proven and successful interactive experiences

• Incorporate new automated tasks

In speech applications, behavior analysis can also help to determine how to change dialogues, properly tune speech recognition (news - alert) for optimal performance and improve error handling strategies.

Step Four: Implement Changes

In this stage, changes are implemented to the IVR/Speech system with an eye toward ongoing improvements.  This change process must be continuous for two reasons.  First, streamlining one aspect of the IVR/Speech system often means that users will get farther into the system and uncover new problems that they had not previously experienced.  Secondly, business objectives, user objectives and the business environment can change from year to year, month to month, or even more frequently.

Conclusion

As self-service options continue to proliferate for consumers, companies are finding it essential to create interactive user experiences that are both helpful and meaningful.  At the same time, these experiences must meet bottom line business objectives � cost savings, revenue generation and customer retention.  As companies respond to these opportunities, they are finding a variety of reasons to reinvigorate the IVR system. 

With behavioral insight, companies can better balance and meet business objectives.  The key to optimizing business performance is to turn meaningful observation and analysis into new, value-driving action. 

Dr. Cohen is president, CEO and co-founder of ClickFox (www.clickfox.com).  ClickFox�s software modeling solutions enable its customers to translate complex customer interactions across multiple self-service channels�such as IVR, speech recognition, Web sites, kiosks and CRM systems�into fact-based decisions that optimize channel and cross-channel business performance. Dr. Cohen holds a Ph.D. in Mechanical Engineering and a Masters of Science in Computer Science. A data modeling expert and a leading research faculty member and educator at the Georgia Institute of Technology, Dr. Cohen alongside Nissim Harel, conceived the original concept of ClickFox. Through his vision and leadership ClickFox is growing from an idea to a leader in its field, counting among its customers several Fortune 100 companies. Prior to creating ClickFox, Tal helped organizations such as General Motors, the U.S. Air Force, and Boeing achieve better business results through creative modeling solutions. He has also authored multiple publications on data modeling and numerical methods.

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