Creating ‘satisfied customers’ is an obvious goal for any organization, and each year, companies spend countless hours and millions of dollars in the name of customer satisfaction. But what happens when tried and true logic, and even years of experience aren’t enough to move the needle? The savviest of companies are learning that it’s time to replace art with science.

 

Organizations that use traditional thinking to justify the key cause-and-effect relationships that drive business results and customer satisfaction ratings often compound the problem instead. In contrast, companies that focus on methodically examining the supplier/customer relationships through interaction analysis obtain far more valuable insights by seeing their operations through the fresh eyes of their customers. These insights drive smart decision-making and produce positive results.

 

Interaction analysis is the framework for organizing and delivering enterprise performance through methodologies, processes, and metrics that get to the heart of the customer experience: the point of contact between the customer and the company. The process may include surveys or speech analytics to study the variables that attract, retain, and strengthen client relationships and anticipate their future needs. Companies are able to apply first-hand customer data to answer important questions that impact their success including:

 

·         Does the organization understand its customers’ needs?

·         Is the organization responsive to the biggest customer priorities? 

·         Are customers having their needs met consistently?

 

Extracting intelligence by applying a series of measurements builds key correlations about supplier and customer interconnections, giving companies the opportunity to discover what variables most affect customer satisfaction and the bottom line. What will make the customer personally identify with the company? What will make the customer recommend the company to a friend?

 

Organizations that embrace analysis ensure that each interaction brings value to the customer and the organization, and obtain reliable data to make the most impactful decisions. This takes discipline, and a willingness to resist the temptation to be all things to all people. One telecommunications provider worked with contact center experts to statistically evaluate more than a dozen customer experience improvement activities. Only two of the activities had any measurable impact on customer satisfaction, and several were actually detracting from satisfaction – a shock to the management team. 

Not surprisingly, the results were met with trepidation, but by using interaction analytics, these findings had meaningful statistical support. Project managers could highly correlate individual operational activities with measurable results. The company redirected efforts and resources accordingly, boosting satisfaction ratings by several percentage points.

 

In other cases, companies feel that they have already tried everything to improve an aspect of their operations, with limited success. Again, acting on statistically relevant data allows companies to implement effective performance improvement methodology.

 

A cable provider’s survey results showed poor customer satisfaction related to outages, despite numerous improvement efforts. By looking at the results analytically, the provider realized that outages are inherently negative events, and that, while customer service cannot eliminate the outage itself, the customer’s satisfaction level could be influenced by altering the protocol for handling outages. After reviewing the data, the company made minor adjustments to agent training which impacted overall satisfaction in these challenging situations. At the same time, they learned they had been significantly over-investing in the issue: dissatisfaction due to outages represented less than a two percent impact on overall customer satisfaction.

 

Approaching customer interactions methodically can also unearth solutions that are not otherwise readily identifiable. One large bank, which consistently ranked among the top three in national customer satisfaction surveys, introduced outsourcing to achieve cost efficiencies and better position themselves for long-term financial viability. The change initially reduced customer satisfaction by 25 points. Instead of pulling the plug on the program, the bank, in partnership with the outsourcing company, chose to analyze interactions closely in three areas:

 

·         What was the outsourcer’s knowledge of the bank’s specific application?

·         What was the outsourcer’s knowledge of the overall banking business?

·         What protocols, including language idioms, did the outsourcer use in handling bank clients (soft skills)?

 

Any one factor could bring down the total customer satisfaction score by 10 points, but the three combined factors could drop customer satisfaction by as much as 35 points. Training was refocused on the total customer experience, and results followed. Today, the bank’s customer satisfaction scores are higher than before outsourcing began.

 

Interaction analysis provides the framework for insight into the customer experience, and analysis of the call or contact structure is an imperative second step. Here too, analytics must be approached from a customer-centric perspective. Satisfaction hinges on the customer’s perception of how their time is spent and can be separated into five segments:

 

·         Salutation

·         Customer identification

·         Problem identification

·         Problem resolution

·         Closure

 

The first three segments are valuable, but can detract from the call if too much time is spent in these areas. In a service setting, regardless of company or industry, callers are most interested in one thing: problem resolution. Therefore, how time is spent is better measured by the average minutes to resolution rather than total length of the call.

 

Speech analytics is an excellent tool to break down this component of the call into meanings and patterns, as well as unseen relationships that can help contact center managers identify and understand customer needs. Experts can identify key factors that help define the state of the customer experience, such as:

 

Positive Experience Indicators

·         Praise

·         Engagement

·         Confirmation

·         Interactivity

 

Negative Experience Indicators

·         Apologies

·         Distress

·         Silence

·         Talk-over