Many companies include a variation of the goal “Provide world-class service” in their mission statements. These same companies have well-planned business strategies and comprehensive marketing strategies. But ask them about their customer-service strategy and you’ll find it’s often nothing more than a bullet point in the mission statement.
A customer-driven service platform allows a company to place a dollar value on customer satisfaction, thus enabling management to tie financial results to customer satisfaction and employee performance. The keys to building a strong customer-driven service platform include collecting and managing the right customer- and employee-satisfaction data; including call-monitoring data, customer and employee survey results, daily internal metrics, and then using a variety of advanced analytics and predictive modeling techniques to bring everything together to track and predict the success of business and marketing efforts.
For many companies, it makes sense to outsource some or all of the process of developing a successful quality program and building a robust customer-driven service strategy. The results can have a dramatic effect on brand loyalty, day-to-day marketing efforts, and the long-term bottom line.
When establishing a customer-driven service strategy, the first point to look at is how your customer is represented in your company. For most companies, customers are represented by data collected in many ways, for many reasons, and by many departments. There usually isn’t a single department responsible for pulling all the data together. A company with a strong customer-driven service platform will have a quality department responsible for linking all the customer data the company collects.
There are four key types of data required for a well-built customer-driven service platform:
In many companies, various departments access this data through static daily or weekly reports. Nowhere do these data meet analytically or operationally to show the cause and effect of major business actions. Because the data aren’t linked, it’s difficult for a company to see how different aspects of operations are affected by one another. In reality, each of the four data points reflects effective “levers” that can be pulled to affect business or marketing efforts. Over time, these four key data points can be tied to financial fluctuations and return on investment (ROI) analysis.
It’s been said, “He who has the data, rules.” In many companies the four key data types are owned by or kept in separate silos or departments that have formed strong “fiefdoms.” Marketing owns the customer data, human resources owns the employee feedback, quality owns the monitoring data, and operations creates and drives the daily metrics. Fiefdoms tend to protect their data and can be unwilling to share or allow other departments to control the analysis, impeding the development of a customer-driven service platform.
While other departments should take an active role in the collection and interpretation of data, only one department should be responsible for linking all the data that will feed the customer-driven service platform—the quality department. If fiefdoms exist or the quality department doesn’t have the analytical power to build the linking service platform, then consider outsourcing the task to a quality company that specializes in building customer-service measurement platforms. By centralizing this responsibility in the quality department and partnering with an outsourced quality company, management can reduce internal power struggles and allow the outsourced partner to be the liaison between the opposing factions.
More and more, companies are outsourcing large portions of what were traditional quality-department functions. Large and small companies are starting to create in-house quality-management teams, while outsourcing the actual work of collecting data, market testing, and continuing-improvement projects, including Six Sigma efforts. The benefits of this emerging quality model include costs savings and improved performance, as well as third-party neutrality that appeals to company management, regulators, partner call-center operators, and third-party sales providers.
The four primary quality operations to consider outsourcing include:
There are a number of reasons to outsource the monitoring and evaluation function. Much of it has to do with the type of monitoring model that your company employs: most companies operate either a traditional monitoring model, multiple quality-assurance monitoring (QAM) teams operating within the center, or a decentralized monitoring model—a QAM team accomplished by coach-driven monitoring with no internal QAM team.
The challenges raised by these two models are similar: they’re costly, calibration consistency of accurate standards is difficult, and the objectivity of the reporting is suspect and not effectively used by the center or the company. What’s more, in the decentralized model, instead of one internal QAM team to calibrate, there are as many as 40 individual coaches or assistant coaches all working different schedules. As call volumes increase and service levels drop, it’s tempting to shift quality-monitoring employees to help answer calls.
The new monitoring model
The emerging centralized monitoring model provides a viable alternative. This model is actually a hybrid of the traditional and decentralized models and allows companies to replace the traditional internal QAM team and outsource the required base, call-monitoring, and evaluation requirements for coaches in the decentralized monitoring model. Besides reducing costs, the emerging model puts actionable data in the hands of management and coaches, so they can focus on improvement efforts and targeted coaching.
In the emerging centralized monitoring model, an objective, third-party company evaluates all centers from one core calibrated group of employees. This group is directly calibrated by company program managers and reports results on a robust reporting platform that allows anyone in the company to track a quality trend at all levels, including that of the individual employee. This model can eliminate the need for a large centralized QAM team, as there’s no need to “check the checkers.”
One of the challenges with this model is the perceived lack of accountability of an outsourced quality company. It can be easy to blame a lack of improvement on not getting the right data from an outsourced quality company. Your outsourced quality-evaluation vendor must have a good calibration process, along with a great reporting platform, to eliminate this concern.
Without an actionable and accurate customer- and employee-feedback loop, a company cannot begin to understand the effects of its business and marketing plans, as well as company procedures, policies, systems, products, and services. Every company should have a minimum of two types of customer surveys—relationship and transactional.
For budgetary reasons, many companies use only relationship surveys. Relationship surveys track the brand image in areas such as price, value, advertising, customer service, billing, etc. Surveys are given at random to the general base of customers with no point of reference to business activities. Thus, a customer may have used a company’s product or service one week ago or one year ago. With no point of reference, customers draw their answers from collective memories or their experiences or what they remember from advertising or word of mouth. Relationship surveys are good for tracking brand strength but very bad for managing the day-to-day business decisions affecting customers.
Transactional surveys measure customers’ experiences within a given time frame of their interaction with one aspect of a company’s products, services, or support. Customers have had sufficient time to complete their interactions and form opinions. A good transactional survey breaks down the customer’s interactions into the key elements of the experience. With the proper analytical modeling, a company can survey and track which aspects of the customer experience are causing the customer to be satisfied (or dissatisfied) with the outcome of the interaction.
Transactional surveys drive operational changes. Because they are relevant to a specific experience at a specific point in time, it’s possible to tie survey results to customer satisfaction as it relates to weekly internal metrics and financial performance. When building a strong customer-driven service platform, a company should consider linking all customer data from transactional surveys to daily-operation metrics and relationship data in order to track the correlations to financial fluctuations in the business. Once this link has been established, the company can truly have a service strategy that drives the business from a customer’s perspective.
Executing a fully functional customer-driven service platform is often a two-year journey, if a company is starting from scratch. In the first year, the proper surveys are set up to collect customer data, which can be combined with monitoring data to validate the effect of customer satisfaction on operations. With 12 months of data, customer-satisfaction and financial predictive models can be run to determine the link between customer and operational data. The second year is used to drive customer-based operational changes on a large scale, because investments in customer service efforts can be linked with cost-saving efforts.
This two-year strategy doesn’t mean your company can’t start using survey data from day one. Within three months of starting properly-designed surveys, it can be possible, with effective analytics, for a company to accumulate insightful data to effect change. If you don’t have these analytical abilities within your company then outsource this function to a quality company.
Invite employees to the party
Once a company has built an actionable and accurate customer survey process, it will then have the foundation to replicate the same process with employees. Almost all companies track employee satisfaction, although many companies struggle with what to do with the data they collect. Left up to their own interpretation and without higher analytics modeling, some companies will fall back on simply reviewing employee comments. Using employee comments with limited data analysis leads to misplaced action on events that may not in fact be driving employee performance or attrition.
Conversely, with a well-designed employee survey platform, a company can link employee satisfaction to reduced attrition to improved customer satisfaction to improved revenue. With the right modeling, a company can quantify the return on investment of a pay increase, commission increase, changes to employee benefits, or other aspects of a company’s culture.
Many larger companies have sophisticated marketing and research departments and still outsource survey design, data collection, and advanced analytics. Small companies may have no marketing or research department, and an outsourced partner is critical. Regardless of company size, it’s vital that sophisticated customer and employee-satisfaction surveys are created properly.
Some companies dumb down customer satisfaction data. In fact, some market-research companies admit there are better ways of interpreting customer data but the companies they serve don’t have the discipline to understand and work with higher-level analytics. This has led to much buzz about how a company needs only one question to run its business. The “Net Promoter” theory uses a simple mathematical calculation of customers who are willing to recommend your company to a friend. Every company has detractors and promoters, and Net Promoter simply tells a company whether its number of promoters is growing.
The major problem with the Net Promoter concept is the lack of perspective. Once you know your business is shrinking and/or growing more detractors, how and where are you going to make changes to improve? To identify what needs to be fixed, your business must ask more questions. You will need more insightful transactional data and a higher level of analytics.
To ensure your surveys are asking the right questions, start with an “ideal customer blueprint map.” This is a total exploration of the ideal customer experience for customers in your industry. The mapping includes focus group benchmarks for industry norms and breaks down each aspect of a company’s service delivery cycle. It explores the articulated and unarticulated needs of your customers and tries to define expectations and delights within their service experience. The final blueprint can then be applied to a company’s current business model to determine where there are weaknesses and points of competitive advantages.
From the ideal customer blueprint map a company can then design a blueprint survey. In this process, a comprehensive life cycle survey is created to capture every critical aspect of a company’s service and sales delivery. Through advance modeling techniques, a company can determine the effect of key business activities from a customer’s perspective. The blueprint survey lays the foundation for development of the ongoing customer satisfaction/loyalty survey—a far more effective tool than a generic survey that may completely overlook that one aspect of your business that differentiates you from the competition.
The outcome of a blueprint survey is easy to translate to management and employees because they can see it came from customers’ input, and the results will help show who is responsible for each action that drives satisfaction. Employees will know what they control, how it’s measured, and how they can improve their portion of the customer experience.
Don’t “dummy down” data
One of the most common ways companies “dummy down” customer satisfaction data is by looking at only “top two/three box” responses to key questions. This is where the business reports only the percentage of responses to the 4 and 5 scores on questions with a scale of 1 to 5. When reporting top box response in this way, a company can claim, for example, that “85 percent of all customers are satisfied or very satisfied with our service.” Unfortunately, this isn’t an accurate or actionable reflection of the company’s true performance. Top box reporting also doesn’t reflect the total effect of changing performance within the top boxes as well as downward movement of customers in the bottom two boxes. Any negative movement, regardless of which box the customer rates, is information the business needs. It’s critical for a business to know how all customers are evaluating the business and how all customers are fluctuating in positive and negative directions.
A company that wants to build a customer-driven service platform must employ an index methodology for analyzing and reporting customer and employee survey results. The index methodology survey process calculates multiple critical survey questions into a single number that, when operational, will ensure that customer feedback becomes part of the DNA of any company. A customized indexed methodology should include relationship surveys, tracking the health of a company’s brand, and transactional surveys, tracking real-time operational performance. This index approach can take the single number calculation and break it down into five or six secondary operational representing numbers that allows a business to drive improvement that’s accountable and actionable at all levels in the organization. This indexed approach also makes it easy to compare call center performance at all levels across your entire network.
In addition, the indexed approach also allows a company to track its performance to many national syndicated surveys such as JD Powers and American Customer Satisfaction Index. This approach is best outsourced in the beginning to ensure buy-in from management, then brought in-house after the methodology becomes firmly established.
The final level of higher analytics involves bringing all the data together to track and predict financial impact on business and marketing efforts. Using a variety of advanced analytics and predictive modeling techniques, a good quality partner will be able to help your business determine where you’re losing money or brand position due to poor performance. This modeling and analytics will determine your business plan’s driving issues and will quantify losses or potential growth opportunities. All analytics will be actionable, quantifiable, and measurable. A robust platform can be built to track the day-to-day internal metrics tied to customer satisfaction and the financial impact on business operations. Combining customer and employee feedback data with monitoring data, internal metrics data and financial data will change your company forever.
Putting theory into practice
Imagine you want to reduce the wait time on the phone for your customers because you believe they’re waiting too long and are dissatisfied with their experience. If your company had a robust customer-driven service platform in place you would be able to analyze your data something like this:
In the boardroom, the question would be asked, “Who wants to invest $650,000 to make $3.2 million?” The answer would be clear. Think about how this debate plays out in your company over the same issue or other issues such as: What is the cost of lower customer service from an offshore center vs. and onshore center? What is the right wait time for a phone call? What effect is your interactive voice response system having on customer satisfaction?
With a customer-driven service platform in place—along with the right partner—these subjects and more can be debated accurately and with a clear picture of the connection between customer metrics and financial results.