Original Publication: Customer Management Insight - September 2008
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It’s common knowledge that it is often cheaper to keep a customer than to gain a new one. They’re most important asset to any business. We guard their identities by protecting our customer lists. Often, however, we don’t fully understand who they are. This is not because the customer is trying to hide from the business owner. Many customers happily respond to surveys, provide feedback, fill in forms, and provide information to the company representatives. They submit personal facts through the Web, via email, and on the phone. So why is it that all of these efforts by the customer result in many business owners asking, “Who are you?”
The primary factor that impedes our view of the customer — making them invisible to us — is the quality of the customer information gleaned from all the collected data.
This lack of visibility or recognition has not gone unnoticed by the customer. Many get frustrated when they call an agent for assistance, only to spend an additional ten minutes providing their name and address ... AGAIN. This is just one impact of poor information quality.
This issue also can affect the ability of the business to provide additional service to the customer. Not knowing what products or services your customer has recently purchased makes it difficult to upsell new offers. Even worse, it can create embarrassing situations. Poor information quality has resulted in ten-year-old boys being offered new credit cards with $10,000 limits, much to the chagrin of their parents.
There are three simple steps that can be taken to improve information quality and bring customers back into focus. These steps span the information development process and address issues within the information systems architecture and the business. Such basic “house cleaning” will put you on the path to better information quality and happier customers.
Step 1: Customer Data — The Raw Material
You cannot have a good-quality product without good-quality raw material. The customer data set must be complete, accurate, and valid in order to provide a solid basis for good information quality. The responsibility for this effort rests in the hands of the business owners as well as the information systems team.
The focus of the data gathering stage is quality and accuracy. Here the phrase “garbage in, garbage out” (GIGO) all too apropos: The quality of the data coming out of the database will directly reflect the quality of the data put in. Thus the agents, customer service reps, and web designers have a significant impact on the quality of your customer data. It is essential to work with these key data interface points to ensure that the quality of the data inputs will support the rest of the information process.
In addressing data quality at input, the quickest and most effective approach is a process evaluation. The process steps should be logical, and the data captured should be part of the process, not an addition to the existing steps. This flow not only simplifies the efforts of the agents and customer service representatives, it also ensures that reports and metrics built from the data can track and influence the process.
Once the process evaluation is complete, the system can be modified to support and enforce proper data collection within the process. Several steps can be taken to enforce process compliance, including auto-dating key fields, pull-down menus with selections, radial buttons, and required field entries. These are not foolproof methods, however, so process review, training and enforcement are key pieces of the data quality effort. Ensuring that customer data is entered into the system during the process is one major step in improving your overall view of the customer.
Step 2: The Reports — First Stage
The biggest challenge for any business manager is to see the customer as the customer expects to be seen. This requires reports based on the “customer perspective,” which necessitates an alignment of reporting business rules with the customer experience. One of the symptoms of poorly aligned metrics is having high internal performance metrics that are at odds with declining customer satisfaction rates and increasing customer turn over. This misalignment creates an invisible customer.
Many managers today have a standard set of reports they have used for years. Their experience tells them that moving these metrics in the desired direction should improve the customer’s level of satisfaction. This perception is not necessarily wrong, but there should be some validation and alignment of the metrics to ensure they meet the business need and customer perspective. It may be time to replace these older “windows on the business,” and develop a point of view that better aligns with the customer.
This common reporting disconnect is not the only indication of reporting misalignment. Another sign is the “data wars” that result from multiple business owners attempting to find the “right metric” to improve customer satisfaction. Such internal conflicts can lead to a downward spiral of new tools and new reports. It is important to understand these symptoms for what they are. In cases where this disconnect is persistent, it is most likely time to hit the reset button.
One essential step a business should take is to correlate the existing reports with the business’s customer strategy. This will highlight the gaps in the reporting structure, and may well identify needed changes in other metrics and reports. Keep in mind that quality and value are in the eyes of the consumer — your customer — and your efforts should be aligned with their perception. This will go a long way toward getting a clear view of your customer.
Step 3: The Information — The Refined Product
No single report will provide the insight needed to make decisions regarding your customer. You can reduce call handle times to near zero, yet still find that customers are angrily leaving your business because they cannot get service. You can resolve all customer issues on the first contact, yet still create frustration for agents and customers. But combining these reports with other reports, such as customer satisfaction surveys or customer retention rates, can provide a more complete and accurate picture of what really meets the customer’s need. It is important to ensure that the right balance of reports is used to create a solid, valid picture of the customer. This requires an understanding of the business process as well as the technologies to be used, so don’t throw this over the wall to IT. To do so would create an IT picture of the customer, and that may not be the best view. Keeping the business objectives in mind is key in developing quality information and a clear view of the customer.
It is also important to understand the downstream impact of a change. Making corrections in a single performance factor without understanding the impact on other business processes can be a recipe for frustration. For example, if a cost reduction effort increases hold times, the customer will not be happy. If reductions in handle times result in the customer making multiple calls to get an issue resolved, you have once again fixed an internal problem but negatively impacted the customer. If efforts to upsell are directed toward a customer who is dissatisfied with their current service, you may be accelerating that customer’s departure.
The development of information should cover an entire process, not just one or two metrics. A review of each of the key performance indicators (KPIs) and how they impact the following process step will go a long way in completing an effective analysis. You may want to consider a metric tree that contains a few KPIs that cover an entire process (such as ticket age) and then sub-metrics that support the KPIs (such as hold time, handle time and first-call resolution). These types of analysis will provide a more complete picture of the customer’s interaction with your agents and centers.
It is also necessary to review the analytics to ensure they align with the current strategy and customer base. Outdated information is as undesirable as misaligned information. Make sure that the information provided by your analytics matches the current business strategy, not the one from last year. This will ensure you see your current customers, not an outdated photo of customers past. History is valuable, but it cannot change the future.
Maintaining Customer-Centric Momentum
Obtaining quality customer information is a cycle. Thus, it is important to get feedback from your customers to ensure you remain on track with your efforts. Your customers will change as time moves on, so it is important to change your efforts to stay aligned with their needs. Know your customers, and keep that relationship current to ensure a clear current picture.
There are two distinct efforts with regard to the customer. First, it is up to the business to create the customer. This is done through targeted marketing (information based), product development (information driven) and, sometimes, acquisition from competition (again, information driven). Second, once the organization has won the customer’s business, the challenge becomes building loyalty to keep the customer. The clear picture that only good-quality information can deliver will help you understand these critical customer aspects:
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Needs
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the minimum expectations, or the “table stakes.” If you do not have an understanding of the customer needs, they will not stay with you long, but will leave when they find a product or service with a better perceived value.
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Wants
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the things that will keep the customer coming back to you and your business.
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Application
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how the customer uses your product or service in their daily business or personal functions. If you do not understand how the customer uses your product or service, you will not be able to adjust your offering as the customer changes.
The issue of information quality must be resolved if we are to succeed. Failure to do so can result in increased customer dissatisfaction, and possibly defection. In contrast, improved customer information quality can reduce costs, increase revenue and help expand the business.
Three Steps to Customer Visibility — And Why So Many Call Centers Fail at Them
Good-quality information on the customer is gained through a three-step process. The first step in manufacturing an information product is to gather your raw materials. This is the customer data collected from the Web, the call centers and the surveys. Secondly, the data is consolidated into reports, which group the facts about the customer, providing a clearer view of how your business works with them. Finally, the reports are analyzed and compared, creating customer information and providing a basis for decisions.
Companies in general try to follow these steps, but gaps or errors in the process can lead to major quality issues with the data gathered. Poor customer information quality can arise from any of a number of sources. The issue could be within the data architecture, where key facts about the customer are corrupted due to some technology process. It may rest with the agents and operators that gather the key pieces of data from the customer and then hurry through the data entry process, creating errors within the data set. It could be in the reporting platform, where valid data sets are consolidated using invalid business rules. But no matter where the problem originates, the result is the same. The face of the customer becomes blurred behind the poor quality of the business information, and service suffers as a result.
The Invisible Customer — A Case of Poor Information Quality Hiding Customer Value
Issue: Significant data quality issues at data entry resulted in invisible customers for a help desk organization.
Impact: Several million dollars of potential revenue were going unrecognized due to missed opportunities for upselling, resale and system enhancement.
Solution: A proactive data quality initiative combined with weekly scorecards on data quality and ongoing review of data quality progress. Specific key dimensions within the data set were identified and targets for acceptable data quality levels were established. The scorecards were then reviewed with key managers and stakeholders to define and drive data quality improvements.
Result: The company identified nearly $11 million in potential revenue opportunities in the first quarter of implementation, enabling the help desk teams to proactively address customer needs and increase revenue from services offered.
