The Indispensable Role of Accurate Data


The Indispensable Role of Accurate Data

In an era characterized by rapid digital transformation and staffing shortages, the importance of data entry and accuracy has become a central pillar in customer experience (CX), employee experience (EX), compliance, cost management, and productivity enhancement.

A more accurate data set helps businesses gain deep customer insights, streamline communication, and create personalized experiences, enhancing customer satisfaction and loyalty.

Similarly, for employees, precise data enables informed decision-making, boosts their productivity, reduces time spent fixing errors, and fosters a more streamlined and effective work environment.

At the same time, accurate data is critical to compliance and cost management efforts. Misinformation or inaccurate data can lead to non-compliance with regulations, inviting fines and damaging a company’s reputation.

In other words, data accuracy is not just a measure of operational efficiency but a determinant of overall business health and future success. This is critical for today’s contact centers globally.

The Data Dilemma

Organizations of all sizes recognize data’s vital role in driving growth and maintaining their competitive edge, especially in all interactions that occur in the company’s customer-facing contact centers.

For instance, a 2022 study found that 80% of business leaders say that data is essential to effective decision-making at their company. And 73% percent say it helps reduce uncertainty and enables more accurate decisions in business conversations.

However, a meaningful gap exists between companies’ sentiments about data and real-world implementation. According to the same Salesforce study, two-thirds of businesses are not using data to make pricing decisions that align with shifting economic conditions, like inflation.

…data accuracy is not just a measure of operational efficiency but a determinant of overall business health and future success.

Similarly, less than one-third of companies use data to inform their strategy when launching in new markets. Meanwhile, 79% do not use data to inform their organizations’ diversity and inclusion policies. And just 17% of business leaders are using data to help inform their climate targets.

Finally, some companies don’t know what to do with all the firehose of information coming their way. 41% percent of business leaders told the Salesforce study researchers that a “lack of understanding of data because it is too complex” is a major challenge to data-driven decision-making.

Within contact centers and within other areas of business, many are just using bad data. According to the Harvard Business Review (HBR), poor quality data can significantly impair decision-making within organizations.

When data is mislabeled, missing, or incorrect, it presents a skewed version of reality, resulting in decisions that may not align with the actual business environment. If decision-makers rely on inaccurate data, they may make strategic moves based on false premises, leading to misguided strategies, inefficiencies, or missed opportunities.

Furthermore, bad data often leads to conflicting reports or analyses, eroding trust in the information and, by extension, the decisions based on it. This lack of trust may cause decision-makers to think they are making data-driven decisions when they are actually relying on guesswork when coming to conclusions.

Within the contact center, one prime example of how data quality impacts the CX – and business reputation – is communication between the brand and those who support, buy, rely on, or engage with it.

If a contact center does not have accurate information for customers, opportunities to facilitate sales conversions are missed. As are taking preventative measures to ensure issues are addressed before they arise, or even servicing a customer who is processing a complaint. As a result, inaccurate data causes companies to lose the ability to consistently build customer trust and can negatively impact it instead.

The Cost of Bad Data

Bad data comes with significant financial and opportunity costs. In a staggering IBM report cited by the HBR on the price of bad data, that company estimated that bad data costs the U.S. more than $3.1 trillion annually, the functional equivalent of removing Apple from the economy.

In reality, the quantifiable costs of bad data are difficult to calculate because the costs are spread out between decision-makers, managers, employees, and everyone else.

Bad data costs time, money, and opportunity, with consequences unique to every organization. It can compromise logistical capacity, brand reputation, and efficiency outcomes.

Within the contact centers and customer profiles of retailers, for example, bad address data is responsible for at least 8% of domestic first-time deliveries failing to reach their destination, as reported in Chain Store Age. Costing retailers an average of $17.20 per order.

Even if failed deliveries were the couriers’ fault, the majority of consumers still expect the retailers to resolve the issues, making dirty data very costly.

A great rule for businesses to use when assessing the impact of dirty data is the 1-10-100 rule. This looks at the increasing amount that poor data has on your business the longer you leave it.

  • In the first phase, $1 relates to the amount it costs to verify at the point of capture and is the quickest, cheapest, and most effective way of capturing accurate data.
  • In the second phase, $10 represents how much businesses will pay the longer they leave it.
  • $100 is the figure used to represent the amount of money a business will spend if they make no effort to clean their data.

Data doesn’t have to be perfect. Even reducing error rates by 50% can make a meaningful bottom-line difference, increasing productivity, employee experience, and customer satisfaction.

In one industry example of a major airline and their contact center, the company wanted to deliver a fast and easy online booking flow for customers while reducing incorrect address entries and payment failures. They had an issue with reduced functionality in their booking flow due to errors and friction when customers input their addresses.

CX considerations drove the need to address this issue; errors in address data led to friction and halted page advancement, interrupting the booking flow.

Bad data costs time, money, and opportunity, with consequences unique to every organization.

In response, the airline integrated a real-time address verification system into its online booking portal, automatically correcting any inaccurate customer data at the point of entry.

The verification system helps prevent incorrect or incomplete customer information from entering the airline’s databases. This reduces the risk of miscommunication or missed flight updates due to incorrect contact details, ensuring customers always receive crucial booking information.

The system also includes geocoding functionalities, which provide the precise latitude and longitude for every address entered, helping the airline analyze geographical trends and optimize routes or marketing campaigns accordingly.

While bad data is demonstrably bad for organizations, good data can have far-reaching repercussions, improving performance among a variety of KPIs.

Good Data Positively Impacts Results

Clean, accurate, and properly structured data is a catalyst for organizational growth and improvement, in the contact center and beyond.

In the evolving eCommerce landscape, there’s a growing trend of integrating user experience with financial and fraud experiences.

This intersection forms a pivotal part of the overall CX. Big-name companies across various industries are adopting innovative financial technologies and fraud prevention tools, effectively reducing friction and fraud in the customer journey.

These strategies cultivate seamless, secure online experiences that meet and exceed customer expectations. The modern consumer anticipates this consistency across all interaction channels, creating a universal standard for user experiences irrespective of industry.

A critical component of data quality is ensuring it can be seamlessly integrated across various systems…

High-quality, well-structured data plays a crucial role in this integrated approach. Real-time address verification, for one, streamlines data entry processes, elevates CX, and optimizes data quality.

Whether customers are engaging with real-time contact center agents or accessing information online, the experience has to be consistently streamlined, driven by accurate data processes: or the bottom line will suffer.

These strategies harmonize differences in data formats and standards, bolstering the integration and matching of data across numerous systems, such as billing, CRM, and fraud prevention systems. The ripple effect of improved data quality extends to enhance data analysis, fraud detection models, and various other business operations.

In the digital-first era, delivering a frictionless and secure user experience backed by reliable data can significantly determine a business’s success.

How to Get Better Information in the Hands of Contact Center Agents

Improving data quality is imperative to improving bottom-line performance and overall business opportunities. It requires a concerted, company-wide effort that includes the following.

  • Emphasizing data accuracy at the point of entry in the contact center or in customer-completed forms. It’s crucial to ensure data is captured accurately from the start. Tools like type-ahead global address verification can simplify address entry and enhance the overall CX, all while capturing accurate data for your back-end systems.
  • Integrating systems. A critical component of data quality is ensuring it can be seamlessly integrated across various systems, such as onboarding, payments, CRM, and fraud detection platforms. Companies can improve their data integration and matching processes by resolving differences in data formats and varying standards, starting in the contact center.
  • Performing regular data audits. Regularly checking data for accuracy and consistency is crucial. A data audit can help identify and correct errors, outdated information, and inconsistencies. This process should be part of an ongoing data quality management strategy throughout companies and within contact center processes.
  • Learning from the eCommerce industry. Companies can take a page from the eCommerce industry’s playbook. ECommerce companies have mastered the art of creating frictionless experiences, and a big part of this is the quality of the data they collect and use. And, how to leverage well organized data to optimize how they communicate with customers.

These strategies can help business leaders and their teams collect, aggregate, and understand their company and customer data more effectively.

Unraveling the Data Dilemma

For modern enterprises, the value of accurate data cannot be understated, given its profound influence on customer and employee experiences, compliance, cost management, and productivity.

However, a concerning disparity exists between understanding data’s importance and its practical application in strategic decisions. Poor data quality incurs substantial costs, impairs decision-making, and results in missed opportunities: challenges businesses can’t afford to overlook or ignore.

On the other hand, clean, accurate data can stimulate organizational growth and significantly improve performance indicators. Businesses can enhance their data quality by adopting strategies such as data verification at the point of entry, regular data audits, and systematic data integration.

Embracing the power of data in practical applications and ensuring its accuracy is no longer optional. It’s a necessity for businesses seeking to thrive in the digital era. Starting in the contact center.

Matthew Furneaux

Matthew Furneaux is a location technology veteran and retail and eCommerce expert with over 20 years of experience in helping global businesses reach their customers globally. As director of location intelligence at Loqate, a GBG company, Furneaux is responsible for strategy and innovation and has worked with leading brands.