For businesses across all industries, data is constantly growing. This, in particular, arrives from customers and lead generation. However, not all customer data is good or even handled appropriately. This builds up to a problem we refer to as bad customer data, and if left to rot, has serious consequences that could seriously harm your brand.
It might surprise you how much data out there is of poor quality. Statistics show around 71% of consumer data worldwide contains errors. These errors may account for inconsistent information, validity concerns, or even accuracy.
Inaccurate data is thought to affect at least 88% of companies. Might yours be part of this statistic?
While poor or dirty data will have an immense impact on your brand’s daily running, it can impact your customers, too. Let’s consider why insufficient data from customers is such a significant concern and how you can counter-act it.
What is Bad Data?
Bad customer data is that which is inaccurate, inappropriate, or even redundant. If the data you hold on your customers doesn’t accurately reflect even their simplest information, your brand runs the risk of damaging relationships.
Bad data, ultimately, revolves around poor record management. You are handling poor quality data if you fail to update your information regularly or you do not account for errors.
Poor data can arise for various reasons. Sometimes, you may simply be using inefficient tools or programs. At other times, you may be negligent with data without actually realizing it.
If the information you hold isn’t accurate or ‘clean’, you stand to disappoint anyone you do business with. As customer data is sometimes complex, it can be challenging to know how to manage it.
Of course, this problem travels a little deeper. Therefore, let’s consider the negative impact of poor record management.
how does data impact branding?
While it’s easy to assume that big brands can weather any storm, even small data problems can cause major headaches, it can affect loyalty, increase costs and most worryingly lose customers. We explain exactly how bad data impacts brands below.
Here are a few key areas relevant to the broader impact of bad data.
It Affects Loyalty
Securing any customer loyalty takes a lot of time and effort. However, the way you handle and manage their data could send shockwaves quicker than you may expect.
Customer loyalty revolves around trust. To build this trust, brands need to reassure buyers that they will offer a consistent, reliable service.
Even small data errors, if widespread enough, can give off a poor impression. What if you fail to deliver to correct addresses, process payments, or follow up on queries? All of these circumstances can arise through poor data management.
Loyalty depends on ongoing confidence in your brand. To maintain this, you need to demonstrate you care about consistent data quality. Even if your data mismanagement is unintentional, damage can grow out of control very quickly.
It Increases Costs
In the US alone, the economy wastes $3.1 trillion on dirty data and resolving issues.
That total comprises costs to resolve customer queries, bounce back from data loss, and more. Besides, should poor data management result in privacy breaches, you may face increasing legal costs.
Of course, we must also come back to the idea of loyalty. Failure to assure customers you care about their data may result in revenue loss. For smaller businesses, these costs can be devastating.
It Breaks Down Connections and Goodwill
Customer loyalty is one aspect, while customer goodwill is a slightly different animal. Goodwill and positive awareness of a brand can generate leads for years to come.
Should poor data handling go public, it can impact heavily on broader perception. Even those people who do not buy directly from your brand have an impact on your success. Statistics show that 21% of companies handling bad data experience a reputation downturn.
For example, should your handling of a data crisis resound poorly with the public, you restrict potential revenue. While more prominent brands continue to trade on mass awareness, it is still ‘word of mouth’ that rules overall.
A smaller business that struggles to bounce back from data mishandling may not have the resources to survive. This has long-ranging impacts, should they wish to grow for years to come.
It Reduces Morale
Poor data management also affects employees. Staff who are left to “pick up the pieces” may need to spend a lot of time cleaning up bad data.
Also, poor quality data management systems are frustrating to use. Inefficient data siloes pile up and can be challenging to navigate.
This not only adds to employee frustration but may cause conflict between customers and employees. Should your team have the best tools available to manage and monitor customer data, there is less impact on morale.
Employees with low morale are less likely to perform well. This impacts the efficiency, productivity and overall performance of your business. Surveys already indicate 61% of employees are burning out. It’s essential to avoid adding to the problem.
It Loses Businesses Customers
Bad or dirty data can lose even big brands plenty of custom. This is as a result of some of the points discussed above. Impacts on loyalty and confidence may lead customers to look elsewhere.
This may be the case if they directly experience poor quality care. In industries such as healthcare, for example, bad data could result in long waiting times. It may even result in improper medication or treatment.
Retaining custom is just as important as sourcing leads. If you do not adequately manage existing client data, you may experience an exodus.
It Results in Poor Lead Generation
Beyond brand appeal, lead generation directly suffers as a result of dirty data. Frighteningly, around 40% of generated leads from only a few years ago ran on bad data.
The effect of bad data on sales is pretty simple to measure. Inaccurate or inappropriate information might not connect you to the right people. This could upset non-leads who don’t wish to hear from you.
Beyond this, inaccurate data for a lead generation means – ultimately – you can’t convert. A clean database of potential customer information allows you to build an outreach program that works confidently.
The Challenges Involved in Data Collection and Maintenance
There are various challenges brand managers face when it comes to collecting data. However, many might not appreciate the potential problems ahead when it comes to maintenance.
Ultimately, human error is a significant problem likely to affect either side of the chain. Even before leads collect and convert, if data is inaccurate, the revenue potential is minimal.
Human error is responsible for more than 60% of dirty data. Without the right tools to help manage and maintain good quality data, the wrong kind is likely to continue piling up.
Even talented data analysts and experts may find that, over time, data siloes are challenging to maintain. Data ‘lake’ models can lead information to muddle, duplicate, and expire. While it may seem easy to let the data pile up in this way, it gets harder and harder to manage over time.
What’s more, data is decaying by 30% each year. It’s getting outdated and stale. The need to keep on top of this issue is growing ever more important.
Perhaps the biggest problem facing businesses regarding data management is influx. As you may imagine, as the population increases, so does data. Data increases at roughly STATISTIC HERE. Even when splitting into different industries and spheres, this still amounts to an incredible mountain of information.
That data pile is never going away. The consequences of poor data management, therefore, are that effectively useless records keep adding up. Businesses must be willing to adapt to new data models if they wish to clean things up! Thankfully, collecting and maintaining customer data is getting easier.
How WinPure Can Help
WinPure offers professional data cleansing and matching software to support businesses across many different industries. WinPure aims to help clean, correct, standardize and maintain your data. No mountain or silo of data is too large nor too complex.
Data cleansing software is ideal for breaking down existing lakes and siloes. WinPure can help to remove duplicate data, rearrange mailing lists, and re-organize databases. The suite can also help you to maintain spreadsheets and even complex CRM suites.
Data scientists spend more than half of their uptime correcting mistakes. With WinPure, you are in a position to streamline this process. What’s more, you can effectively automate clean data processes for years to come.
Therefore, even as data grows and builds, you can maintain it in a concise, understandable series of databases.
It’s important to remember it’s never too late to start managing your customer data more efficiently. You have responsibilities to ensure your brand caters to customer needs. That certainly, applies to the data you hold and use regularly.
To find out more about how WinPure can help you bounce back from bad customer data, consider a free trial. Download our suite for free and sample a cleaner, more efficient data capture and organization standard today.