At present, the market is going through a major shift with the advent of AI-driven technology and its wider applications. Customers are making decisions faster than ever. Research revealed that more than 61% of customers have accepted that their priorities are constantly changing based on the current happenings. Thus, it's high time for the brand to maintain a higher quality of data to understand its customer mindset. Working with high-quality data helps you make informed decisions faster.
Besides that, the growing number of communication channels has made everything even more complex. Keeping things up-to-date can bring the desired results and cut down your operational costs as well. All you need is to invest in the right data management process and tools to inculcate revenue growth while bringing down the cost factors.
Understand the importance of data quality
Before you begin to improve data quality, you have to understand what data quality truly means. Understanding data quality parameters along with the data attributes can help maintain the data quality. Essentially, the quality of the data depends on its accuracy, completeness, and consistency. Quality data helps businesses to meet their intended purpose and bring the desired growth to the process. If not, the data quality measures are maintained well, it can lead to incorrect conclusions, skewed insights, which can put the business positioned into negative consequences.
When you include the data quality insights into your operations, you cannot expect the following things in your database at all
To make your data work, you have to improve its quality. Your organization can make better decisions when working with better-quality data. Do not forget that you can increase the reliability of data when you move ahead with data quality enhancement measures.
The cost of poor data quality
The biggest risk you can make when you consider working with bad quality data. Every year, businesses face losses in millions because of poor records and bad decisions. Due to constant changes in business procedures and quick changes in customers' choices (as discussed before), data becomes obsolete quickly. If the data is not getting updated with an accurate cleansing methodology, it can negatively affect the business procedure.
Let's now assume what impacts you can face when you work with poor data.
Increase customer acquisition costs
If we look from scratch, a business puts a lot of hard effort into acquiring customer data. That too, from different sources. It involves money and other vital resources of the organization. When the data quality decreases, it automatically increases customer acquisition costs.
Spend marketing in the wrong direction
Imagine you have a fixed budget that you can spend on marketing expenses. But unfortunately, you spend all your budget on targeting the wrong audience. Is that feasible for you? Of course, it's not. Working with poor quality data only screw your marktring spending and let it not shine through your marketing endevours.
Higher risks of reputation loss
Organizations stand tall in the industry because of their widespread reputation. But when you started working with bad data, the risk of reputation loss increases significantly. Because you would never know any cracks in your data. Many businesses have failed before (diminishing age-old reputations) as they used bad data in their business operations.
Chances of legal issues increase
When you use poor data to reach your audience, you can face legal claims. Reaching out to customers with unsolicited messages can cause you to incur excessive penalties. On top of that, the rules and regulations of GDPR also make the process more complex overall. Various case reports are there where companies used poor records and got legal claims because of that.
Strategies to enhance data quality
Eliminating poor records with quality data updates is the thing what you deserve for better business growth. There are some strategies you can try here to enhance the scope of your data quality standard and promote business growth.
✢ The requirement for clean and quality data should be defined clearly and with well-defined measures. First, you need to strategize the data collection process. The procedure to collect quality data should be in one direction. Therefore, everyone in your team can follow it well.
✢ The procedure to collect data should be consistent and accurate. Plus, a validation method should be there to eliminate errors within the process.
✢ Manage all your data in the centralized database management system for better results. It helps you stay connected with all the data sources.
✢ Provide a complete training session to your staff members to get the best out of the data processing. So that everyone on your team can understand the gravity of maintaining data quality.
Make data your strength with the data quality experts
Every business is different, so are their competitive strategies. Businesses should follow their own competitive path while taking the best quality data into the process. While putting the best-quality data into the process, you can expect better outcomes (per se, definite outcomes). That too, without spending much on data management. All you need here is the right experts and their expertise to grow.
If you feel that your current data management process is not sufficient to produce quality data, you need a consultation with a data expert on this matter. With their help, you can achieve better business agility and boost your ability to grow your business further.
