The customer data you collect will be used to help you make predictions and decisions to assist you in furthering your business goals. In order to implement these business decisions and strategies successfully, you need to have systems in place so you’re ensuring data quality and accuracy.
Ensuring data quality and accuracy is key to creating and implementing data-driven business decisions.
Unreliable or poor-quality data can lead to impractical, poorly developed sales, marketing, and customer service strategies. These ill-conceived strategies can have detrimental consequences for your business.
While low-quality data can potentially wreak havoc on your business, high-quality customer data can do wonders for multiple areas of your business.
Impact on sales
Quality customer data can help your business identify prime sales opportunities through trends in your data reports. You can then focus your sales efforts on the most profitable opportunities and allocate your efforts toward business actions that will bring the most reward to your business.
Additionally, ensuring data quality and accuracy can help you identify customer shopping behaviors and popular products or services. With this information, you can better develop new products and services that meet your customers’ wants and needs.
Impact on marketing
Your marketing efforts are essential to attracting new customers and clients. With the help of quality customer data, you can develop and launch targeted marketing campaigns that are effective in reaching your ideal customers. Additionally, personalized marketing campaigns can result in better customer conversion rates, improving your campaign’s return on investment (ROI).
Impact on customer service
When you’ve got high-quality customer data on your side, you can consistently deliver excellent service to your customers.
Timely data related to customers’ buying behaviors, interests, and preferred methods of contact allows you to assist them in the best way possible, provide personalized shopping experiences, and ensure every interaction with your business is a positive one.
Characteristics of quality data
There are four key indicators of quality data to look out for when ensuring data quality and accuracy:
Timeliness: Outdated data can lead to inaccurate or false predictions for sales and industry trends. Customer data should always be up-to-date and timely.
Accuracy: Quality customer data should be error-free to ensure accurate forecasting for sales, industry, and customer behavior trends.
Reliability: Quality customer data is reliable data you can trust. Your customer data should always come from sources you know, trust, and can ensure are reliable.
Consistency: The data you collect should be consistent, meaning it shouldn’t contradict other timely data you’ve collected, regardless of source.
How to ensure data quality and accuracy with your CRM
Ensuring your CRM contains quality data is key in customer data collection. Below are three processes you can employ with your CRM today to ensure your customer data is timely, accurate, reliable, and consistent.
One way to ensure data quality and accuracy within your CRM is through data validation. Data validation is the process of reviewing customer data to confirm that it meets the standards and rules set forth by your business and industry.
Data validation is an important step in the customer data collection process because it helps provide data accuracy and clarity. This process allows you to avoid any errors in your data and can help your teams better interpret the information.
CRM data cleaning
CRM data cleaning, also known as data scrubbing or cleansing, is the process of modifying or removing customer data that is:
Data cleaning is another invaluable step in the customer data collection process because it ensures data in your CRM is accurate, consistent, and trustworthy.
Data governance is the process of setting up internal standards and policies related to data collection and storage. These standards set forth by your business help “govern” how your customer data is collected, stored, analyzed, and deleted.
Essentially, it’s a set of rules you create for how your team manages the data you gather in your CRM.
4 pillars of data governance
There are a lot of different answers out there when it comes to nailing down the four pillars of data governance — it’s a concept lots of people share, but everyone has their own ideas about what those four pillars are.
On this page, we’re giving you our take on the four pillars we think are most important:
Data quality: Your data should be high-quality, reliable information.
Data accuracy: Your data shouldn’t have any errors and should always be timely and accurate.
Data management: Your data should always be handled with care, meaning it should be properly stored to avoid the risk of data breaches. Not to mention, it should be organized so it’s easy to navigate.
Data usage: You should always use the customer data you collect ethically and efficiently.
How can a CRM help?
When you invest in a CRM system like Nutshell, you’ll gain access to customer data collection and management tools like automation features and in-depth reporting. With Nutshell’s help, ensuring data quality and accuracy is a breeze. Not to mention, you can easily comb through data and weed out any low-quality information to make room for high-quality data. Learn more about how Nutshell’s CRM can help you collect and store quality data that’s accurate and reliable today by starting a free trial of our all-in-one CRM.