"By introducing data quality initiatives, some companies have added millions of dollars to their bottom line as they gain benefits such as increased sales, lower distribution costs and better compliance" - Andreas Bitterer, Gartner Research vice president.
Big data and business analytics forecast to reach more than $210 Billion dollars in revenue through 2020. But what it means for quality data?
Whether we are aware of it or not, data regulates many important decisions in our lives. Think of the way we communicate, the tools we use and the way we ran our company.
Data is everywhere around us and has a tangible impact on our daily lives.
But what happens in a company when decisions are based on bad data? What are the impacts? 🤔
The consequences of BAD data
Nowadays, customers and more specifically, the data attached to them are the basis of the success of the different departments of a company. Although most managers, marketers, analysts and sales are aware of this fact, only 3% of all business data meets basic quality standards.
In the United States alone, the annual cost of poor data quality resulted in a $3.1 billion losses. It represents an alarming amount, especially considering the fact that we all routinely process data.
Some non-financial impacts that are often overlooked include:
- Incorrect strategic decisions made as a result of poor data analysis
- Loss of credibility for the company
- Productivity time lost
- And many others
If, from the outset, customer information is erroneous, how are your marketers going to send communications to their contacts? How will your salespeople succeed in getting appointments with their prospects? How will your managers achieve their goals? How will your after-sales service agents provide quality support?
More than ever, the key to success lies with your customer information. What is "data quality"?
Before you begin to master data quality, it is important to understand what it is.
According to Gartner, data quality is determined using several benchmarks.
These include:
- Existence: does the company possess the data?
- Validity: which data is still valid and which is not?
- Coherence: Is the same data is stored in different places? Is it the same?
- Integrity: are the data elements and data sets accurate?
- Precision: does the data accurately describe the properties of the object?
- Relevance: is the data appropriate or not?
That's a lot of information to process and organize, isn’t it?
Related : What is contact data quality management?
The benefits of QUALITY data
Good data help achieve much more than just better revenues and savings in the short, medium and even long term. The ability to reach customers and prospects is essential to any business strategy.
Customer data is used across the entire organization, from marketing, sales to delivery and customer success.
With more reliable data comes greater credibility and better decision-making. In addition, reports grow more accurate and customers benefit from tailored and targeted messaging.
Some inaccurate entries do not constitute a big problem, but as your business evolves, more and more misinformation might create major trouble. Costs will increase and efficiency will decrease significantly.
Related : 6 great benefits from quality contact data
How to improve data quality?
Most companies attribute data quality problems to human errors; but that’s not all there is to it. A lack of knowledge, ownership, processes and technologies also hinders data quality.
For a long time, the department responsible for sorting customer data was IT. In recent years, however, data quality responsibility has also shifted to the Chief Technology Officer (CTO). New positions have also emerged such as the Chief Data Officer (CDO) or Data Analysts in order to monitor and manage valuable information. Marketing managers are also starting to get a good understanding of the data since their role in creating awareness, converting and nurturing has evolved.
If you feel that data in your company is bad or incomplete, here are some steps to take:
Understand your database
If you want to implement a data quality strategy, your company must first understand the errors made in the database. It is important to identify what are the common mistakes that occur in your company. Is there any information missing? Incomplete? Sometimes it's a small mistake that is often repeated; some put an area code, others not, or some will forget the apartment number for example. To help you, here is the list of the most common errors:
- Missing data: empty fields
- Incorrect or inaccurate data: Information that has not been entered correctly
- Inappropriate data: data entered in the wrong field
- Non-compliant data: data that has not been standardized according to system standards
- Duplicate data: An account or contact that holds more than one record in the database
- Wrong data entry: typos, transpositions and spelling variations
Once the errors are identified, training your employees is a good way to make sure everyone understands how your system works, especially if you are using a centralized information system. A small training for the new ones and a memory refresh for the oldest will be most helpful!
Clean existing data
Once your company has identified common data errors, these must be corrected. Depending on the size of your company, you can choose someone internally to process all of your information manually or if your resources do not have the time to solve this problem, there are several companies that offer data cleaning solutions.
Remember, the longer you wait to complete this step, the longer it will take to finish the job.
Remove duplicates
If your information comes from multiple sources, it is almost certain that your system contains multiple duplicate contacts. These must therefore also be cleaned.
This seemingly unimportant situation diminishes your company's ability to capture a unique view of each customer, lead and prospect, preventing you from effectively communicating with them.
Improve and update the data
Once your database is all cleaned up, the most important thing is to keep it that way. Information which will be added to it must be accurate. To do this, everyone in the company must work together. Several data capturing tools exist to help you in your task in order to maintain impeccable customer information.
The value of your data is the foundation of your success. Every piece of information should be consistent and relevant if you want to increase your revenue. In addition to affecting revenue, erroneous customer data waste the time of employees, have a negative impact on decision-making, increase costs and complicate the implementation of strategies.
Regardless of your business area, if you want to increase your revenue, reduce cost, and improve customer acquisition and retention, you need to invest in good quality data. One of your best assets!
In Summary, cleaning up your existing information and standardizing it will be a big step forward. It is important to keep your data in a centralized system and keep it up to date. Thus, your different departments will have access to quality contact information which will help your business to grow.
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