9 Critical Data Hygiene Practices Businesses Must Follow

There is a lot of buzz surrounding business listing data. When it is used to supplement client information, business listing data functions as a force multiplier, providing businesses with in-depth customer knowledge. But, unclean data is a commercial database’s fatal flaw. It damages the decisions based upon it and can negatively impact the company’s bottom line. 

Therefore, ensuring data hygiene has become a critical concern for listing providers. However, keeping up with business listing databases is more than a one-step or one-time process. It requires proactive efforts to monitor the data, validate it, and keep it updated.  The reason most organizations opt for data cleansing and enrichment services from trusted third-party outsourcing services providers. 

So, use these 9 tips to create a data cleaning strategy for your business. 

9 Top Data Hygiene Practices For Updated Database 

1. Execute an audit for business data 

Completing an audit before adopting a data hygiene strategy is critical. 

Your business may be in the practice of frequently gathering data from multiple sources. However, more is not necessarily better, as data overload without appropriate quality control can facilitate the spread of misleading information. So, begin by assessing your current database’s state to determine the accuracy of its data.

  • Evaluate all data to see what is useful and accurate.
  • Confirm that datasets apply to those who will use them. 
  • Examine whether data fields affect the people who use them for marketing communication.
  • Examine all the sources from which the data was collected so that multichannel sources can be pooled together in silos.

These steps are required to create an efficient information hygiene plan aware of the origins and the most current information. They also make it easier to maintain a listing database.

2. Establish metrics and monitoring systems for the data cleanliness of business listings.

Set specific criteria for the categories to be included and the overall architecture of your database. Establish KPIs for data quality in categories, including demographics, geography, behavior, and contact information. Make a detailed action plan to address:

Developing KPIs to preserve data will reveal the causes of your data integrity difficulties. It will also assist you in comprehending the data problems that damage your database.

3. Set guidelines for standardization and impose restrictions

Maintaining data cleanliness isn’t possible if you let irregular data enter your listings without being checked beforehand. Non-systematized data gives way to unreliable data. To assist with this, the database entries should be standardized. Also, standardization makes it easier to find and get rid of duplicates.

Thus, once you begin database scrubbing, make sure only systematized data is added. 

After communicating with your team, create a standard set of rules that must be applied throughout the database. 

  • Based on database requirements, change abbreviations into a lengthier format or vice versa. 
  • For consistency, convert all numerical, monetary, and other nominal values into a uniform format.
  • Use case sensitivity carefully.
  • Create range limitations to keep fields’ values from being nonsensical.
  • Mandate that input values fall inside a specific range.

These all guarantee consistency in the data entered. Additionally, it will stop erroneous information from being added to your listing database. As a result, you can have more faith in new data quality.

4. Verify the accuracy of data in your business listing 

Verify all of the facts in your business listing across several sources. You might find new leads and commercial opportunities by confirming recent data and supporting new client profiles.

Verification performed through various human and automated testing methods helps find irregularities, mistakes, or corrupted records.

You can use the verification criteria listed below for your database:

  • Cross-index verification: Compare data to reputable databases, delete material that doesn’t fit the most recent database, and identify untrustworthy data sources.
  • Verification of data type: Find inconsistencies in value representations. Re-check the numbers to see whether it matches another entry or falls within the range of values.
  • Range checking: Set predetermined numerical requirements for individual fields. An alert will be triggered if the supplied numerical number does not fall within the defined range.
  • Complicated data validation: This validation is required for various company listing databases. In these cases, tool-enabled verification aids in evaluating data based on predefined criteria.

You may ensure the accuracy of your data and take the data quality requirements inch closer to being met by following the actions indicated above.

5. Get rid of duplicate business data 

Duplicate or repetitive entries constitute a significant issue for businesses. 

Many companies, for example, use emails to differentiate between contact entities. On the other hand, customers frequently enter their personal and professional email addresses in different submission forms. As a result, two different yet identical recordings are created. 

Data collectors must take every measure to avoid multiple similar entries in their business databases. This is because duplicate records result in inaccurate reporting and prevent your clients from gaining a unified view of their customers. Furthermore, it gives your customers a bad experience and harms your brand’s reputation.

6. Append business listing data 

Your corporate database contains fields for first, middle, and last names, mailing addresses, and company addresses for each contact record. To establish best-in-class business strategies for sales, advertising, and customer support, data aggregators should add more fields to the records, such as contact number, yearly salary, profession, etc.

  • Utilize other databases to research relevant fields and other information.
  • Add additional data sections to help the company database become richer.
  • Employ software tools to clean and build the listing database

7. Automate business data cleaning

Human processes for data hygiene are ineffective, arduous, and expensive. Spending on methods or services that automatically clean up, upgrade, add, and de-duplicate records is time, effort, and money well spent. Mistakes are inherent in manual data entry, and human error is the primary source of erroneous data.

Moreover, an incorrect record can cost you a lead and thousands of dollars in future revenue that never materializes. Thus, it is preferable to either hire a large enough team of skilled data experts who can meet your requirements or outsource data cleansing services to an experienced company. Professional data cleansing service providers can search your databases for duplicate records. In addition, they analyze extensive databases and utilize computers to spot irregularities and aberrations resulting from human error.

8. Regularly update data 

Data degrades quickly. This can occur in several ways. For instance, companies combine and split, house addresses change, and contact numbers and mailing addresses change. Setting up a system to monitor such changes and constantly update data is critical for preventing data deterioration. Moreover, you may spare clients from chasing dead ends and poor marketing ROIs by updating data in real-time.

9. Break down the organizational silo 

Most companies have separate portals for their sales and marketing departments. Salespeople, for example, devote a significant amount of time to customer engagement, whereas marketing professionals devote significant time to campaign management programs. Consequently, these departments tend to communicate in their terminology and stick to their standards, best practices, and formats.

To ease such gaps between departments, all teams involved in updating client records must agree on data accuracy and criteria for entering and amending customer information (for instance, by mandating that clients’ records be analyzed and updated after two months).

Final Thought 

Data is dynamic and ever-changing. Even after cleaning, standardizing, and updating, it will deteriorate unless you keep maintaining it. As a result, most firms are concerned about data hygiene. Furthermore, as the number and variety of data collected grow dramatically, it will become more competent. So, if you plan to dump this responsibility on your in-house team at once, that plan will backfire on you. Not only will your enterprise data be at risk but also, your employee productivity will suffer. 

A simple solution to this problem is to get services from a data cleansing outsourcing company.

Data cleansing services have proven crucial to a company’s growth plan, scalability, adaptability, endurance, and longevity. Here is why:

  • Such providers are well-versed in the best data hygiene practices.
  • They have a team of data professionals with experience in handling large databases.
  • They invest in data management-specific tools and technologies that can be utilized to boost efficiency.
  • Outsourcing companies engage with clients from various industries, thus gaining a broader range of experience and expertise in database enrichment.

Hopefully, now you understand the critical appeal of data appending and the necessity for a third-party partnership when it comes to managing enterprise databases

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