In the past few years, big data has turned into the hype. Companies collect tons of information trying to make sense of it. Their effort often pays off as research found that businesses leveraging big data increase profit by 8-10%. Data analytics also improves business efficiencies by 17%, speeds up innovation cycles by 25%, and produces other measurable results.

What these companies don’t usually expect is that managing big data is a challenge. Without proper data hygiene and a data cleansing strategy, information becomes outdated. The lack of validation and cleansing also results in dirty data. Apart from being useless, such information can lead you astray. You will have problems reaching out to customers, use unreliable statistics for research, and make wrong business decisions.

To prevent the negative impact of dirty data, businesses need a data cleansing strategy. Regular CRM data cleansing and standardization rules can help keep records in order. This will make the database more reliable and up-to-date.

For more data hygiene best practices, read the next section of our post.

What Is Data Hygiene?

Data hygiene is all processes used by an organization to detect, correct, or remove inaccurate records. By “inaccurate records,” we mean outdated, unformatted, and misleading data entries that don’t provide valid information.

To make data hygiene practices truly efficient, most companies adopt a cleansing strategy. This strategy includes several tried-and-tested techniques to verify the information and improve the quality of data. The methods used to support data hygiene vary on a case-by-case basis.

For example, if a company collects data through automated record-keeping, CRM database cleansing will also be automated. They will use automated customer address verification, email address checks, formatting, and data enrichment. On the other hand, when a business manages customer data manually, its data cleansing strategy will be based on tools that support manual data checks. They can prefer to verify data entry one by one or in batches instead of automating these procedures. Although manual checks are much slower than automated, many businesses still have them.

Why Is a Data Cleansing Strategy Important?

Imagine you have a database with thousands of contacts, but you are unsure whether they are reliable. You take the risk and use this data to segment your target audience. Now, you have a list of prospects that are the most likely to purchase your product. After investing money in a marketing automation campaign and your sales reps’ hard work, it turns out that a large portion of the selected customers ignores your offer. You lose a lot of money and precious time.

Why does it happen? The data you rely on may be outdated and inaccurate. The lack of CRM database cleansing, standardization, and formatting harms the accuracy of customer research. You choose the wrong target segment. The low quality of data also prevents you from reaching the customers.

Summing up, here’s a list of top reasons to do CRM database cleansing:

• A data cleansing strategy saves you time and budget.
• A data cleansing strategy reduces churn rates.
• A data cleansing strategy improves the accuracy of customer communications.
• A data cleansing strategy makes your marketing and sales teams more effective.
• A data cleansing strategy is essential for further digital transformation and automation.
  

Moreover, CRM database cleansing makes you confident in the business decisions you make. You have verified information to rely on. Besides, thanks to data cleansing and standardization, you quickly adopt new technology. After you checked and structured the information, you can instantly upload it to any platform or application for further use.

5 Data Hygiene Best Practices: How to Keep Your Customer Data Healthy and Up-To-Date

These tips will be suitable for most businesses that handle large volumes of data. The choice of data cleaning tools is up to you, but we recommend implementing some standard data hygiene practices.

#1. Audit your existing data and data cleansing strategy (if you have it)

Before taking any steps to run CRM database cleansing, you need to evaluate your data’s current state. According to IBM, 27% of business leaders don’t know how much of the information they possess is accurate. Don’t become one of them.

To run an audit, you have to:

• Evaluate all in-house systems that use customer information to learn what data categories are critical. You are quite likely to discover that not all data entries are necessary for your business.
• Find out what data types you collect through web forms, subscription forms, etc. Some of the information you store may just overload your systems resulting in dirty data.
• Check for structural database errors (e.g., insufficient validation, wrong table structure, misconfigured integration, incorrect formatting or encoding).

#2. Prioritize data to know what to focus on

Once you finish with the audit, you should already know which data sets are the most important, and which don’t affect you much. Hence, it will be easy to prioritize them.

Start fixing the types of data that matter for revenue-generating activities, like the phone numbers, emails, or top accounts’ shipping addresses. This will allow you to avoid getting bogged down in CRM database cleansing and feel the benefits of data scrubbing right away.

#3. Create standardization and formatting rules

We recommend converting all monetary values, numbers, addresses, and other standard data types into a consistent format. You should also remove case sensitivity if it’s not critical. When you know what data entries are valid, it’s easier to run CRM database cleansing and instruct your employees on how to cleanse data.

Data format standardization will also enable you to write formatting rules for customers. Now, when they fill out personal and contact details, they will be more likely to share correct data.

#4. Add the missing data and remove duplicates

Filter your database to see what data values are missing and think about how to get these details. For example, data enrichment tools can help you find out additional information based on existing records (e.g., get an address from an email, learn gender based on name, link a profile to social media, etc.).

After enriching information, you should consolidate duplicate data by merging or deleting duplicates in the database. Thanks to this, your database won’t include confusing and unnecessary entries.

#5. Automated data recording and verification

CRM system cleansing is a continuous process. To run effective marketing campaigns, analyze your target audience, and perform other tasks where data freshness matters, you need the latest data. 

Therefore, it’s better to automate CRM database cleansing by integrating your system with data validation tools. The software will regularly check your data records and verify customer data as soon as people share it. For example, Inkit autocompletes and validates data in checkout forms. It’s 100% automated and smoothly integrates with CRMs and other third-party tools.

Inkit’s Verify for Data Hygiene Automation

Verify is Inkit’s tool designed for address verification and autocomplete. It enables e-commerce businesses and other businesses that collect customers’ addresses to validate the information.

Verify provides customers will address suggestions as they share data and automatically re-verifies addresses before order shipment. The businesses that use this tool benefit from automated CRM database cleansing and improved data hygiene.

Have any questions about using Inkit in your data cleansing strategy? Contact us for a talk or to get the demo.