Imagine data as the fuel propelling businesses forward. But here’s the catch: sometimes, this vital fuel is subpar, hampering the engine’s performance and overall business operations – from marketing and sales to profits and growth. Surprisingly, many businesses are aware that their data isn’t up to par, yet they don’t take action. It’s comparable to driving a car on low-quality fuel, which you know isn’t suitable for the engine.

Now, when faced with such a situation, what’s the logical step? Would you swap out the engine or refine the fuel? Clearly, the sensible approach is to purify the fuel. In a parallel manner, ensuring that your business database is clean is imperative for optimal functioning.

Let’s see how data scrubbing can help turn the tables in your favor, securing the highest return on investment.

The role of data scrubbing in business growth

Data scrubbing, also known as data cleansing, involves the identification, correction, and removal of inaccurate, inconsistent, or irrelevant data from databases. It employs various techniques, such as validation, standardization, deduplication, or enrichment, to enhance data quality and make it decision and research-worthy.

Furthermore, the benefits of high-quality data go beyond what you might anticipate, offering ample advantages to your internal teams, some of which have been discussed below:

1. Sales

• Accurate lead targeting: Clean data ensures that your sales team is reaching out to the right prospects. This leads to higher conversion rates and more efficient targeting.

• Improved sales forecasting: Reliable data aids in accurate sales forecasting. This helps the sales team set realistic goals, allocate resources effectively, and adjust strategies as needed.

• Reduced follow-up errors: Clean data prevents situations where multiple sales representatives inadvertently reach out to the same lead, minimizing confusion and potential frustration.

2. Marketing

• Precise audience segmentation: Your marketing teams can use clean data to segment audiences accurately. This leads to more targeted campaigns and higher engagement rates.

• Personalized marketing: Accurate data allows for personalized messaging, increasing the effectiveness of marketing campaigns and fostering a deeper connection with customers.

• Better campaign performance: With clean data, marketing campaigns are more likely to yield positive results, leading to a higher return on investment.

3. Accounting/Finance

• Invoice accuracy: With correct billing and invoicing information, the chances of payment disputes and delayed payments are drastically reduced.

• Report generation: Accurate data is essential for generating reliable financial reports. Clean data minimizes errors and discrepancies in financial statements.

• Efficient payment processing: Clean data speeds up payment processing by eliminating errors in customer and vendor information, leading to smoother cash flow management.

4. Customer support

• Enhanced customer service: A clean database provides a comprehensive view of customer history and interactions. This helps customer support teams address inquiries and issues more effectively.

• Faster issue resolution: High-quality data also ensures that customer support teams have the right information at their fingertips, allowing quicker and more accurate resolution.

• Personalized assistance: With clean data, customer assistance teams can provide more customized support based on a thorough understanding of each customer’s needs and preferences.

5. Operations and Management

• Efficient resource allocation: When your data is clean, you can prevent wasteful spending by ensuring that resources are directed toward accurate and relevant targets.

• Strategic decision-making: Reliable data supports informed decision-making at the management level, leading to more effective strategies and long-term planning.

• Process optimization: Clean data reduces errors in various processes, leading to streamlined operations and improved overall efficiency.

One thing that’s crystal clear is that data scrubbing delivers tailored benefits to each team within your organization. From better targeting for sales and marketing to accurate financial reporting and improved customer service, the advantages of clean data span across all aspects of your business, contributing to enhanced performance, productivity, and return on investment.

Now the question is,

How to cleanse or scrub your data?

Data scrubbing is a meticulous process that involves identifying and rectifying errors, inconsistencies, and inaccuracies within your databases. Here’s a step-by-step guide on how to effectively scrub your data:

1. Data assessment

Begin by conducting a thorough assessment of your existing data. Identify the sources of data, the types of information collected, and potential areas of concern. This assessment will help you understand the scope of the data cleansing process required.

2. Deduplication

Duplicates are a common issue in databases and can lead to confusion and errors. Use deduplication techniques to identify and eliminate duplicate records. This involves comparing data entries and removing or merging identical or similar records.

3. Data enrichment

Enhance your data by adding missing information. Data enrichment involves supplementing existing data with additional details from reliable external sources. This can include adding demographic information, social media profiles, and firmographic data to enrich customer profiles.

4. Standardization

Standardize data formats to ensure consistency. This includes formatting addresses, names, and other data elements in a uniform way. Standardized data is easier to manage and analyze.

5. Data validation

Validate the accuracy and integrity of your data. Implement validation rules to ensure that the data entered meets specific criteria. For instance, ensure that email addresses are in the correct format, phone numbers have the right number of digits, and dates are valid.

6. Data governance

Implement data governance policies and guidelines to maintain data quality across the organization. Assign responsibilities to respective teams for data quality and establish processes for handling data-related issues.

7. Regular maintenance

Data cleansing is not a one-time process. Establish a schedule for regular data maintenance to ensure that your data remains accurate and up to date. This could be monthly, quarterly, or annually, depending on the volume and frequency of data changes.

Can it be done in-house?

Well, yes!

However, it comes with a number of challenges, such as:

• Resource allocation: Internal teams may be diverted from core tasks.

• Expertise gap: Lack of specialized knowledge in data quality practices.

• Costs: Expenses related to tools, training, and maintenance.

• Time-consuming: Manual efforts can delay decision-making.

• Limited scalability: Challenges in handling growing data volumes.

In such situations, partnering with database scrubbing experts can be a viable option – benefitting you in several ways, including:

• Expertise: Access to a team proficient in maintaining data quality.

• Cost efficiency: Savings on infrastructure, tools, and training.

• Focus: Internal teams can concentrate on core competencies.

• Scalability: Resources can be adjusted to match data volumes.

• Efficiency: Faster and more accurate results with streamlined processes.

Ultimately, the decision depends on your organization’s needs and goals. Whatever you choose, make sure your data stays clean at all times!