Decoding Data Validation: significance, Challenges and Implementation

Ensuring the quality of data becomes even more critical as organizations around the world adopt data-oriented practices to improve operational efficiencies and increase revenue. Poor quality data gathered from different sources can derail a company’s efforts to meet key business objectives. They are often burdened with the sheer volume of data—and face challenges for data standardization, lack of data governance, disparate data systems, manual processes, etc.

Companies collect customer data including techno graphic, demographic, firmographic, and financial via internal functions and external interactions. But the collected data is often raw and inaccurate that isn’t fit for direct business consumption. As this doesn’t offer actionable insights, there arises a need for data validation. Implementing organization-wide data quality programs to validate and standardize databases makes it easier for stakeholders to trust their data.

Understanding Data Validation

As the name suggests, data validation is the way of ensuring the accuracy and quality of data before merging it with the master database of the company or using it for other purposes—numerous processes and techniques help uphold its integrity.

It is a form of data cleansing that involves verifying the data in terms of its relevance and contact ability. The process ascertains that the data is unique, complete, and consistent with the expected range of values. Investing in data validation services helps organizations enrich their master database with relevant information.

Challenges in the Process

Access to an accurate and compliant database helps personalize customer journeys, avoid pitfalls, and streamline sales marketing campaigns. However, maintaining database integrity becomes challenging for the sales and marketing team due to multiple reasons. Diving deep into the challenges of the process and quantifying its impacts can help businesses improve their bottom line. Take a look:

• Lack of Data De duplication & Standardization

We all know that data comes from a variety of sources and gets integrated into CRMs, ERPs, etc., which is further exacerbated as data lives in silos. Companies usually don’t have a robust deduplication engine, resulting in duplicate data getting stored in the system. Hence, the lack of data standardization and uniform data storage guidelines is one of the key issues for many organizations.

• Lack of Infrastructure

Another critical challenge is the non-implementation of automated and/or AI-based data validation engines. B2B databases require next-gen automated tools to verify and validate databases with NLP capabilities to keep them relevant and refreshed. Manual validation of data leads to repetitions and errors within the database.

• Lack of Expertise

Another fundamental challenge of database verification is that organizations lack expertise in data maintenance and management processes. Their marketing and sales teams have to shoulder the responsibility of data validation manually, leading to stale in the system. Organizations often don’t understand the importance of the data validation process and associate a business cost with their quality programs.

Significance of Database Validation

Businesses of varying sizes and verticals rely on high-quality data to make critical decisions. It offers insights into consumer behavior, changing market trends, purchasing habits, predicting future trends, etc. Engaging in professional data verification services helps organizations in navigating the challenges at different stages of the pipeline and offers multi-fold benefits:

• Strategic Time Management

Validating data regularly weeds out inaccuracies and duplicates, preventing the sales and marketing teams from using incorrect databases for their campaigns. Suppose a sales team is shooting emails at dead email addresses or calling on disconnected numbers. This results in a wastage of effort and time hurting the organization’s overall revenue. Address and phone verification services help overcome such challenges.

• Accurate Results

Validating the data for inaccuracies and anomalies helps maintain an updated database. It helps companies establish their product placement with potential customers. Many buyers choose the vendor that contacts them first; hence, having valid contact information gives more accurate results in maximizing the bottom line.

• Optimize Marketing Budget

B2B Marketing has a higher upfront cost that comes with a higher engagement potential. Data verification and validation allow companies to invest their resources in relevant prospects. It becomes easier for businesses to build a targeted campaign when they are confident about whom they are contacting.

• Maximize Customer Satisfaction

One of the effective ways to prevent data decay is validation. Validating a list of databases for customer information increases an organization’s ability to effectively communicate and support its customer needs. Plus, it also increases the potential to upsell and cross-sell with existing customers.

Implementing Validation & Hygiene Practices

Database validation and verification is an ongoing process that needs subject matter expertise. Deriving relevant and correct information from different data sources is difficult and complex. Collaborating with professional providers helps them continuously renew and enrich their existing database. These third-party vendors follow stringent data governance guidelines to ensure the privacy of customer data. They can implement cross-reference validation, correlate new data with existing datasets, perform range checking to fill the gaps and identify, and eliminate the inconsistencies between data.

Conclusion

Data validation is a big leap forward that goes beyond the repetitive standardization process. It opens new avenues to develop great customer and value propositions and helps companies gain trust and confidence in their data.

Plus, sales and marketing teams get actionable intelligence to make meaningful decisions and improve the pipeline that maximizes ROI. There are several challenges associated with the process, but there is nothing that cannot be overcome.