Overview
Data validation ensures the accuracy of B2B data, leading to successful analytic outcomes and marketing campaigns. According to the 6th annual B2B marketing data report, 88% of marketers believe data quality is one of the biggest factors in successful execution of marketing strategies. So, the importance of data validation and raising data quality is understood well by most B2B data sellers. But often, lack of expertise, skilled staff, resources, or other constraints hold them back from deploying advanced data validation systems. This affects their business prospects.
Validity checks are labor intensive and complex and require significant investment in resources. Therefore, companies seek support from B2B data sellers, or they would have done it by themselves.
Manual B2B data validation efforts are insufficient for shouldering the workload in the case of large datasets. And only automation can provide the accuracy and speed needed to sort and check enormous volumes of data. So, regardless of constraints, a B2B data seller needs to invest in automated data validation systems.
Challenges for B2B data sellers
Data quality is the foundation of sales and marketing revenue for both data sellers and their clients. And there can be no compromise in this area. However, a B2B data seller faces multiple challenges in maintaining data accuracy. These challenges include:
Data decay: Company data and contact details change at a rapid pace, leading to data decay.
Keeping Database constantly enriched: Capturing additional layers of data on existing clientele from multiple sources continuously requires serious effort.
Data authenticity for SMEs: The data of privately held companies, especially those of smaller and medium sizes, are difficult to find and authenticate.
Keeping the database comprehensive: Keeping the database comprehensive with information on all viable companies/startups is difficult, as most are not reported.
Why B2B data providers can’t avoid investing in data validation
Investing in technology-enabled services like data verification, validation, enrichment, and cleansing helps B2B data sellers develop a strong, high-performing, and scalable database. A validated database has higher accuracy and helps sell data with full confidence.
Readily usable data with proper standardization and segmentation
More than 50% of buyers choose that data seller who contacts them first. So, to win the race, your database needs to remain primed for sale on short notice. Since data changes every minute, you need a well-planned automated validation system to ensure your data always stays salable. B2B data is not only about sourcing. There are many steps taken to process aggregated data before it can be validated for final use by businesses.
These include data acquisition, cleaning, standardizing, segmenting, and other significant operations. In automated systems, data is validated with predetermined rules and scheduled macros that run at regular intervals and reduce errors. This ensures much higher output accuracy. And you can offer clients access to a validated B2B database on the go.
Build credibility through a high-performing decay-resistant database
The annual B2B data decay rate is estimated to be about 70%. With almost 60% of workers changing job titles within their organizations every year and 40% changing their emails every two years, maintaining data hygiene becomes a big challenge. Your data quality drops without proper validation and affects your productivity, efficiency, reliability, and brand reputation.
Your buyers look for reliable, actionable intelligence to make informed decisions, achieve more sales, and maximize their ROI. The success of their sales and marketing teams depends on accurate data. And by providing meticulously validated B2B data, you help them to drive higher conversions. When they have higher confidence and trust in your data, they are more inclined to build long-term client associations.
Optimized ongoing data maintenance cost
Implementing an automated database maintenance strategy is cost-effective. Going by the common 1-10-100 rule, the cost of preventing bad data is $1, the cost of correcting existing problems is $10, and it costs $100 if you do nothing. Ongoing B2B data validation thus saves both time and money. Keeping data up to date, structured, and ready for use keeps remediation costs in check and greater ROI. This is how executing a structured B2B data validation plan increases operational efficiency and reduces overall maintenance costs.
Structure validation helps in easy integration with client’s databases
Validating the structure of the data is just as important as validating the data itself. Structure validation standardizes the data collected from different sources and formats. Small inconsistencies, such as multiple names for the same data, or the same data in different formats, may seem trivial but can significantly affect database deployment.
43% of sales and marketing teams agree that a lack of accurate data negatively affects their marketing campaigns. Normalizing and standardizing the data ensure accurate data for your buyers. It also ensures compatibility with other datasets for easy integration.
A comprehensive and accurate database leads to higher revenues
Keeping your database validated and updated with all relevant information can be a complete game changer. Once you are confident of your data, you will be in a better position to talk about it and convince your buyers. B2B data buyers are 2.8 times likelier to make purchases with better information.
Your buyer needs to be convinced of your data quality, as 89% of them know data quality is crucial for business success. Thus, an accurate and validated database offers a win-win situation for both the seller and buyer of the data. And that builds your market credibility and increases your customer base and loyalty.
Conclusion
The growth of B2B companies depends on accurate and validated data. Data helps them understand the customer better and find actionable leads. However, providing validated B2B data to clients presents multiple challenges. Any data that an aggregator sells must be current, relevant, accurate, updated, and enriched. Sometimes, conducting all data processes in-house can be cumbersome, or against an asset-light approach. This is where specialized B2B data validation services with relevant expertise and infrastructure can provide valuable assistance.
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