Snapshot:

Data decay is one of the severe challenges that impact the sales prospecting of B2B enterprises and hinders their growth. The realm of the B2B database is highly volatile and dynamic, with constant updates and changes. Failing to keep up with the continuous changes can have a detrimental impact on a B2B business’s revenue and reputation. According to a reliable market survey, around 94% of global B2B markets speculate that their corporate database is inaccurate or decayed. Furthermore, customer data across industries decayed at an estimated 30-40% rate per year during the pre-COVID times.

Data decay is essentially the deterioration of a company’s sales and marketing prospect lists. Data decay compromises a wide range of issues, from duplicate data to redundant and obsolete data. The larger the company, the greater is the size of their current and prospective customer databases. This is an age of rapid shifts and transformations. Companies are continuously adding new business, expanding into new verticals, or changing their decision-making personnel. Failing to keep track of all these changes can lead to the deterioration of old data in the CRM and adversely impact sales and marketing prospecting.

Causes of data decay

Every organization, irrespective of its scale and size, sources data from multiple channels. They have their internal engines, inbound and outbound, as well as third-party B2B database providers. B2B database is complex and continuously changing, and more often than not, enterprises fail to validate and refresh these databases, causing data decay.

Lack of standardization: One of the key reasons for bad data hygiene in B2B organizations is that every company has its unique database taxonomy and data storage guidelines. When they receive data from multiple sources, it is not always standardized, which is further exacerbated since data resides in silos.

Absence of data maintenance tools: Most companies lack sophisticated technology-enabled deduplication and data validation engines, which unintentionally results in the storage of stale and duplicate data in the system.

Lack of expertise in database management: One of the fundamental causes of data decay is that organizations lack technical expertise in data maintenance and management processes. The marketing and sales team often try to clean, validate, and refresh data manually, which leads to errors and repetitions within the database.

Data protection and privacy laws: Stringent GDPR guidelines and data protection laws have limited the quality and volume of data available, particularly in Asia and Europe. One of the vital information that a B2B marketers needs, beyond contact details, is a company’s finances. However, unlike the listed companies, there is no mandatory norm for unlisted companies to publish their financials. This paralyses the company’s ability to segment and target prospects based on their size and scale.

Impacts of data decay on B2B business prospecting

Data decay negatively impacts the overall business growth and revenue in the B2B segment. It hurts the sales prospecting, increases operational overheads, and impedes demand generation. According to a recent survey, the cost of preventing bad data from entering into the CRM is $1, and the cost of correcting existing data problems is $10. Furthermore, as much as 546 hours are wasted on bad data by a sales rep every year. Bad data leaks into the marketing and sales campaigns and drains revenue in different ways. In terms of prospective customers, data decay significantly increases conversion drop, leading to the business impact loss.

According to Jayant Kshirsagar, Senior VP Marketing, Markets & Markets, “Data decay not only impacts the prospective customer base but also has repercussions on the existing customers. It limits a company’s ability to communicate and support its customers’ needs effectively. This inability reduces customer satisfaction and increases customer support costs. Furthermore, the opportunity to cross-sell and upsell to the existing customers is also lost.”

Implementing data maintenance and data hygiene practices 

Data maintenance is an ongoing process where enterprises must regularly clean their databases. It must be integrated with the marketing outreach programs. Enterprises must implement a marketing program that continuously engages and clean the data as part of the process. It is imperative for organizations to develop a robust data nurturing program that leverages AI and machine learning algorithms to augment and clean their contactable database as part of the program. Furthermore, Enterprises must collaborate with their data partners to continuously renew and enrich the existing databases. It is also necessary that companies follow stringent data privacy and protection policies as part of the process. Enterprises must be very conscious of how and where they collect their data.

Stressing on the importance of data protection, Jazz Leong, Head of Integrated Marketing-APAC, Microsoft, says, “Enterprises must have their partners, and the marketers follow stringent data processing and management guidelines. They must ensure that marketers comply with data protection and privacy policies. Also, companies must obtain opt-in consent for every lead generation campaign, regardless of the geography.”

Unlock more insights: “How to Transform B2B Database into a Lead Machine?”

How to eliminate data decay and keep the database relevant?

Organizations need to do due diligence and leverage AI and machine learning tools to automate data maintenance practices and eliminate the risks of data decay. Let’s look at some of the steps that companies can follow to refresh and keep their databases relevant.

Data standardization and verification: The first step in data maintenance is to standardize the data obtained from varied sources. Enterprises need to get rid of duplicate data in their system through a robust deduplication engine. Organizations need cost-effective automation tools that can quickly conduct bulk verification of the contact details.

Data enrichment: The second step in the process of data maintenance is data enrichment. The companies must collaborate with third-party b2b database providers to continuously append new pieces of information within their existing databases. It keeps data refreshed and updated and prevents it from deteriorating.

Data profiling: Lastly, companies need to regularly monitor relevant influencers and decision-makers within their existing firmographic data. Data profiling allows companies to get a lot of net new data in terms of technographic, firmographic, financial, and demographic data. Additional business intelligence like market signals and buyer intent can also help companies improve their sales prospects.

Explaining these points comprehensively, Joy Nandi, Global Head of Intelligent Data Services, Denave, says “Data decay can be avoided by a simple 3-step process. Firstly, deploy data standardization, deduplication, and ongoing data-validation techniques for fast automated bulk verification of existing data in their database. Secondly, work with experienced vendors for data enrichment activities on an ongoing basis, which entails appending additional information to an organization’s database and keeping existing records refreshed and updated to keep it relevant. And finally, as needed, get additional data profiling done for continuously monitoring new relevant stakeholders from existing target companies, and getting net-new entity and basic contact data from their ideal customer profile ecosystem. Additional deeper levels of intelligence about entities including their technographic, firmographics, historical financials, and demographics data as well as real-time synthesized market signals and buyer intent can also greatly positively impact conversion rates from prospect to leads.”

Data plays a crucial role in optimizing the marketing and sales campaigns for better prospect targeting and conversions. Read the blog “Battle-Tested Ways to Expel B2B Data Decay and Elevate Sales Prospecting” to know more.

Conclusion

There is no single solution for companies to fix the problems of data decay. Data maintenance and hygiene is a combination of manual and automated efforts. Enterprises must combine human ingenuity with AI and machine learning tools to effectively manage, enrich, and grow their databases. Each business has a unique challenge with its database and requires a unique treatment to address it. However, there are some of the industry best practices that they can implement to reduce the risks of data decay.

Watch our webinar on “The Curse of Data Decay on Sales Prospecting” to get deeper insights on how leading global enterprises are leveraging futuristic tools and strategies to eliminate data decay and drive business growth.