Identifying causes, business impact, and techniques to eliminate bad data from C

1. DISSECTING DATA DECAY Identifying causes, business impact, and techniques to eliminate bad data from CRM

2. Page 1: Introduction Index Understanding the phenomena of data decay Page 2: Causes of data decay Page 3: Business impacts of data decay Page 4: Techniques to eliminate data decay Implementing data maintenance & hygiene measures Page 5: Conclusion Page 6:

3. SETTING UP THE CONTEXT B2B businesses rely heavily on accurate databases for sales and marketing success. From phone numbers and email addresses to tech stack, branch locations, and financial details, companies need quality data to strengthen their lead generation campaigns and maximize conversions. Modern sales and marketing are not just about data gathering, but the ability to generate business insights from data sets and then act on these insights innovatively to accrue sales benefits. However, data decay is one of the most pressing challenges for b2b businesses, hurting their sales opportunities and overall growth. According to a recent survey, around 94% of global markets speculate that their database is inaccurate or stale, primarily due to large-scale data decay. Moreover, around 3% of data gets decayed every month globally. In addition, contactability with key stakeholders across departments and companies is a significant issue with employees quickly changing job roles and companies. According to a data impact analysis for businesses, the cost of preventing bad data from entering the CRM is about $1, the cost of fixing every data problem is $10, and the cost of repairing the data after leaving it unchecked is $100. Owing to poor data quality, b2b sales reps waste approximately 27% of their time chasing after the wrong or irrelevant accounts. ©Denave

4. WHAT IS DATA DECAY? Data decay is essentially the deterioration of a company’s sales and marketing prospect lists. It encapsulates a diverse range of data issues, including duplicate data, redundant and obsolete data. The larger the company, the more significant is the size of their existing and prospective customer lists that need continuous maintenance to stay refreshed, alive, and relevant. The current business environment is highly volatile, with companies adding new businesses, scaling into new verticals, or chopping-changing their decision-making personnel. Failing to track all these changes leads to the deterioration of existing data in the CRM and negatively impacts sales and marketing prospecting. One of the primary reasons for data decay is that companies don’t have a robust data deduplication and standardization engine. This inadvertently results in the storage of obsolete and duplicate data in the system. Another cause for data decay can be attributed to the unique database taxonomy and data storage guidelines. When a company extracts data from different sources, it is not always standardized, which is further exacerbated since data exist in silos. ©Denave

5. CAUSES OF DATA DECAY Every enterprise, irrespective of its size and scale, sources data from varied channels. They have their internal inbound and outbound engines along with third-party b2b database providers. However, the b2b database is quite complex, and companies often fail to validate and refresh these databases, which breeds data decay. Below are some of the common causes of data deterioration in the b2b ecosystem: Lack of standardization: Companies struggle to maintain a standardized CRM with relevant databases due to the absence of a data standardization process along with unique taxonomy and data storage guidelines. This is aggravated further since data resides in silos. \ Lack of data maintenance tools: Most b2b enterprises still persist with manual data maintenance practices. They lack sophisticated tech-powered data deduplication and validation engines, making it difficult for them to ascertain the relevance and contactability of the databases. Lack of early validation results in the storage of old and duplicate data in the CRM system. ©Denave

6. Lack of industry expertise: One of the most widespread bottlenecks among small and large enterprises is the lack of technical expertise in data maintenance, hygiene, and management processes. They often rely on manual methods to clean, refresh, update, and enrich data, allowing inaccuracies to seep into the system. Data privacy and protection laws: Stringent GDPR and data protection laws have limited the data quality and quantum available in the market, particularly in Asian and European countries. One of the mission-critical information that b2b marketers need, beyond contact details, is the financial information of target customers. However, unlike the publicly listed companies, unlisted companies need not divulge their financial information. This incapacitates an organisation’s ability to segment and target customers based on their size and scale. ©Denave

7. IMPACTS OF DATA DECAY ON B2B ENTERPRISES Data decay negatively impacts the customer outreach campaigns, demand generation, and overall business growth in the b2b segment. It hurts the b2b lead generation campaigns, shoots up marketing overheads, and stuns the lead to conversion ratio. The average financial effect of inaccurate and bad data runs up to $9.7 million per year. Existing customer base: Data decay limits a company's abilities to maintain open and personalized communication models with its existing customer base. This causes unfulfilling customer relationships and increased customer support costs. A below-par customer relationship arising due to poor communication affects approximately 25% revenue of a business. Also, the opportunity to upsell and cross-sell to the existing accounts is lost significantly. Prospective customers: In terms of prospective customer lists, data decay significantly increases conversion drop, leading to the business impact loss. Lack of regular contact validation, enrichment, and renewal of the prospective account lists impedes a company's branding projections. Increased churn rates: The term churn rate signifies the percentage of email subscribers that unsubscribe to a company's mailing list over a fixed period. Bad data can increase the churn rate and wreak havoc on a company's email marketing campaigns. According to a survey, the churn rate drains approximately 25 to 30% of the average mailing list every year. ©Denave

8. Missing the target audience: To pull off a successful market campaign, marketers must strike the iron while it's hot. It essentially means that they must disseminate highly relevant email or product messages to relevant accounts at the most opportune time. However, due to decayed datasets, marketers will struggle to create buyer personas and waste their time and resources approaching the incorrect audience lists. ©Denave

9. COUNTERACTING DATA DECAY The smallest bit of prevention can offset time and resources waste arising due to data decay mishaps. Beyond conventions, companies must do due diligence and leverage future-forward tools like AI and machine learning to automate data maintenance strategies and eliminate data decay risks. Let’s run down some of the steps that b2b enterprises can follow to keep their database relevant and contactable. Data standardization: This first stride towards data maintenance is to standardize the data obtained from multiple sources. Enterprises need to get rid of duplicate data in their CRM through an AI- powered deduplication engine. Companies need cost-effective automation tools to quickly conduct bulk verification of contact details, along with technographic, demographic, financial, and firmographic information. Data enrichment: The second phase of the data maintenance journey is to enrich and update datasets to keep it’s contactability intact in the face of recurring changes. It is advisable for businesses to enlist the services of reliable third-party b2b database providers to continuously append new pieces of information within their existing customer accounts. They must regularly scourge for additional information that will keep their datasets refreshed, updated, and relevant in the long run. ©Denave

10. Data profiling: Lastly, enterprises must frequently track key influencers and decision-makers within their existing firmographic data. Data profiling allows for database segmentation based on different features and labels. It also helps companies acquire net new data in terms of technographic, firmographic, financial, and demographic data. Moreover, additional customer intelligence like market signals and buyer intent also improves the sales prospects of the companies. Leveraging automation tools: One of the easiest methods to eliminate data decay is switching from manual data collection and management to automated digital tools. Although professional database providers are essential for rigorous data maintenance practices, automation helps streamline the processes and continuously appends and corrects decaying data. ©Denave

11. IMPLEMENTING DATA MAINTENANCE & HYGIENE MEASURES Data maintenance is an ongoing process where companies must regularly clean their corporate database. It must be unified with marketing outreach campaigns. Enterprises must architect a marketing program that continuously cleans and validates 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 database service providers 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. They must be very conscious of how and where they collect their data. 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. ©Denave

12. CONCLUSION No single solution is fool proof for b2b companies to fix the issues of data decay within their databases. Companies need a smart mix of manual and automated processes to streamline their data maintenance and hygiene practices. Enterprises must create hybrid database management models combining human expertise with AI, ML, and NLP tools to effectively manage, enrich, and grow their databases. Every business has a unique set of challenges with its database and requires a unique treatment to address them. However, there are some of the industry best practices that they can implement to reduce the risks of data decay. ©Denave

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