Data Decay

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In the data-dominated world of B2B sales, data is a critical asset that drives nearly every facet of revenue operations and customer engagement. Yet, data decay is a pervasive challenge that undermines the effectiveness of these initiatives. This phenomenon is a significant barrier to growth and productivity, costing organizations time, money, and opportunities.

Understanding Data Decay

Data decay, also known as data degradation, refers to the gradual deterioration in the quality, relevance, and accuracy of data over time. As the world changes, so does the information within it: people change jobs, companies merge or rebrand and technology stacks evolve, rendering yesterday's customer insights obsolete.

For instance, consider a B2B CRM database filled with contact information for key decision-makers. According to research, the average annual decay rate of such data is around 25%. This means that if you're not consistently updating your data, a quarter of it could be irrelevant every year. This decay impacts various types of data, from customer details to market trends, product information, and more. If left unchecked, all of the investment you’re making in sales and marketing campaigns will be less and less effective.

Why is maintaining the relevance of data so difficult?

The world is constantly changing, and nowhere is that more true than on the internet. All of the data that salespeople use to qualify leads and research prospects is subject to rapid change and fluctuation. People change jobs, companies evolve, merge, or cease to exist, and industry trends shift. This constant flux means that information can become outdated quickly without notice.

Moreover, the sheer volume of data generated daily adds to the complexity of maintaining high quality, current records in your CRM. Businesses need to sift through and validate a vast amount of information from dozens of disconnected sources, making it challenging to ensure that the data they rely on is current and accurate.

Lastly, the process of updating data is time-consuming and requires dedicated effort and resources. In many organizations, there is a lack of clear ownership or processes for maintaining data quality. Without systematic approaches assisted with automation and responsible parties, data decay can go unchecked, further complicating the task of keeping data relevant and useful.

The Impact of Data Decay on Your Sales Organization

Data decay has tangible and intangible consequences for businesses:

Reduced Pipeline: When sales and marketing teams work with outdated data, they waste time reaching out to prospects that may no longer be relevant or miss out on potential new targets. This can also result in negative brand perception if contacts are continually approached with irrelevant or outdated propositions.

Strategic Errors: When executives rely on inaccurate data, they risk making sales strategy decisions that could lead to poor outcomes, like running irrelevant campaigns or investing in declining segments and territories.

Decreased Efficiency: Teams spend unnecessary time correcting errors, which could have been allocated to high value sales tasks, such as account planning. This not only slows down the pace of work but also increases costs related to data management and cleaning.

Non-Compliance Risks: With regulations like GDPR, keeping data up to date isn't just good practice—it's a legal requirement. Non-compliance can result in hefty fines and reputational damage.

The Types of Data at Risk of Decay

Data decay impacts every facet of your revenue operations from lead generation to funnel conversion rates and renewals.

Contacts: This includes names, job titles, email addresses, and phone numbers. Given the dynamic nature of job roles and contact information, this data requires frequent updating to remain useful.

Enrichment: Data enrichment can include adding social media profiles, company size, industry type, or other demographic details. Enrichment helps in segmenting and targeting prospects more effectively. Regular enrichment of contact data ensures that sales and marketing teams are working with up-to-date information, increasing the chances of successful engagement.

Buyer intent data: This type of data signifies a prospect's intention to buy, gathered from their online activities and interactions. As market trends and consumer interests evolve, intent data can quickly become outdated, leading to misaligned sales strategies.

Product usage data: For companies offering digital products or services, how and to what extent customers use these offerings is crucial for sales and product development. However, changes in customer preferences or the introduction of new technologies can render this data obsolete, necessitating regular updates to maintain its relevance.

Strategies to Combat Data Decay

However, while data decay is inevitable, its negative consequences are not. Companies can implement several strategies to minimize the impact of data degradation.

1. Regular Data Audits

Routine data audits are essential. By regularly reviewing data sets, companies can identify inaccurate, redundant, or outdated information. This process should not be random but systematic and comprehensive. Depending on the data’s volatility, audits might be required quarterly, bi-annually, or annually.

2. Automated Data Updating

With advancements in technology, many businesses can now update their data automatically in real-time. Tools and platforms can track changes as they occur and modify the datasets instantaneously. For example, when a contact changes their job title on LinkedIn, this information can be immediately reflected in your CRM system.

3. Single Source of Truth

Utilizing the sales CRM as the Single Source of Truth streamlines data management. It consolidates all essential information in one place, ensuring accuracy and consistency across the organization. This approach simplifies updates and decision-making, focusing all data-related activities on one reliable system.

4. Employee Training

Human error contributes significantly to data decay. Training employees on the importance of accurate data entry and the right techniques can go a long way in maintaining data quality.

5. Leveraging Data Decay Analytics

Today's sophisticated data analytics tools can predict decay patterns, providing insights that help organizations preemptively refresh their data.

6. Building a Data-Centric Culture

Cultivating a culture that understands the importance of data integrity can promote proactive behaviors that prevent data decay. Encouraging ownership of data quality among team members instills a sense of responsibility and vigilance.

7. Deploy Data Quality Teams

Dedicated data quality teams focus on the maintenance and integrity of organizational data. They work to ensure that data decay does not undercut business initiatives.

Aomni Delivers Up-to-date Data

A concrete example of a solution that counteracts data decay is the platform Aomni offers. Our AI agent platform provides real-time account research and insights, ensuring that the data at your fingertips is always as current as possible. What sets Aomni apart is its AI-driven intelligent automation, which works diligently to monitor and refresh data, minimizing the impact of decay.

Conclusion

Data decay is an unavoidable challenge in the dynamic world of sales, but its negative impacts are avoidable. Mitigating the effects of data decay is not about engaging in a one-off project; rather, it’s about creating continuous processes and leveraging tools like Aomni that embed data hygiene into the everyday workflow.

Data Decay in Sales