{"id":757,"date":"2023-04-14T07:39:00","date_gmt":"2023-04-14T07:39:00","guid":{"rendered":"https:\/\/dataprot.net\/?p=757"},"modified":"2023-07-14T07:44:44","modified_gmt":"2023-07-14T07:44:44","slug":"data-decay","status":"publish","type":"post","link":"https:\/\/dataprot.net\/articles\/data-decay\/","title":{"rendered":"Data Decay: Causes and Solutions"},"content":{"rendered":"\n

In today\u2019s day and age, information and data are everything, which shouldn\u2019t surprise anyone. After all, we all live in the so-called information age. What most people fail to realize, however, is just how much modern businesses depend on data collection<\/a>.<\/p>\n\n\n\n

The Internet<\/strong><\/a> allowed companies to reach and collect data on a scale never seen before<\/strong>. Businesses rely on it to generate revenue and continue growing their customer pool. Therefore, they need to keep their data pools fresh and limit data decay to a minimum.<\/strong><\/p>\n\n\n\n

What Is Data Decay?<\/strong><\/h2>\n\n\n\n

Data decay happens when once-relevant data becomes unusable by the company due to aging, a hardware failure, or simply getting lost.<\/strong> But what do we mean by this term, and how does data decay?<\/p>\n\n\n\n

Businesses collect vast information on their current and potential customers. This data is then processed by the business\u2019s sales and marketing teams to generate additional leads or revenue for the company. <\/p>\n\n\n\n

The data businesses collect includes emails, addresses, phone numbers, business locations, and other relevant contact information. <\/strong>This data can decay by becoming irrelevant and, in turn, impact sales performance. <\/p>\n\n\n\n

No, bytes didn\u2019t get an expiration date overnight. Data decay refers to each email address that ends up being closed or unused but still exists in the business database. If the company works with outdated information, it can lose valuable time and resources without any tangible gain<\/strong>.<\/p>\n\n\n\n

Types of Data Decay<\/strong><\/h2>\n\n\n\n

While most decay happens because customers change their contact or other relevant details without bothering to notify the companies, it\u2019s not the only reason. We can observe two types of data decay depending on the root cause.<\/strong><\/p>\n\n\n\n

Mechanical Data Decay<\/strong><\/h3>\n\n\n\n

Mechanical data decay refers to any data loss caused by a mechanical failure or a malicious attack.<\/strong> This can happen easily if the company\u2019s hardware isn\u2019t properly maintained. In the end, neglect always leads to a <\/strong>catastrophic hardware failure<\/strong><\/a> that will cost the company a lot of money.<\/p>\n\n\n\n

Investing in prevention is always cheaper in the long run than dealing with the aftermath of a preventable disaster. This is especially true with data since, in most cases, you won\u2019t be able to recover anything useful.Luckily, mechanical data decay can be easily avoided by using cloud storage or backup. A backup can help even against various cyber attacks, including ransomware.<\/p>\n\n\n\n

\"A<\/figure>\n\n\n\n

Logical Data Decay<\/strong><\/h3>\n\n\n\n

While sales and marketing databases can contain new and old information from customers who used the company\u2019s services or subscribed to its mailing lists, nothing guarantees the relevance of the data stored. <\/strong><\/p>\n\n\n\n

Data quality deteriorates over time due to the nature of the data itself. The older the information is, the bigger the chance it is useless to the company, negatively impacting sales and marketing performance. What exactly do we mean by this?<\/p>\n\n\n\n

Changing the email address takes a couple of minutes and doesn\u2019t cost anything. On top of personal emails, you also have various business emails people use during their careers. Now imagine how often people change emails when an average American changes their home address 11 times during their lifetime<\/a>.<\/p>\n\n\n\n

The answer is too often, and let\u2019s not forget about throwaway emails used only to subscribe to various online services. Cell phone numbers don\u2019t fare much better. <\/p>\n\n\n\n

Logical decay happens only when customers don\u2019t update their contact information. It can also occur due to misspellings, either on the customer\u2019s end or during the manual data entry by the employee.<\/p>\n\n\n\n

This makes logical data decay very hard to spot and requires a proactive approach to identifying and removing outdated data from the sales and marketing databases. <\/p>\n\n\n\n

Data Decay Impact<\/strong><\/h2>\n\n\n\n

Any information decay will harm sales and marketing efforts to generate revenue from leads. If a good portion of the database leads to dead ends in the form of unexisting or unused emails, it\u2019s only a drain on an organization\u2019s time and money.<\/p>\n\n\n\n

You would think <\/strong>B2B sales<\/strong><\/a> are immune from data decay since companies rarely change their emails, but it\u2019s far from the truth<\/strong>. It can easily happen that the point of sales contact in the company has moved away to a new job in a different company, and the email is now deactivated, or the company re-branded overnight and changed its email address format and domain.<\/p>\n\n\n\n

In both cases, companies should take steps to ensure that emails sent to old addresses don\u2019t disappear, but that doesn\u2019t always happen.<\/p>\n\n\n\n

It\u2019s estimated that the average monthly B2B data decay is around 2.1%<\/strong><\/a>.<\/strong> It may not look like a lot, but it quickly adds up. Let\u2019s say that you have 5,000 contacts, and you lose 2.1% each month. You would have lost 415 leads in five months, or 10.1% of your database. Every year, you would lose 22.5%.<\/p>\n\n\n\n

Data degradation example<\/strong>: <\/p>\n\n\n\n

    \n
  1. 5,000 \u2013 2.1% = 4895 (Lost: 105)<\/li>\n\n\n\n
  2. 4,895 \u2013 2.1% = 4792 (Lost: 103)<\/li>\n\n\n\n
  3. 4792 \u2013 2.1% = 4691 (Lost: 101)<\/li>\n\n\n\n
  4. 4691 \u2013 2.1% = 4592 (Lost: 99)<\/li>\n\n\n\n
  5. 4592 \u2013 2.1% = 4495 (Lost: 97)<\/li>\n<\/ol>\n\n\n\n

    Data Decay Prevention<\/strong><\/h2>\n\n\n\n

    Companies can\u2019t stop customers from changing their emails. Still, they can introduce steps that will help them avoid data decay effects on their database<\/strong> and, in turn, increase the effectiveness of their sales and marketing teams.<\/p>\n\n\n\n

    Email Verification Tools<\/strong><\/h3>\n\n\n\n

    The best way to clean up your database is by verifying if the email addresses and domains exist before an outbound marketing campaign starts. Every email service will inform you if the sent email isn\u2019t delivered because the address doesn\u2019t exist, but checking every email manually will take ages. Luckily, tools can now automate these processes, saving you time and nerves.<\/p>\n\n\n\n

    Confirmation Email<\/strong><\/h3>\n\n\n\n

    Another simple way to fight email storage data decay is to include email verification<\/strong> during the registration process. This would prevent customers from using a fake email, but it still won\u2019t prevent them from using a throwaway account. <\/p>\n\n\n\n

    Customer Relationship Management Software<\/strong><\/h3>\n\n\n\n

    Customer relationship management (CRM) software helps the company keep all customer data in one centralized and easily accessible location. <\/strong>This allows for a clear overview of all interactions with all potential and current clients and gives data for analyzing potential profit. To optimize sales, it can organize data into separate groups based on product, customer profile, or market. <\/p>\n\n\n\n

    For CRM to be effective, it has to be integrated with other data solutions used by the company. <\/strong>The sales and marketing teams should use one database and not have two separate ones with different information. If a separate database is required, strict data integrity checks should be implemented throughout the organization to prevent further decay. <\/p>\n\n\n\n

    Data Hygiene Implementation<\/strong><\/h3>\n\n\n\n

    Data hygiene<\/a> is one of the most important steps in preventing data decay and one of the easiest to implement. It includes: <\/p>\n\n\n\n