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    Data GuideFebruary 9, 202618 min read

    How Often Businesses Close and Change Numbers: Understanding Data Decay

    Business data decays faster than most people realize. Phone numbers change, emails bounce, businesses close their doors forever. Understanding these decay rates is essential for maintaining effective outreach and planning your data strategy.

    data decaybusiness datadata freshnesscontact informationB2B leadsdata qualitylead maintenancebusiness closuresphone number changesemail bounces
    20%
    Close Year 1
    15-20%
    Phone Changes/Year
    22-30%
    Email Decay/Year
    2.5%
    Monthly Decay Rate
    Section 1

    The Reality of Business Data Decay

    The Inconvenient Truth

    Business contact data has a shelf life. It is not a permanent asset that you buy once and use forever. From the moment you acquire a lead list, the clock starts ticking. Every day, some of that data becomes less accurate, less useful, and eventually worthless.

    This is not a flaw in data providers. It is a fundamental characteristic of business information. Understanding this reality helps you plan appropriately and avoid frustration when some leads do not connect.

    What Causes Data Decay

    • Business closures. Companies fail, owners retire, partnerships dissolve.
    • Relocations. Businesses move to new addresses, change phone numbers.
    • Staff turnover. Decision-makers change roles, leave companies, or retire.
    • Contact updates. New phone systems, email domains, website redesigns.
    • Mergers and acquisitions. Companies combine, rebrand, or get absorbed.

    The Cumulative Effect

    Data decay compounds over time. A database that is 95% accurate today will not stay that way. After 12 months, that same database might be only 70-80% accurate, assuming no maintenance.

    Annual Cumulative Decay Example

    Starting accuracy95%
    After 6 months~85%
    After 12 months~72%
    After 24 months~52%

    The Key Insight

    Data decay is not a problem to solve once. It is an ongoing process to manage. The most successful outreach operations treat data freshness as a continuous priority, not a one-time purchase. Plan for regular data refresh cycles, and budget accordingly.

    Section 2

    Business Closure Rates: The Permanent Decay

    US Small Business Survival Statistics

    1

    Year 1

    ~20%

    of new businesses fail

    5

    Year 5

    ~50%

    have closed by now

    10

    Year 10

    ~65%

    have closed by now

    15

    Year 15

    ~75%

    have closed by now

    Source: US Bureau of Labor Statistics Business Employment Dynamics data. These are national averages - rates vary by industry, location, and economic conditions.

    Industry Variation in Closure Rates

    Restaurants~60% in 3 years

    Highest failure rate of any industry

    Retail~45% in 5 years

    High competition, thin margins

    Professional Services~35% in 5 years

    Lower overhead, more stability

    Healthcare~25% in 5 years

    Consistent demand, regulated entry

    What This Means for Your Data

    • 1
      Newer businesses decay faster

      A list of 1-year-old businesses will have more closures than established ones.

    • 2
      High-risk industries need fresher data

      Restaurant and retail lists age poorly. Refresh more frequently.

    • 3
      Established businesses are more stable

      A business that survived 10 years is likely to survive the next year.

    • 4
      Economic conditions matter

      Recessions accelerate closures. Data from turbulent times decays faster.

    Practical Implication

    If you have 1,000 business leads and assume an average 8% annual closure rate across industries, you will lose approximately 80 businesses from your list every year just from closures. That is before accounting for phone changes, email bounces, or other contact updates.

    Section 3

    Phone Number Changes: The Silent Data Killer

    Why Phone Numbers Change

    • Business relocations. Moving to a new location often means new numbers, especially across area codes.
    • Phone system upgrades. Switching from landlines to VoIP, or changing providers.
    • Area code changes. New area codes introduced due to phone number exhaustion.
    • Number recycling. Old business numbers get reassigned to new owners.
    • Spam blocking. Businesses change numbers to escape persistent spam calls.

    Phone Number Decay Rates

    Annual disconnection rate15-20%

    Includes disconnected, wrong numbers, and reassigned lines

    Monthly decay rate1.5-2%

    Consistent monthly degradation of phone data quality

    After 2 years without refresh30-40% invalid

    Nearly half your phone data becomes unusable

    Phone Data Accuracy Over Time

    95%
    Fresh data
    85%
    6 months
    75%
    12 months
    55%
    24 months

    Visual representation of phone data accuracy degradation over time without maintenance

    Mobile vs Landline Considerations

    Mobile numbers tend to be more stable than landlines because people keep them when they move. However, mobile numbers for businesses may change more often as employees leave or change roles. For small businesses where the owner's mobile is the primary contact, these tend to be more persistent than business landlines.

    Section 4

    Email Address Changes: The Fastest Decay Channel

    Email Decays Faster Than Other Data

    Email addresses are particularly vulnerable to decay. Industry research suggests B2B email data degrades at approximately 22-30% per year. That means nearly one in four emails in your database will become invalid within 12 months.

    This is actually the highest decay rate of any common contact data type. Your email list needs more frequent attention than your phone list.

    Why Emails Become Invalid

    • 1
      Employee turnover

      When employees leave, their email accounts are typically deactivated. Average job tenure is just 4.1 years.

    • 2
      Company email domain changes

      Rebrands, mergers, or moving to new email providers invalidate entire domains.

    • 3
      Mailbox capacity limits

      Abandoned or full mailboxes bounce emails even if the address technically exists.

    • 4
      Personal email changes

      Small business owners using personal emails may switch providers (Gmail to Outlook, etc.)

    Email Bounce Rate Impact

    Healthy bounce rate<2%

    Fresh, well-maintained lists

    Concerning bounce rate2-5%

    Data aging, needs attention

    Dangerous bounce rate>5%

    Risk of being flagged as spam

    High bounce rates damage your sender reputation. Email providers may start blocking your messages entirely, affecting even your valid contacts.

    Email Type Decay Comparison

    Corporate Emails

    25-35%/year

    Highest decay due to employee turnover at larger companies

    Small Business Emails

    15-25%/year

    More stable as owner emails persist, but still significant

    Generic Emails

    10-15%/year

    info@, sales@, contact@ persist longer but reach fewer decision-makers

    Section 5

    Other Contact Data Changes

    Physical Addresses

    Annual change rate10-15%
    Average business moves every7-10 years

    Address changes are less frequent than phone or email, but when they happen, they often trigger other contact changes as well.

    Website URLs

    Annual change rate5-8%
    Sites going offline annually3-5%

    Websites are relatively stable, but rebrands, domain changes, and hosting lapses do occur. Sites marked as "no website" may have built one since.

    Contact Names/Titles

    Job change rate20-25%/year
    Average job tenure4.1 years

    Contact names are the most volatile data point. Even if someone stays at the company, titles and roles change frequently.

    Data Decay Rate Summary

    Data TypeMonthly DecayAnnual Decay2-Year Decay
    Email Addresses2-3%22-30%40-50%
    Contact Names1.5-2%20-25%35-45%
    Phone Numbers1.5-2%15-20%30-40%
    Physical Addresses0.8-1.2%10-15%20-30%
    Business Existence0.7-1%8-12%15-22%

    Rates vary by industry, business size, and economic conditions. These are industry averages based on B2B data research.

    Section 6

    Managing Data Decay: Best Practices

    Recommended Refresh Cycles

    High-Volume Operations

    Refresh data quarterly. If you are sending thousands of emails per month, stale data will damage your sender reputation quickly.

    Medium-Volume Operations

    Refresh data every 6 months. Balance between data freshness and cost efficiency for most operations.

    Low-Volume or Selective Outreach

    Refresh annually minimum. Even occasional outreach suffers from severely outdated data.

    Data Maintenance Tactics

    • 1
      Remove hard bounces immediately

      Do not keep emailing invalid addresses. It hurts your sender score.

    • 2
      Track disconnected numbers

      Flag and remove numbers that return busy signals or are disconnected.

    • 3
      Use email verification services

      Before large campaigns, run lists through verification to catch invalid addresses.

    • 4
      Buy fresh data incrementally

      Instead of large annual purchases, buy smaller batches more frequently.

    Data Freshness Budget Planning

    Approach 1

    Not Recommended
    $1,000
    One-time annual purchase

    Buy once, use all year. By month 6, 15-20% of data is stale. By month 12, approaching 30%.

    Approach 2

    Better
    $500 x 2
    Semi-annual purchases

    Refresh mid-year. Data never gets older than 6 months. Same total spend, better average freshness.

    Approach 3

    Recommended
    $250 x 4
    Quarterly purchases

    Continuous refresh. Data never older than 3 months. Highest quality, same total investment.

    Section 7

    Setting Realistic Expectations

    What NOT to Expect

    • 100% accuracy from any data source. Even the best providers have some stale data.
    • Data that stays fresh forever. Every database degrades over time.
    • Zero bounces or wrong numbers. Some are inevitable regardless of data quality.
    • One-time data purchases lasting multiple years. Plan for ongoing refresh.

    What to Expect and Plan For

    • Fresh data from quality providers: 85-95% accuracy initially.
    • Monthly decay of 2-3% requiring ongoing maintenance.
    • Some bounces and wrong numbers as part of normal operations.
    • Need for regular data refreshes as part of your operational budget.

    The Positive Perspective

    Data decay sounds negative, but it also means opportunity. As your competitors' old data becomes stale, fresh data gives you an advantage. Businesses that have changed their contact info are now harder for others to reach. If you have updated information, you have less competition for their attention.

    Quick Reference: Expected Decay by Timeline

    1 Month
    ~97% valid
    3 Months
    ~92% valid
    6 Months
    ~85% valid
    12 Months
    ~72% valid
    24 Months
    ~52% valid

    These are cumulative estimates accounting for all decay factors. Your actual experience may vary based on industry and data type.

    Section 8

    Summary

    Data Decay Is Inevitable

    Business data degrades at approximately 2-3% per month on average. This is not a flaw in your data source. It is a fundamental characteristic of business information.

    Email Decays Fastest

    Email addresses have the highest decay rate at 22-30% annually. Phone numbers and physical addresses are more stable but still require maintenance.

    Business Closures Add Up

    About 20% of new businesses fail in year one, and roughly 50% fail within five years. This baseline closure rate means permanent data loss regardless of contact updates.

    Plan for Ongoing Refresh

    Treat data freshness as an operational expense, not a one-time purchase. Quarterly refreshes maintain the best data quality. At minimum, refresh annually.

    Understanding data decay transforms your expectations. When some leads do not connect, it is not necessarily a sign of bad data. It is the natural result of an ever-changing business landscape. Plan for it, budget for it, and manage it as part of your ongoing operations.

    The most successful outreach operations are not those with zero bounces. They are those that understand decay, maintain their data appropriately, and treat data quality as a continuous priority rather than a one-time purchase.

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