Real-Time vs Cached Data: Which is Better for B2B Enrichment? (2026)

Understanding the Difference

Real-Time Data

Real-time data is fetched directly from the source (like LinkedIn) at the moment you request it. When you call the API, it scrapes or accesses the current profile and returns what's live right now.

Example: You request a LinkedIn profile at 2:00 PM. The API fetches the profile from LinkedIn at 2:00 PM and returns the current data. If the person updated their job title at 1:55 PM, you'll see the new title.

Cached Data

Cached data comes from a pre-built database that's updated periodically (daily, weekly, or monthly). When you request a profile, you get a snapshot from the last time the database was refreshed.

Example: You request a LinkedIn profile at 2:00 PM. The API returns data from the database that was last updated 2 weeks ago. If the person changed jobs yesterday, you'll still see their old job.

Quick Comparison

When Real-Time Data Wins

1. Job Change Tracking

People change jobs frequently. In B2B sales, knowing someone just started a new role is a golden opportunity. Real-time data ensures you're reaching out with current information.

2. Competitive Intelligence

Monitoring competitor hiring, executive changes, or company updates requires current data. Cached data that's weeks old misses critical signals.

3. High-Value Accounts

For your top 100 target accounts, accuracy matters more than cost. Real-time data ensures your outreach is relevant and personalized with current information.

4. Compliance & Accuracy

Some industries require accurate, up-to-date information for compliance. Real-time data reduces the risk of contacting people who've left companies or changed roles.

5. Profile Monitoring

If you're tracking specific individuals for changes (promotions, job moves, skill updates), real-time data is essential. You want to know when changes happen, not weeks later.

When Cached Data Wins

1. Bulk Enrichment

Enriching 100,000 contacts? Cached data is faster and more cost-effective. Real-time enrichment at that scale would take days and cost significantly more.

2. Historical Analysis

Cached databases often include historical data—previous job titles, past companies, career progression. This context isn't available with real-time lookups.

3. Budget Constraints

Cached data is typically 5-10x cheaper per enrichment. If budget is tight and perfect accuracy isn't critical, cached data delivers better ROI.

4. Broad Market Research

Building lists of "all CTOs at SaaS companies in California" works better with cached databases. They're optimized for filtering and searching large datasets.

5. Low-Touch Campaigns

For mass email campaigns where personalization is minimal, cached data is sufficient. You don't need real-time accuracy for "Hi [FirstName]" emails.

The Staleness Problem

How quickly does B2B data become stale? Research shows:

• Job Changes: 30% of professionals change jobs every 2 years (15% per year)
• Email Addresses: 22.5% of email addresses decay annually
• Phone Numbers: 18% of phone numbers change each year
• Company Changes: Mergers, acquisitions, and rebrands affect 5-10% of companies annually

Impact on cached data:

• 1 month old: ~1-2% inaccuracy
• 3 months old: ~4-6% inaccuracy
• 6 months old: ~8-12% inaccuracy
• 1 year old: ~15-20% inaccuracy

For a database of 100,000 contacts that's 6 months old, 8,000-12,000 records are likely outdated. That's wasted outreach, bounced emails, and frustrated sales reps.

Performance Considerations

Real-Time Performance

Response times: 2-5 seconds per request (depends on source complexity)

Throughput: 10-50 requests per minute (rate limited by source)

Scalability: Challenging for bulk operations; best for on-demand enrichment

Cached Performance

Response times: Under 500ms per request

Throughput: 100-1000+ requests per minute

Scalability: Excellent for bulk operations; can enrich millions of records quickly

Cost Analysis

Real-Time Pricing

Cached Pricing

Key insight: Real-time and cached data can have similar costs per enrichment, but cached databases often require larger minimum commitments or annual contracts.

Hybrid Approach: Best of Both Worlds

Many companies use a hybrid strategy:

Strategy 1: Tiered Enrichment

• Hot leads (score 80+): Real-time enrichment for maximum accuracy
• Warm leads (score 50-79): Cached data, refresh if they engage
• Cold leads (score under 50): Cached data only

Strategy 2: Time-Based Refresh

• Initial enrichment with cached data (fast, cheap)
• Real-time refresh before sales outreach (accurate when it matters)
• Quarterly re-enrichment for active contacts

Strategy 3: Use Case Specific

• List building: Cached data for initial prospecting
• Outreach: Real-time verification before sending
• Monitoring: Real-time for key accounts and competitors
• Reporting: Cached data for analytics and dashboards

Decision Framework

Choose real-time data if:

• Accuracy is critical for your use case
• You're targeting high-value accounts
• You need to track changes over time
• Your volume is manageable (under 10,000 enrichments/month)
• You can tolerate slower response times
• Budget allows for higher per-enrichment costs

Choose cached data if:

• You need to enrich large volumes quickly
• Budget is constrained
• Perfect accuracy isn't critical
• You need historical data and career progression
• You're doing broad market research
• Response time is a priority

Real-World Examples