Why Two Providers Beat One: The Fallback Strategy Behind LinkedIn Enrichment
Using a single enrichment provider leaves emails on the table. Here's why dual-provider fallback consistently outperforms any single provider, and how to configure it correctly.
Every LinkedIn enrichment provider has a database. Every database has gaps. No single provider has complete coverage of every professional profile on the planet.
This is not a criticism of any specific tool — it’s a structural reality of how B2B data networks work. The practical implication: using a single provider means accepting its blind spots as your final result.
Dual-provider fallback is the solution. Here’s why it works and how to use it.
How Provider Databases Are Built
B2B enrichment providers build their databases through a combination of:
- Public profile data scraped and indexed over time
- Data partnerships with B2B contact vendors
- User-contributed data (from tools like email finders installed on users’ browsers)
- Business card and conference attendee data from third-party sources
- Email validation signals from outreach tools
Each provider’s coverage reflects the sources they’ve prioritized and the markets they’ve historically served. A provider that started in the US enterprise tech market will have stronger US tech coverage and thinner coverage in, say, European mid-market manufacturing.
This means two providers serving the same request will sometimes return completely different results — not because one is wrong, but because they’re drawing from different source pools.
What the Data Shows
We ran a test on 100 LinkedIn profile URLs through Datagma alone, LeadMagic alone, and both with fallback enabled. Full methodology and results are in our Datagma vs LeadMagic comparison →, but the headline numbers are:
| Setup | Emails found | Hit rate |
|---|---|---|
| Datagma only | 58 / 100 | 58% |
| LeadMagic only | 54 / 100 | 54% |
| Both with fallback | 71 / 100 | 71% |
The combined result isn’t the sum of both — the two providers share significant overlap (both had data on 41 of the 71 profiles found). But 30 profiles were found by only one provider. That’s the gap fallback fills.
The overlap rate of ~57% is typical for enterprise B2B providers. It’s low enough that fallback adds real value on virtually any list.
How Fallback Works in Practice
The fallback logic is straightforward:
- Submit row to primary provider
- If primary returns an email → write result, mark complete
- If primary returns nothing → submit row to secondary provider
- If secondary returns an email → write result, note it came from fallback
- If secondary also returns nothing → mark as not found
This is what the LinkedIn Enricher add-on does automatically when you have both providers configured. The Provider column in your results sheet tells you which provider found each email — useful for tracking which provider performs better on your specific list composition.
The Credit Math
Using fallback costs more credits than single-provider enrichment. Here’s the trade-off:
For a 100-row list where primary finds 58 and secondary is used for the remaining 42:
| Scenario | Credits used | Emails found | Cost per email |
|---|---|---|---|
| Primary only | 100 | 58 | 1.72 credits |
| Primary + fallback | 142 | 71 | 2.00 credits |
The combined approach costs 42% more credits (100 → 142) but returns 22% more emails (58 → 71). The cost-per-email increases only slightly: 1.72 → 2.00 credits.
For most B2B use cases, this is a good trade. Finding 13 additional contacts on a 100-person targeted list — contacts that would otherwise require manual research or LinkedIn InMail — is generally worth the incremental credit cost.
When the math doesn’t favor fallback:
- Very high-volume commodity lists where per-contact value is low
- Lists with known high coverage by a single provider (test with a 50-row sample first)
- Situations where per-credit cost is high and budget is tight
Choosing Which Provider to Use as Primary
The choice of primary provider affects which provider bears the full lookup cost (you pay both primary and fallback for rows where primary misses):
| List type | Recommended primary | Reason |
|---|---|---|
| US enterprise, large companies | Datagma | Stronger US coverage |
| EMEA-heavy lists | LeadMagic | Better European database |
| Mixed US + EMEA | Datagma | US volume usually dominates |
| SMB / small company contacts | LeadMagic | Better at non-corporate email patterns |
| Tech and SaaS roles | Datagma | Tech-heavy indexing |
| Marketing, HR, operations | LeadMagic | Slightly better on these functions |
Setting the stronger provider as primary means fewer rows go to fallback at all — which reduces total credit consumption. If you’re unsure, run 50 rows through each as primary and compare hit rates on your specific list before committing to a full batch.
When One Provider Is Enough
Fallback adds value when you care about maximizing hit rate. There are cases where single-provider enrichment makes more sense:
You only have one API key. You can’t configure fallback without credentials for both providers. Start with one; add the second when budget allows.
You’re testing list quality. Running a quick single-provider check on 50 rows to estimate list quality before full enrichment is reasonable. Single-provider is faster and cheaper for a calibration run.
Your list has highly predictable coverage. If previous batches have shown that 90%+ of your list type is covered by Provider A, the marginal value of fallback is lower.
The Hidden Benefit: Identifying Provider Strength on Your Specific List
Over time, watching the Provider column in your results gives you real data on which provider performs better for your specific use case:
- If 80% of results come from primary with minimal fallback recoveries → your primary provider is well-matched to your list type
- If fallback is recovering 25–35% → both providers are genuinely complementary for your list; keep both active
- If you’re getting high rates of “not found” even with both → the issue is list composition (non-indexed profiles), not provider choice
This data informs future decisions: which provider to renew credits on first, which to set as primary for specific list segments, and whether a third provider might be worth testing.
See the full test results for Datagma vs LeadMagic → Head-to-head comparison on 100 LinkedIn profiles →
Configure dual-provider fallback on your next enrichment run. LinkedIn Profile Enricher for Google Sheets →