When Enrichment Provider Fallback Helps (And When It Just Wastes Credits)
The math behind LinkedIn enrichment fallback logic, when the extra credit cost pays off, when it doesn't, and a decision matrix for SDRs, recruiters, and agencies.
Fallback sounds like a straightforward improvement: if your primary provider doesn’t find a result, try a second one before giving up. More chances = more results. Why wouldn’t you always use it?
The answer is that fallback consumes additional credits — one per row where the primary provider returned nothing. On large lists where the primary provider already has strong coverage, the marginal gain per extra credit can be poor. On targeted high-value lists, it’s almost always worth it.
Here’s how to tell which situation you’re in.
What Fallback Actually Does
The LinkedIn Enricher add-on’s fallback logic works like this:
For each row:
1. Send LinkedIn URL to primary provider (Datagma)
2. If primary returns email → write result to sheet, done
3. If primary returns nothing → send same URL to secondary provider (LeadMagic)
4. If secondary returns email → write result to sheet, mark provider as "LeadMagic"
5. If secondary also returns nothing → mark row as not foundCredits are consumed at step 1 regardless of result, and again at step 3 only for rows where the primary provider found nothing.
If your primary provider has a 70% hit rate on your list, fallback adds credit costs for the remaining 30% of rows. Of those 30%, LeadMagic will typically find results for roughly 30–40% of them (based on typical provider overlap of ~60–70%).
The Math: Does Fallback Pay Off?
Let’s work through a concrete example with a 500-row list.
Without fallback:
| Step | Count | Credits used |
|---|---|---|
| Primary (Datagma) lookups | 500 | 500 |
| Emails found | 325 (65%) | — |
| Not found | 175 | — |
| Total credits | 500 | |
| Emails found | 325 | |
| Cost per result | 1.54 credits |
With fallback enabled:
| Step | Count | Credits used |
|---|---|---|
| Primary (Datagma) lookups | 500 | 500 |
| Primary results found | 325 | — |
| Fallback (LeadMagic) lookups | 175 | 175 |
| LeadMagic recovers ~35% of fallback rows | 61 | — |
| Total credits | 675 | |
| Emails found | 386 | |
| Cost per result | 1.75 credits |
Fallback added 61 emails (18.8% more results) at the cost of 175 additional credits. The cost-per-email went from 1.54 to 1.75 credits — a 13.6% increase in per-result cost for an 18.8% increase in results.
On most prospecting lists, that’s a positive trade.
When Fallback Is Worth It
High deal value. If each qualified contact is potentially worth thousands in pipeline, the cost difference between 1.54 and 1.75 credits per result is irrelevant. You want the maximum number of contacts.
Targeted lists where every contact matters. A 50-person list of specific executive targets is different from a 5,000-person bulk export. On the small targeted list, missing 10 people because you skipped fallback is a meaningful gap.
EMEA-heavy lists. Provider database coverage in Europe is patchier than US coverage. The gap between Datagma-alone and Datagma+LeadMagic is larger on EMEA lists — often 15–20 percentage points rather than 8–12.
Recruiter sourcing. In executive recruiting, each missed candidate profile that had a result is a real loss. Fallback is typically always worth enabling for recruitment use cases.
Agency list-building for clients. When the deliverable is a contact list, hit rate quality matters more than per-credit cost. Enable fallback and price the credits into your service cost.
When Fallback Is Not Worth It
Bulk commodity lists (1,000+ rows, low deal value). If you’re enriching a large generic export where a 60% hit rate is commercially acceptable, adding 30–40% to your credit spend for a marginal improvement may not make sense.
High-overlap lists. If your list is US enterprise SaaS — the segment where both Datagma and LeadMagic have strong coverage — their databases overlap more. The fallback recovery rate may be 20–25% instead of 35%, reducing the return on the extra credits.
Budget-constrained runs. If you’re working with a fixed monthly credit budget, you may choose to run more rows at the primary-only rate rather than fewer rows with fallback. This depends on whether breadth or depth matters more for your campaign.
Database Overlap: Why It Matters
The value of fallback depends entirely on how different the two providers’ databases are. If they had 100% overlap, fallback would cost extra credits with zero additional results. If they had 0% overlap, every row the primary missed would be recovered by the secondary.
Estimated overlap between Datagma and LeadMagic: 60–70% of confirmed results.
This means roughly 30–40% of what LeadMagic finds, Datagma doesn’t have — and vice versa. That’s a substantial non-overlap, which is why fallback consistently adds value rather than just consuming credits redundantly.
Credit Cost Model by List Size
| List size | Primary only (credits) | With fallback (credits, est.) | Extra results (est.) |
|---|---|---|---|
| 100 rows | 100 | 130–145 | +8–13 emails |
| 500 rows | 500 | 645–725 | +40–65 emails |
| 1,000 rows | 1,000 | 1,290–1,450 | +80–130 emails |
| 5,000 rows | 5,000 | 6,450–7,250 | +400–650 emails |
Estimates assume 65% primary hit rate and 35% fallback recovery rate from remaining rows.
Decision Matrix
| Your situation | Use fallback? |
|---|---|
| Enterprise sales, high deal value | Yes, always |
| Executive recruiting | Yes, always |
| EMEA-heavy list | Yes, always |
| US SaaS, mid-market volume | Yes (positive ROI) |
| Bulk generic export, 1,000+ rows, low deal value | Maybe — run a 100-row test first |
| Tight credit budget, need breadth over depth | No — run more rows without fallback |
| Agency with per-list delivery commitment | Yes — price credits into your rate |
Interaction With “Skip Already-Enriched Rows”
The “Skip already-enriched rows” checkbox in the add-on prevents re-processing rows that already have an email in the target column. This is independent of fallback.
If you have 500 rows and 200 already have emails from a previous run, enabling skip means only 300 rows are processed — saving 300 primary credits plus any associated fallback credits. Fallback only kicks in for the 300 rows that are actively enriched, not the skipped ones.
Using both options together is the correct configuration for re-running a list that was partially enriched in a previous session.
Recommended Configuration by Team Type
| Team type | Primary | Fallback | Skip enriched |
|---|---|---|---|
| B2B SDR (US market) | Datagma | LeadMagic enabled | Always on |
| Recruiter (EMEA sourcing) | LeadMagic | Datagma enabled | Always on |
| Recruiter (US sourcing) | Datagma | LeadMagic enabled | Always on |
| Agency (mixed geography) | Datagma | LeadMagic enabled | Always on |
| Budget-conscious bulk lists | Datagma | Disabled | Always on |
Configure fallback in the LinkedIn Enricher add-on in under a minute. LinkedIn Profile Enricher for Google Sheets →