Find Mobile Numbers for a List of LinkedIn Profiles

This tutorial shows how to build a table that finds mobile phone numbers for a list of contacts using their LinkedIn URLs. It covers running multiple phone number sources in a Waterfall to maximize coverage.

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Before you begin

• Connect these integrations in Settings > Integrations:
  • BetterEnrich (primary mobile source)
  • Apollo (secondary mobile source)
  • LeadMagic (third source - for additional coverage)

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What you will build

A table that tries three mobile number sources in order and returns the best available number:

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Step 1: Create the table

1. Click New Table and name it Mobile Number Finder.
2. Import your list of LinkedIn URLs as a CSV, or paste them directly.
3. Name the first column LinkedIn URL.

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Step 2: Add BetterEnrich mobile finding

1. Click Add Column and select Action Column.
2. Search for and select Find Mobile Number by LinkedIn URL (BetterEnrich).
3. Map the LinkedIn URL column to the LinkedIn Profile URL input.
4. Select Phone Number as the output.
5. Click Save.

This action costs 10 credits per row.

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Step 3: Add Apollo as a fallback

1. Click Add Column and select Action Column.
2. Search for and select Find Mobile Number using LinkedIn URL (Apollo).
3. Map the LinkedIn URL column to the LinkedIn URL input.
4. Select Phone Number as output.
5. Click Save.

This action costs 2 credits per row.

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Step 4: Add LeadMagic as a second fallback

1. Click Add Column and select Action Column.
2. Search for and select Find Mobile Number by LinkedIn URL (LeadMagic).
3. Map the LinkedIn URL column to the LinkedIn URL input.
4. Select Phone Number as output.
5. Click Save.

This action costs 10 credits per row.

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Step 5: Build the final mobile formula

1. Click Add Column and select Formula Column.
2. Enter:

IF(betterenrich_mobile != "", betterenrich_mobile,
  IF(apollo_mobile != "", apollo_mobile,
    IF(leadmagic_mobile != "", leadmagic_mobile, "")
  )
)

3. Name this column Final Mobile.

This formula returns the first non-empty result from the three sources, in priority order.

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Step 6: Add a Normalize Phone formula

Phone numbers from different sources come in different formats. Normalize them before exporting:

1. Click Add Column and select Action Column.
2. Search for and select Normalize Phone Number (TexAu Utility).
3. Map Final Mobile as the Phone input.
4. Select Normalized Phone as the output.
5. Click Save.

This formats all numbers consistently (e.g. to E.164 format: +15105551234).

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Step 7: Run the table

1. Click Run All Rows.
2. After completion, filter by Final Mobile is not empty to see how many contacts have a number.

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Expected results

For a list of 100 LinkedIn profiles:

• BetterEnrich alone: typically 20-50% coverage
• BetterEnrich + Apollo: typically 30-60%
• BetterEnrich + Apollo + LeadMagic: typically 35-65%

Mobile number coverage is significantly lower than email coverage. Executives and sales-facing roles yield the highest hit rates. Developer, engineering, and non-client-facing roles tend to have lower mobile number availability.

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When to use mobile numbers vs email

Mobile numbers are most valuable for:

• Cold calling outreach
• SMS sequences
• WhatsApp outreach
• Verifying identity in high-value deals

For bulk outreach, email is more cost-effective. Reserve mobile enrichment for high-priority accounts or contacts where email outreach has not converted.

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Troubleshooting

All three sources return empty for the same contact. Mobile number availability is not guaranteed. If all three sources return empty, the contact's number is not in the available databases. No enrichment provider has complete global coverage. Accept that some contacts will not be reachable by mobile.

Numbers are returned in different formats from different sources. The Normalize Phone Number utility action solves this. Always run normalization before exporting or passing numbers to a dialer or sequencing tool.

BetterEnrich mobile costs are higher than expected. BetterEnrich mobile costs 10 credits per row regardless of whether a number is found. Run Apollo first (lower cost) and only run BetterEnrich on rows where Apollo returned empty. This requires running the table in two stages with a filter between them.