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apollo-list-building

This skill should be used when the user asks to "build a list in Apollo", "use Apollo for list building", "search for prospects in Apollo", "create an outbound list with Apollo", "find contacts in Apollo", "build a prospecting list in Apollo", "use Apollo filters for outbound", "export leads from Apollo", "set up Apollo for list building", or any variation of using Apollo.io to build prospect lists for B2B SaaS outbound.

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Apollo List Building

Apollo.io combines list building, enrichment, email finding, and sequencing in one platform. For list building specifically, Apollo's strength is that you search, find, enrich, and verify in one step. No separate enrichment tool. No separate email finder. The search returns contacts with emails ready to sequence. This makes Apollo the fastest path from "I need a list" to "I'm sending emails."

The principle: Apollo's database is large (275M+ contacts) but not perfect. Treat Apollo as your primary data source for 80% of contacts, then fill gaps with a secondary tool (Hunter, Lusha, or manual LinkedIn research) for the 20% Apollo misses.

Apollo Search Strategy

The two search approaches

Approach	How it works	Best for
People search	Search for individual contacts by title, company filters, location	Finding specific personas. Building contact-level lists
Company search → People search	Find companies first, save to a list, then search people within those companies	ABM. When you need 3-5 contacts per named account

Recommended workflow: Use company search to build the account list. Then use people search filtered to that account list to find contacts. This mirrors the account-first approach from icp-list-from-linkedin-sales-nav skill.

Apollo Filters

People search filters

Filter	How to use	Example
Job titles	Enter specific titles. Use OR for variations	"VP Sales" OR "Head of Sales" OR "CRO"
Seniority	Select level: C-Suite, VP, Director, Manager, etc.	VP + Director for decision-maker lists
Department	Select function: Sales, Marketing, Operations, Engineering	Sales + Operations for RevOps-adjacent lists
Company headcount	Set range	51-200 employees
Industry	Select from Apollo's taxonomy	Software, Internet, Financial Services
Location (HQ)	Company headquarters location	United States, or specific states
Revenue	Company revenue range	$10M-$100M
Technologies	Filter by tech stack (based on job postings and web detection)	"Salesforce" or "HubSpot"
Funding	Filter by funding round, amount, date	Series B, raised in last 12 months
Company lists	Filter to a saved company list	"Q2 ABM Target Accounts"
Email status	Filter by email availability	"Verified" only (recommended for outbound)
Contact lists	Exclude contacts already in a list	Exclude "Already Contacted Q1"

Filter combination rules

Layer at least 3 filters. Title + company size + industry at minimum. Two filters produce lists too broad for effective outbound
Use "Verified" email filter. Apollo marks emails as Verified, Guessed, or No Email. Filter for Verified when building outbound lists. Guessed emails have higher bounce rates
Exclude existing lists. Before building a new list, exclude contacts from previous campaigns. This prevents re-contacting the same people
Use the "# Employees" filter, not "Revenue." Employee count is more reliably populated in Apollo than revenue. Revenue data is available for fewer companies

Company search filters

Filter	How to use	Example
Industry	Primary vertical	Software, Financial Services
Headcount	Employee count range	51-500
Location	HQ region	United States
Revenue	Annual revenue range	$5M-$50M
Technologies	Tools the company uses	Salesforce, HubSpot
Funding	Round type and recency	Series A-C, raised in last 6 months
Keywords	Company description keywords	"SaaS", "B2B", "sales engagement"
Growth signals	Headcount growth percentage	> 20% growth

Building a List: Step by Step

Step 1: Company search (if using account-first approach)

Apollo → Search → Companies
  Industry: Software
  Headcount: 51-500
  Location: United States
  Funding: Series A, B, C (last 12 months)
  Keywords: "B2B" OR "SaaS"
  ↓
Review results. Remove non-ICP companies
  ↓
Save to Company List: "Q2 Target Accounts - B2B SaaS"

Step 2: People search

Apollo → Search → People
  Job Titles: "VP Sales" OR "Head of Sales" OR "CRO" OR
              "Chief Revenue Officer"
  Seniority: VP, C-Suite
  Department: Sales
  Company Lists: "Q2 Target Accounts - B2B SaaS" (from Step 1)
  Email Status: Verified
  ↓
Review results (check 20 profiles for relevance)
  ↓
Save to People List: "Q2 VP Sales - B2B SaaS"

Step 3: Export or sequence directly

Option	How	When to use
Add to Apollo sequence	Select contacts → Add to Sequence	When using Apollo's built-in sequencing
Export to CSV	Select contacts → Export	When using Outreach, Salesloft, or Lemlist for sequencing
Sync to CRM	Apollo → CRM integration → push contacts	When loading directly into HubSpot or Salesforce

Step-by-step rules

Review 20 profiles before saving the full list. Click into 20 random results. Are they your ICP? Are the titles accurate? Are the companies real? If 4+ out of 20 are wrong, tighten filters
Save searches, not just lists. A saved search can be re-run later to find new contacts that match the same criteria. A saved list is static. Use both: saved search for ongoing prospecting, saved list for a specific campaign
Export includes email. Apollo exports include the verified email, saving the enrichment step that Sales Nav exports require. This is Apollo's key advantage for outbound

Apollo Credits and Cost Management

How credits work

Action	Credit cost
View contact details (email, phone)	1 credit per contact
Export contact	1 credit per contact (same credit as viewing)
Enrich a contact via API	1 credit
Send an email via Apollo sequencing	0 credits (included in plan)

Credit optimization

Strategy	How	Savings
Filter for "Verified" emails only	Avoid spending credits on contacts with no email or guessed email	15-25% credit savings
Exclude previously exported contacts	Don't re-export contacts you already have in CRM	10-20% savings
Use company search first, then people search	Narrow to ICP companies before viewing individual contacts	Avoids spending credits on contacts at non-ICP companies
Check CRM before Apollo	If the contact is already in your CRM with a verified email, don't use an Apollo credit	5-15% savings
Bulk select + export (not one-by-one)	Batch operations are more efficient than individual clicks	Time savings (same credit cost)

Credit rules

Basic plan: 900 credits/month. Enough for ~900 new contacts/month. If your team needs more, Professional plan has unlimited credits
Credits reset monthly. Unused credits don't roll over. Use them or lose them
Viewing a contact's details and exporting them uses the SAME credit. You don't pay twice. One credit = view + export
Apollo sequencing doesn't cost credits. Sending emails through Apollo sequences is included in all paid plans. Credits are only for data access

Apollo Data Quality

What to expect

Dimension	Apollo quality	What to watch for
Email accuracy	85-92% (verified emails)	Verify with NeverBounce/ZeroBounce before sending. Even "verified" has 8-15% error rate
Phone accuracy	75-85% (direct dials)	Lower than ZoomInfo. Test before relying on phone as a channel
Title accuracy	85-90%	Titles may be outdated. Cross-reference with LinkedIn for senior prospects
Company data (size, industry)	80-90%	Generally reliable. Revenue data less complete than employee count
Personal email contamination	5-10%	Apollo sometimes returns @gmail/@yahoo alongside or instead of work email. Filter these out
International data (outside US/EU)	50-70% coverage	Thinner coverage in APAC, LATAM, MEA. Plan for lower find rates

Data quality rules

Always verify emails before sequencing. Apollo's "verified" status is not the same as a third-party verification. Run through NeverBounce or ZeroBounce before sending
Filter out personal emails. Before exporting, check for @gmail.com, @yahoo.com, @outlook.com in the results. Remove these from outbound lists
Cross-reference titles for VP+ contacts. A title in Apollo might be 6 months outdated. For senior contacts ($50K+ deals), spot-check on LinkedIn
International lists need a secondary source. Apollo's US/EU coverage is strong. For APAC or LATAM, expect 50-70% find rate and supplement with region-specific tools or manual research

Apollo Saved Searches and Alerts

Setting up saved searches

1. Run a people search with your ICP filters
2. Click "Save Search" → name it descriptively
   Example: "VP Sales - B2B SaaS - 51-500 emp - US - Series A-C"
3. Enable notifications for new results
4. Apollo emails you when new contacts match the search

Saved search strategies

Strategy	How to set up	What it catches
New ICP contacts	Save your core ICP search. Check weekly for new results	People who changed jobs into ICP titles/companies
Funding signal	Company search: funded in last 30 days + ICP criteria	Newly funded companies that match ICP
Hiring signal	Company search: headcount growth > 20% in last 90 days	Growing companies with implied tool needs
New contacts at target accounts	People search filtered to saved account list. Sort by "added to Apollo"	New hires at accounts you're already targeting

Saved search rules

Name searches descriptively. "Search 4" tells you nothing. "VP Sales - Series B SaaS - US - Q2" tells you everything
Review saved searches weekly. New results accumulate. Check weekly, add to your outbound list, then mark as reviewed
Update saved searches quarterly. ICP evolves. Title patterns change. A search from 6 months ago may be returning stale criteria. Refresh
Maximum 5-8 active saved searches. More than 8 creates alert fatigue. Focus on the searches that produce the highest-quality results

Apollo + CRM Integration

HubSpot integration

Feature	How it works
Contact sync	Apollo contacts push to HubSpot as contacts. Dedup on email
Company sync	Apollo companies push to HubSpot as companies. Dedup on domain
Activity sync	Apollo email activities sync to HubSpot contact timeline
Two-way sync	Changes in HubSpot reflect in Apollo and vice versa
Enrichment	Apollo enriches existing HubSpot contacts with missing data

Salesforce integration

Feature	How it works
Lead/Contact push	Apollo contacts push as Leads or Contacts (configurable)
Account sync	Apollo companies push as Accounts
Activity logging	Apollo email opens, clicks, replies logged to SFDC
Campaign sync	Apollo sequences map to Salesforce campaigns

Integration rules

Set up CRM integration before building lists. If contacts go to Apollo first and CRM second, you risk duplicates and data mismatches. Configure the sync from Day 1
Map Apollo fields to CRM fields explicitly. Apollo "Job Title" → HubSpot "Job Title." Apollo "Company Size" → HubSpot "Number of Employees." Don't rely on auto-mapping
Set dedup rules. Match on email for contacts. Match on domain for companies. Without dedup rules, every Apollo export creates duplicates in CRM
Tag Apollo-sourced contacts. Set a "Lead Source" or "Data Source" field to "Apollo" for every contact pushed from Apollo. This enables source-level quality tracking

Apollo for Different Campaign Types

Signal-based campaign

Company search:
  Funding: Series B, raised in last 90 days
  Industry: Software
  Headcount: 51-500
  Location: US
  ↓
Save companies → "Recently Funded B2B SaaS"
  ↓
People search within that list:
  Titles: "VP Sales" OR "Head of Revenue" OR "CRO"
  Email status: Verified
  ↓
Export → verify → sequence with funding signal angle

Persona-based campaign

People search:
  Titles: "Revenue Operations" OR "RevOps" OR "Sales Operations"
  Seniority: Manager, Director, VP
  Company headcount: 51-500
  Industry: Software, Internet
  Location: US
  Email status: Verified
  ↓
Save as list → "RevOps Leaders - B2B SaaS - US"
Export → verify → sequence with RevOps-specific angle

ABM account list

Company search → manually review and save target accounts
  OR
Upload a CSV of target account domains → Apollo matches
  ↓
People search within the matched account list:
  Titles: Champion + Economic Buyer + Technical Evaluator
  3-5 contacts per account
  ↓
Save → export → verify → multichannel ABM cadence

Pre-Export Checklist

[ ] Filters layered: at least title + company size + industry
[ ] "Verified" email filter applied
[ ] Previous campaign lists excluded (no re-contacting)
[ ] Customer domain list excluded (no cold-emailing existing customers)
[ ] Competitor domains excluded
[ ] 20 profiles spot-checked for ICP relevance
[ ] Personal emails (@gmail, @yahoo) filtered or flagged
[ ] Search saved for future re-runs
[ ] Export tagged with campaign name and date
[ ] Plan to verify emails with NeverBounce/ZeroBounce before sequencing

Measurement

Metric	Target	What it tells you
ICP match rate (from spot-check)	> 85% of exported contacts match ICP	Filter precision
Email verified rate	> 80% of contacts have Apollo "Verified" email	Apollo data coverage for your ICP
Post-verification valid rate	> 85% of Apollo "Verified" emails pass third-party verification	Apollo email accuracy
Bounce rate on first send	< 3%	Combined data + verification quality
Reply rate from Apollo-sourced lists	> 5% (Tier 3), > 8% (Tier 2)	Overall list + copy quality
Credits used per qualified contact	< 1.5 credits (accounting for non-ICP contacts viewed)	Credit efficiency
Personal email contamination rate	< 5% of exported list	Data hygiene

Anti-Pattern Check

Exporting 5,000 contacts with 2 filters. Title "Sales" + Location "US" returns millions of results. 5,000 of them will include retail sales associates, car salespeople, and SDR interns. Layer at least 3 filters. Quality over volume
Not filtering for "Verified" email status. Apollo contacts without verified emails have 20-40% bounce rates. Filter for Verified. The list will be smaller but usable
Skipping third-party email verification. Apollo's "Verified" still has an 8-15% error rate. Run every Apollo email through NeverBounce or ZeroBounce before sending. The $15-30 cost per 1,000 verifications prevents domain reputation damage
Building lists without excluding previous campaigns. Prospect receives the same cold email from 3 different campaigns over 2 months. Exclude previous campaign lists from every new search
Not excluding customers and competitors. A cold email to a paying customer or a competitor's employee is embarrassing. Upload customer and competitor domain lists as exclusions
Using Apollo's phone data without testing. Apollo's phone accuracy (75-85%) is lower than its email accuracy. Test a sample of 20 phone numbers before building a phone-heavy cadence from Apollo data
One giant search instead of persona-specific searches. "VP Sales" and "RevOps Manager" are different personas with different messaging. Build separate lists for separate personas. Each gets its own search, its own list, and its own sequence
Never re-running saved searches. The saved search finds new contacts every week (job changes, new hires, newly added profiles). Not checking it weekly means missing fresh prospects. Review saved searches weekly

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# Apollo List Building

## Apollo Search Strategy

### The two search approaches

| Approach | How it works | Best for |
|----------|-------------|----------|
| People search | Search for individual contacts by title, company filters, location | Finding specific personas. Building contact-level lists |
| Company search → People search | Find companies first, save to a list, then search people within those companies | ABM. When you need 3-5 contacts per named account |

**Recommended workflow:** Use company search to build the account list. Then use people search filtered to that account list to find contacts. This mirrors the account-first approach from icp-list-from-linkedin-sales-nav skill.

---

## Apollo Filters

### People search filters

| Filter | How to use | Example |
|--------|-----------|---------|
| Job titles | Enter specific titles. Use OR for variations | "VP Sales" OR "Head of Sales" OR "CRO" |
| Seniority | Select level: C-Suite, VP, Director, Manager, etc. | VP + Director for decision-maker lists |
| Department | Select function: Sales, Marketing, Operations, Engineering | Sales + Operations for RevOps-adjacent lists |
| Company headcount | Set range | 51-200 employees |
| Industry | Select from Apollo's taxonomy | Software, Internet, Financial Services |
| Location (HQ) | Company headquarters location | United States, or specific states |
| Revenue | Company revenue range | $10M-$100M |
| Technologies | Filter by tech stack (based on job postings and web detection) | "Salesforce" or "HubSpot" |
| Funding | Filter by funding round, amount, date | Series B, raised in last 12 months |
| Company lists | Filter to a saved company list | "Q2 ABM Target Accounts" |
| Email status | Filter by email availability | "Verified" only (recommended for outbound) |
| Contact lists | Exclude contacts already in a list | Exclude "Already Contacted Q1" |

### Filter combination rules

- **Layer at least 3 filters.** Title + company size + industry at minimum. Two filters produce lists too broad for effective outbound
- **Use "Verified" email filter.** Apollo marks emails as Verified, Guessed, or No Email. Filter for Verified when building outbound lists. Guessed emails have higher bounce rates
- **Exclude existing lists.** Before building a new list, exclude contacts from previous campaigns. This prevents re-contacting the same people
- **Use the "# Employees" filter, not "Revenue."** Employee count is more reliably populated in Apollo than revenue. Revenue data is available for fewer companies

### Company search filters

| Filter | How to use | Example |
|--------|-----------|---------|
| Industry | Primary vertical | Software, Financial Services |
| Headcount | Employee count range | 51-500 |
| Location | HQ region | United States |
| Revenue | Annual revenue range | $5M-$50M |
| Technologies | Tools the company uses | Salesforce, HubSpot |
| Funding | Round type and recency | Series A-C, raised in last 6 months |
| Keywords | Company description keywords | "SaaS", "B2B", "sales engagement" |
| Growth signals | Headcount growth percentage | > 20% growth |

---

## Building a List: Step by Step

### Step 1: Company search (if using account-first approach)

```
Apollo → Search → Companies
  Industry: Software
  Headcount: 51-500
  Location: United States
  Funding: Series A, B, C (last 12 months)
  Keywords: "B2B" OR "SaaS"
  ↓
Review results. Remove non-ICP companies
  ↓
Save to Company List: "Q2 Target Accounts - B2B SaaS"
```

### Step 2: People search

```
Apollo → Search → People
  Job Titles: "VP Sales" OR "Head of Sales" OR "CRO" OR
              "Chief Revenue Officer"
  Seniority: VP, C-Suite
  Department: Sales
  Company Lists: "Q2 Target Accounts - B2B SaaS" (from Step 1)
  Email Status: Verified
  ↓
Review results (check 20 profiles for relevance)
  ↓
Save to People List: "Q2 VP Sales - B2B SaaS"
```

### Step 3: Export or sequence directly

| Option | How | When to use |
|--------|-----|-------------|
| Add to Apollo sequence | Select contacts → Add to Sequence | When using Apollo's built-in sequencing |
| Export to CSV | Select contacts → Export | When using Outreach, Salesloft, or Lemlist for sequencing |
| Sync to CRM | Apollo → CRM integration → push contacts | When loading directly into HubSpot or Salesforce |

### Step-by-step rules

- **Review 20 profiles before saving the full list.** Click into 20 random results. Are they your ICP? Are the titles accurate? Are the companies real? If 4+ out of 20 are wrong, tighten filters
- **Save searches, not just lists.** A saved search can be re-run later to find new contacts that match the same criteria. A saved list is static. Use both: saved search for ongoing prospecting, saved list for a specific campaign
- **Export includes email.** Apollo exports include the verified email, saving the enrichment step that Sales Nav exports require. This is Apollo's key advantage for outbound

---

## Apollo Credits and Cost Management

### How credits work

| Action | Credit cost |
|--------|------------|
| View contact details (email, phone) | 1 credit per contact |
| Export contact | 1 credit per contact (same credit as viewing) |
| Enrich a contact via API | 1 credit |
| Send an email via Apollo sequencing | 0 credits (included in plan) |

### Credit optimization

| Strategy | How | Savings |
|----------|-----|---------|
| Filter for "Verified" emails only | Avoid spending credits on contacts with no email or guessed email | 15-25% credit savings |
| Exclude previously exported contacts | Don't re-export contacts you already have in CRM | 10-20% savings |
| Use company search first, then people search | Narrow to ICP companies before viewing individual contacts | Avoids spending credits on contacts at non-ICP companies |
| Check CRM before Apollo | If the contact is already in your CRM with a verified email, don't use an Apollo credit | 5-15% savings |
| Bulk select + export (not one-by-one) | Batch operations are more efficient than individual clicks | Time savings (same credit cost) |

### Credit rules

- **Basic plan: 900 credits/month.** Enough for ~900 new contacts/month. If your team needs more, Professional plan has unlimited credits
- **Credits reset monthly.** Unused credits don't roll over. Use them or lose them
- **Viewing a contact's details and exporting them uses the SAME credit.** You don't pay twice. One credit = view + export
- **Apollo sequencing doesn't cost credits.** Sending emails through Apollo sequences is included in all paid plans. Credits are only for data access

---

## Apollo Data Quality

### What to expect

| Dimension | Apollo quality | What to watch for |
|-----------|-------------|-------------------|
| Email accuracy | 85-92% (verified emails) | Verify with NeverBounce/ZeroBounce before sending. Even "verified" has 8-15% error rate |
| Phone accuracy | 75-85% (direct dials) | Lower than ZoomInfo. Test before relying on phone as a channel |
| Title accuracy | 85-90% | Titles may be outdated. Cross-reference with LinkedIn for senior prospects |
| Company data (size, industry) | 80-90% | Generally reliable. Revenue data less complete than employee count |
| Personal email contamination | 5-10% | Apollo sometimes returns @gmail/@yahoo alongside or instead of work email. Filter these out |
| International data (outside US/EU) | 50-70% coverage | Thinner coverage in APAC, LATAM, MEA. Plan for lower find rates |

### Data quality rules

- **Always verify emails before sequencing.** Apollo's "verified" status is not the same as a third-party verification. Run through NeverBounce or ZeroBounce before sending
- **Filter out personal emails.** Before exporting, check for @gmail.com, @yahoo.com, @outlook.com in the results. Remove these from outbound lists
- **Cross-reference titles for VP+ contacts.** A title in Apollo might be 6 months outdated. For senior contacts ($50K+ deals), spot-check on LinkedIn
- **International lists need a secondary source.** Apollo's US/EU coverage is strong. For APAC or LATAM, expect 50-70% find rate and supplement with region-specific tools or manual research

---

## Apollo Saved Searches and Alerts

### Setting up saved searches

```
1. Run a people search with your ICP filters
2. Click "Save Search" → name it descriptively
   Example: "VP Sales - B2B SaaS - 51-500 emp - US - Series A-C"
3. Enable notifications for new results
4. Apollo emails you when new contacts match the search
```

### Saved search strategies

| Strategy | How to set up | What it catches |
|---------|-------------|----------------|
| New ICP contacts | Save your core ICP search. Check weekly for new results | People who changed jobs into ICP titles/companies |
| Funding signal | Company search: funded in last 30 days + ICP criteria | Newly funded companies that match ICP |
| Hiring signal | Company search: headcount growth > 20% in last 90 days | Growing companies with implied tool needs |
| New contacts at target accounts | People search filtered to saved account list. Sort by "added to Apollo" | New hires at accounts you're already targeting |

### Saved search rules

- **Name searches descriptively.** "Search 4" tells you nothing. "VP Sales - Series B SaaS - US - Q2" tells you everything
- **Review saved searches weekly.** New results accumulate. Check weekly, add to your outbound list, then mark as reviewed
- **Update saved searches quarterly.** ICP evolves. Title patterns change. A search from 6 months ago may be returning stale criteria. Refresh
- **Maximum 5-8 active saved searches.** More than 8 creates alert fatigue. Focus on the searches that produce the highest-quality results

---

## Apollo + CRM Integration

### HubSpot integration

| Feature | How it works |
|---------|-------------|
| Contact sync | Apollo contacts push to HubSpot as contacts. Dedup on email |
| Company sync | Apollo companies push to HubSpot as companies. Dedup on domain |
| Activity sync | Apollo email activities sync to HubSpot contact timeline |
| Two-way sync | Changes in HubSpot reflect in Apollo and vice versa |
| Enrichment | Apollo enriches existing HubSpot contacts with missing data |

### Salesforce integration

| Feature | How it works |
|---------|-------------|
| Lead/Contact push | Apollo contacts push as Leads or Contacts (configurable) |
| Account sync | Apollo companies push as Accounts |
| Activity logging | Apollo email opens, clicks, replies logged to SFDC |
| Campaign sync | Apollo sequences map to Salesforce campaigns |

### Integration rules

- **Set up CRM integration before building lists.** If contacts go to Apollo first and CRM second, you risk duplicates and data mismatches. Configure the sync from Day 1
- **Map Apollo fields to CRM fields explicitly.** Apollo "Job Title" → HubSpot "Job Title." Apollo "Company Size" → HubSpot "Number of Employees." Don't rely on auto-mapping
- **Set dedup rules.** Match on email for contacts. Match on domain for companies. Without dedup rules, every Apollo export creates duplicates in CRM
- **Tag Apollo-sourced contacts.** Set a "Lead Source" or "Data Source" field to "Apollo" for every contact pushed from Apollo. This enables source-level quality tracking

---

## Apollo for Different Campaign Types

### Signal-based campaign

```
Company search:
  Funding: Series B, raised in last 90 days
  Industry: Software
  Headcount: 51-500
  Location: US
  ↓
Save companies → "Recently Funded B2B SaaS"
  ↓
People search within that list:
  Titles: "VP Sales" OR "Head of Revenue" OR "CRO"
  Email status: Verified
  ↓
Export → verify → sequence with funding signal angle
```

### Persona-based campaign

```
People search:
  Titles: "Revenue Operations" OR "RevOps" OR "Sales Operations"
  Seniority: Manager, Director, VP
  Company headcount: 51-500
  Industry: Software, Internet
  Location: US
  Email status: Verified
  ↓
Save as list → "RevOps Leaders - B2B SaaS - US"
Export → verify → sequence with RevOps-specific angle
```

### ABM account list

```
Company search → manually review and save target accounts
  OR
Upload a CSV of target account domains → Apollo matches
  ↓
People search within the matched account list:
  Titles: Champion + Economic Buyer + Technical Evaluator
  3-5 contacts per account
  ↓
Save → export → verify → multichannel ABM cadence
```

---

## Pre-Export Checklist

- [ ] Filters layered: at least title + company size + industry
- [ ] "Verified" email filter applied
- [ ] Previous campaign lists excluded (no re-contacting)
- [ ] Customer domain list excluded (no cold-emailing existing customers)
- [ ] Competitor domains excluded
- [ ] 20 profiles spot-checked for ICP relevance
- [ ] Personal emails (@gmail, @yahoo) filtered or flagged
- [ ] Search saved for future re-runs
- [ ] Export tagged with campaign name and date
- [ ] Plan to verify emails with NeverBounce/ZeroBounce before sequencing

---

## Measurement

| Metric | Target | What it tells you |
|--------|--------|------------------|
| ICP match rate (from spot-check) | > 85% of exported contacts match ICP | Filter precision |
| Email verified rate | > 80% of contacts have Apollo "Verified" email | Apollo data coverage for your ICP |
| Post-verification valid rate | > 85% of Apollo "Verified" emails pass third-party verification | Apollo email accuracy |
| Bounce rate on first send | < 3% | Combined data + verification quality |
| Reply rate from Apollo-sourced lists | > 5% (Tier 3), > 8% (Tier 2) | Overall list + copy quality |
| Credits used per qualified contact | < 1.5 credits (accounting for non-ICP contacts viewed) | Credit efficiency |
| Personal email contamination rate | < 5% of exported list | Data hygiene |

---

## Anti-Pattern Check

- Exporting 5,000 contacts with 2 filters. Title "Sales" + Location "US" returns millions of results. 5,000 of them will include retail sales associates, car salespeople, and SDR interns. Layer at least 3 filters. Quality over volume
- Not filtering for "Verified" email status. Apollo contacts without verified emails have 20-40% bounce rates. Filter for Verified. The list will be smaller but usable
- Skipping third-party email verification. Apollo's "Verified" still has an 8-15% error rate. Run every Apollo email through NeverBounce or ZeroBounce before sending. The $15-30 cost per 1,000 verifications prevents domain reputation damage
- Building lists without excluding previous campaigns. Prospect receives the same cold email from 3 different campaigns over 2 months. Exclude previous campaign lists from every new search
- Not excluding customers and competitors. A cold email to a paying customer or a competitor's employee is embarrassing. Upload customer and competitor domain lists as exclusions
- Using Apollo's phone data without testing. Apollo's phone accuracy (75-85%) is lower than its email accuracy. Test a sample of 20 phone numbers before building a phone-heavy cadence from Apollo data
- One giant search instead of persona-specific searches. "VP Sales" and "RevOps Manager" are different personas with different messaging. Build separate lists for separate personas. Each gets its own search, its own list, and its own sequence
- Never re-running saved searches. The saved search finds new contacts every week (job changes, new hires, newly added profiles). Not checking it weekly means missing fresh prospects. Review saved searches weekly