How Cleanlist's Playbook Builder Automates Your Sales Pipeline

Most GTM teams spend their mornings the same way. Export a list. Clean it in a spreadsheet. Enrich one provider at a time. Copy-paste results into the CRM. Score leads manually. Route them to reps.

That is four hours of work before anyone sends a single email.

Agents eliminate all of it. You define a series of data operations once (enrich, verify, score, route) and Cleanlist AI runs it automatically every time new leads enter your pipeline. No spreadsheets. No manual handoffs. Just clean, scored, routed leads ready for outreach.

This guide walks through five ready-to-use agents, shows you how to build custom ones, and shares the results teams are seeing.

What Is a Cleanlist AI Agent?

An agent is a workflow engine inside Cleanlist AI that does one sales job on its own. Think of it as an "if this, then that" system purpose-built for B2B data operations.

Each agent runs a play, a series of steps:

You connect these steps in any order. The agent runs top to bottom whenever it is triggered (manually, on a schedule, or via API) and posts each run to Slack.

The key advantage: consistency. Every lead goes through the same process. No reps skipping verification. No managers wondering why half the list has missing phone numbers.

Why Your GTM Team Needs Agents

Manual data work is the silent killer of pipeline velocity. Here is what it actually costs your team:

Time: The average SDR spends 5-8 hours per week on data tasks. That is 25-40% of their selling time gone.

Quality: Manual processes create inconsistency. One rep verifies emails. Another skips it. A third enriches phone numbers but forgets firmographics. The result is a pipeline where data quality varies by rep.

Speed: Every hour between lead capture and first touch reduces conversion rates. If your outbound team takes two days to clean and enrich a new list, competitors who automate it reach those prospects first.

Scale: Manual processes break when volume increases. Doubling your lead flow should not mean doubling your ops headcount.

Agents solve all four problems. Define the process once, and every lead gets the same enrichment, verification, and scoring - in minutes, not days.

5 Ready-to-Use Agents

These agents cover the most common GTM workflows. Each one is available as a template in the agent library: select it, customize the settings, and run.

1. Outbound Prospecting Agent

Use case: You have a raw list of target prospects. You need verified contact data, ICP scores, and CRM-ready records.

Steps:

1. Enrich contacts - Run waterfall enrichment to fill emails, phones, job titles, and firmographics from 25+ data sources
2. Verify emails - Check deliverability status (valid, risky, catch-all, invalid)
3. Score against ICP - Rate each lead on company fit, title match, and seniority
4. Filter - Remove invalid emails and leads scoring below 50
5. Route - Push Tier 1 leads (score 80+) to your sales team's priority queue, Tier 2 (50-79) to nurture sequences

Expected outcome: A cleaned, scored list where 70-85% of records have verified emails and your reps only see leads worth pursuing.

2. ABM Target Account Agent

Use case: You have a list of target accounts for an ABM campaign. You need to identify the right contacts at each company, enrich them, and score for fit.

Steps:

1. Enrich company data - Fill firmographics (size, revenue, industry, tech stack) for each target account
2. Find contacts - Identify decision-makers matching your buyer persona at each account
3. Enrich contacts - Run waterfall enrichment on discovered contacts
4. Score - Apply ICP scoring with heavy weight on account-level fit
5. Route - Group contacts by account and push to your ABM platform or CRM

Expected outcome: 3-5 verified, scored contacts per target account, ready for multi-threaded outreach.

3. Event Follow-Up Agent

Use case: You collected badge scans or signup forms at a conference. The data is messy - partial names, personal emails, missing company info.

Steps:

1. Deduplicate - Remove duplicate records from badge scan data
2. Enrich - Fill company name, work email, job title, and phone from partial inputs
3. Verify - Validate all emails for deliverability
4. Score - Rate against ICP to prioritize high-value attendees
5. Route - Send high-fit leads to sales for personal follow-up, rest to a marketing nurture campaign

Expected outcome: Event leads enriched and routed within hours of the event ending - not days.

4. CRM Cleanup Agent

Use case: Your CRM has thousands of records with missing fields, outdated titles, and unverified emails. You need to fix it without manual work.

Steps:

1. Export stale records - Pull contacts not updated in 90+ days
2. Re-enrich - Run waterfall enrichment to refresh job titles, companies, and contact data
3. Verify emails - Check which emails are still deliverable
4. Flag changes - Identify contacts who changed jobs or companies
5. Update CRM - Push refreshed data back, archive contacts with invalid data

Expected outcome: 20-40% of stale records updated with current data. Bounce-prone emails flagged before they damage your domain reputation.

5. Win-Back Campaign Agent

Use case: You want to re-engage closed-lost deals and churned customers. But their contact data may be outdated.

Steps:

1. Export closed-lost and churned records - Pull from CRM with original close/churn date
2. Re-enrich contacts - Update job titles, companies, and emails (many will have changed roles)
3. Verify - Confirm email deliverability for refreshed records
4. Score - Re-score against current ICP criteria (their company may have grown or changed)
5. Segment - Split into "same company, new role" vs. "new company" vs. "same role, same company"
6. Route - Push to tailored win-back sequences based on segment

Expected outcome: 15-25% of win-back contacts have new, actionable data. Segmented outreach converts 2-3x better than a generic "checking in" email.

How to Build a Custom Agent

The five templates above cover common workflows. But your team's process may be unique. Here is how to build a custom agent from scratch. You can also tell Clu the job in one sentence and it drafts the agent for you.

Step 1: Define the trigger

Every agent starts with a trigger - the event that kicks off the workflow.

Choose the trigger that matches your workflow. Most teams start with manual triggers, then move to automated ones once the agent is validated.

Step 2: Add enrichment steps

Add enrichment steps to the agent's play. Configure each one:

• Enrichment type: Partial (email + company data) or Full (add phone numbers)
• Data sources: Use all 25+ sources or restrict to specific providers
• Overwrite rules: Overwrite existing data, fill gaps only, or keep the freshest value

For most workflows, "fill gaps only" is the safest default. It enriches missing fields without overwriting data your team already verified.

Step 3: Add verification

After enrichment, add a verification step to validate the data:

• Email verification: Checks deliverability in real time
• Phone validation: Confirms format and carrier status
• Company matching: Cross-references company data against multiple sources

Step 4: Add scoring and filtering

Use ICP Scoring to rate every record. Then add filters to segment by score:

• Tier 1 (80-100): High-fit leads for immediate outreach
• Tier 2 (50-79): Moderate-fit leads for nurture
• Tier 3 (below 50): Low-fit leads to archive or deprioritize

Step 5: Configure routing

The final step: where do processed leads go?

• CRM: Push directly to Salesforce, HubSpot, or Pipedrive
• Sales engagement: Route to Outreach, Salesloft, or Apollo sequences
• Spreadsheet: Export as CSV for manual review
• Webhook: Send to any custom endpoint

Step 6: Test with a small batch

Before running an agent on your full list, test with 50-100 records. Check that:

• Enrichment fills the expected fields
• Verification flags the right records
• Scoring produces a reasonable distribution
• Routing sends records to the correct destination

Results You Can Expect

Teams using agents consistently report measurable improvements across four areas.

Time savings

Data quality

• Email deliverability: Teams see bounce rates drop from 15-25% to under 3% after adding verification steps
• Fill rates: Waterfall enrichment fills 85-95% of records compared to 60-70% from single-source tools
• Accuracy: ICP scoring removes 30-40% of leads that would have wasted rep time

Pipeline velocity

Faster data processing means faster first touch. Teams using agents reduce time-to-first-outreach from 2-3 days to under 4 hours. That speed advantage compounds - prospects are more likely to respond when your outreach arrives while their intent signals are still fresh.

Rep productivity

When reps stop doing data work, they sell more. Teams report 25-35% more selling time per rep after automating enrichment and scoring. For a 10-person SDR team, that is the equivalent of adding 2-3 more reps without the headcount cost.

Check our pricing page to see which plan includes agents and calculate your ROI based on team size.

Frequently Asked Questions

How many agents can I run?

Pro runs 5 active agents, on schedules and CRM triggers, and Enterprise runs unlimited agents. Most teams run 3-5 active agents covering outbound, inbound, ABM, and CRM maintenance.

Can I edit an agent after it has run?

Yes. Editing an agent only affects future runs. Past results are not changed. You can also duplicate an agent and modify the copy to A/B test different enrichment or scoring configurations.

What happens if enrichment fails for a record?

The agent continues processing remaining records. Failed records are flagged with the reason (no match found, insufficient input data, provider timeout). You are not charged credits for an email or phone number that is not found. You can re-run the agent on failed records after adding more input data.

Do agents work with my CRM?

Cleanlist AI integrates natively with Salesforce, HubSpot, and Pipedrive. For other CRMs, use the API or webhook routing step to push data to any endpoint. Zapier and Make integrations are also available for no-code connections.

How is this different from Zapier or Make automations?

General automation tools can move data between apps, but they lack native enrichment, verification, and scoring capabilities. You would need to stitch together 4-5 separate tools to replicate what one Cleanlist AI agent does natively. Agents are purpose-built for B2B data operations - enrichment, verification, and scoring are first-class steps, not bolt-on integrations.

Manual pipeline work is a solved problem. Agents let you define your GTM data process once and run it automatically on every list, every lead, every time. Build your first agent in under 10 minutes and see what your team can do when data work disappears from their calendar.