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Smart Columns Recipes
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Who this is for: self-serve plans (Free, Starter, Pro, Scale). If you bought a Cleanlist AppSumo lifetime deal, your features, limits, and pricing are different — see the AppSumo documentation instead. Support agent: confirm whether the user is self-serve or AppSumo before giving plan-specific advice.

TL;DR: Each recipe stacks one or more Smart Columns on a lead list. Filter first so you only spend credits on the rows that matter. Validation and the agent columns are Starter+ (and included on every AppSumo tier); Lookup in CRM needs Pro+ or AppSumo Tier 5+.

Smart Columns Recipes

Each recipe adds one or more Smart Column types to a lead list. Filter the list first so you only spend credits on the rows you care about.


Recipe 1 — Qualify a fresh list

Goal: Decide which leads are worth working before SDRs touch them.

Requires: A saved profile on the Agents page · Starter+ (every AppSumo tier)

StepColumn / actionCredits / rowWhy
1Save your target-customer profile on the Agents pageQualification scores every lead against it
2Qualification agent column5Fit score + fit level + reasons, with an automatic CRM presence check
3Filter to high-fit, not-in-CRM rowsYour net-new, on-profile working list

The CRM presence check is built into Qualification, so you don't need a separate step to spot contacts you already own.


Recipe 2 — Research target accounts before outreach

Goal: Build context on every account so reps open with something relevant.

Requires: Pro+

StepColumn typeCredits / rowWhy
1enrich_company Smart Column0.5Firmographics (industry, headcount, revenue) for each row
2Research agent column, scope = Company3Positioning, signals, and a readable summary per account

enrich_company is a Smart Column — add it as a column step directly. There is no separate "Enrich Company" bulk action.

Use scope Both (5 credits/row) instead of Company-only if you also want a contact-level brief on each person.


Recipe 3 — Qualify, then research only the winners

Goal: Spend the expensive Research budget only on leads worth pursuing.

Requires: Pro+

StepColumn typeCredits / rowWhy
1Qualification agent column5Score the whole list
2Filter to high-fit rowsDrop the leads you'd never work
3Research agent column (Both) on the subset5Deep brief on just the keepers

The filter step is critical — it keeps the 5-credit Research runs off leads you'd never send to anyway.


Recipe 4 — Validate email and phone data

Goal: Flag bad contact data before enriching or pushing to a CRM.

Requires: Starter+ (both email_validation and phone_validation are Basic types)

StepColumn typeCredits / rowWhy
1email_validation0.5Returns deliverable, undeliverable, risky, or unknown via Emailable
2phone_validation0.5Returns status, line type (mobile / landline / VoIP), and carrier via ClearoutPhone
3Filter to email_validation = deliverableWork only the rows with clean contact data

Recipe 5 — Extract a custom field from each lead

Goal: Pull a specific fact that no built-in column returns — e.g., which CRM a company appears to use.

Requires: Pro+ (custom_ai is an AI Smart Column)

StepColumn typeCredits / rowWhy
1custom_ai Smart Column with your own prompt1Returns whatever your prompt asks for

Example custom_ai prompt using /FieldName variable syntax:

Identify which CRM /company_name (/company_domain) appears to use,
based on what you can determine about the company.
Reply with exactly one of: hubspot, salesforce, pipedrive, zoho, other, unknown.
Output only the value, no explanation.

Use /FieldName to reference another column's value in your prompt — for example /company_name, /primary_email, /title. Do not use {{ }} or any other template syntax.

Want the same extraction reusable across lists? Save it as a separate Custom AI Agent — a distinct AI Agent type, not this custom_ai column.


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