Basic Data Validation for a B2B File

This module covers how to spot-check a sample of records using web search and LinkedIn to estimate what percentage of a list is still usable,
Basic Data Validation for a B2B File
Photo by Campaign Creators / Unsplash

Track: Outreach Operations
Estimated time: 9 minutes
Difficulty: Beginner

What this covers

Before we invest time enriching or submitting a legacy contact list for validation, we need to know whether the data is still worth anything.

This module covers how to spot-check a sample of records using web search and LinkedIn to estimate what percentage of a list is still usable — and what signals tell you a record is dead.

Step-by-step reference

Step 1 — Pull a sample of records

Open the legacy list. Do not try to check every record — that's not the goal here. Select a representative sample of 5–10 records spread across industries or segments if possible. You're building an estimate, not a full audit.

Step 2 — Run a quick web search on each contact

For each record, take the person's name and current (listed) company and drop them into Google search together. Scan the first page of results for:

  • Their current role and company
  • Any news about a job change, promotion, or departure
  • LinkedIn profile appearing in results (check it directly)
Cautionary note on AI summaries (Google/Bing overviews): These give you a useful first clue but are not definitive. Use them to form a hypothesis, then verify against the actual LinkedIn profile or company page. Never update a record based on an AI summary alone.

Step 3 — Check LinkedIn directly

Open the contact's LinkedIn profile. Look at:

SignalWhat it tells you
Current role + companyIs the listed data still accurate?
LocationHave they moved region or country?
"X VP" / "Former" labelsLikely retired or between roles
Recent activityActive profile = more reliable data

For senior contacts (Director and above), LinkedIn profiles are usually more complete and easier to verify.

Step 4 — Classify each record

As you work through the sample, assign each contact one of three statuses:

  • Good — Still at the listed company, role roughly the same, contact details likely still valid
  • Moved but trackable — Changed company or role, but still active and potentially a viable lead depending on ICP fit
  • Dead — Retired, relocated out of region, or profile data no longer matches the use case

Flag "moved but trackable" records in the sheet (bold, highlight, or a status column — use whatever convention is already in place). Do not delete them; they may be enrichable via Lusha.

Step 5 — Make the call on the full list

After working through your sample, estimate the percentage of records that fall into each category. Use this as your decision framework:

  • >50% good or trackable → Worth submitting the full list to a validation service (e.g. NeverBounce, ZeroBounce) to recover accurate emails and phone numbers
  • <50% good or trackable → Flag to Harry before proceeding; the list may not be worth the enrichment cost

Note: even a record with an accurate name and company is only partially useful. Email address and direct phone number are the critical data points for outreach — if those are likely stale (person left the company), the record needs re-enrichment regardless of everything else.

Rules + edge cases

If you can't find the person at all on LinkedIn or Google — that's useful signal too. Flag as "unverifiable" in the sheet. Don't spend more than 2 minutes on a single record.

If the person has changed company but is still in the same industry and seniority — they may still be a viable lead depending on the campaign. Flag as "moved but trackable" and note the new company. Harry will decide whether to re-enrich via Lusha.

If the person appears to be retired — mark as dead. Look for signals: "X VP", "Former", no recent activity, returned to home country after an expat posting.

If the list has mixed industries — check at least one or two records from each industry cluster. Data decay rates vary; hospitality and pharma senior roles, for example, turn over frequently.

Do not spend more than 30–45 minutes on a spot-check. The goal is a directional read on list quality, not a full audit. If the task is taking longer, pause and check in.

Escalation signal: If more than 70% of your sample comes back dead or unverifiable, stop and flag to Harry before doing anything else with the list. Do not submit it for validation without sign-off.


Self-assessment checklist

Before moving to the next module, confirm you can do all of the following without referring back to this page:

  • I know how to pull a representative sample from a legacy list for spot-checking
  • I can run a web search and read the signals that indicate whether a record is still current
  • I understand why AI-generated search summaries are a clue only — not a source of truth
  • I can check a LinkedIn profile and classify a contact as good, moved but trackable, or dead
  • I know which data points (email, phone) make a record actionable for outreach
  • I know the threshold for recommending list validation vs. flagging to Harry
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