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Build a LinkedIn CSV Sample for Customer-Story Account Research

Choose relevant functions, inspect a small profile sample and review the actual CSV fields before researching customer-story opportunities at a larger set of accounts.

Once you have a reason to research a company, the next task may be finding people who can clarify a customer-story project. A small LinkedIn profile sample can help. A large file of names selected only by seniority usually cannot answer the ownership question by itself.

For a case-study writer or video agency, the useful sequence is account brief, possible functions, a deliberately selected profile sample and a review of what the file actually contains. Decide whether to expand only after that review.

This article explains the research task and the public Leadsforlinked CSV schema. It does not demonstrate a new live export, claim that a title proves budget ownership or provide a list of people to contact.

Start with one account and the question in your brief. If you are investigating who commissions written customer stories, Content or Customer Marketing may be sensible functions to research. If the question concerns customer access, another team may matter.

Record the company, possible function, location constraints and reason for each criterion. Avoid making the rule “everyone with director in their title.” The project-owner guide separates programme ownership, delivery, access and approval so you can investigate them deliberately.

Keep existing contacts and current conversations visible in your working process. A second profile from the same company is not a reason to start a parallel pitch. Check your team’s actual history before deciding whether anyone should be contacted.

Make a small sample that can challenge the rule

Use a regular LinkedIn People search to inspect the account and functions you selected. Read the profiles rather than treating a title match as a complete answer. A role can be broad, outdated or unrelated to the work you mean.

Choose a small sample you can review record by record. The right size depends on the job and available people; this is not a promise that a fixed number will reveal a decision-maker. Keep a note of why each selected profile belongs in the research.

The demonstrated Leadsforlinked route is regular People search, Chrome extension, an audience in the app and CSV download. Sales Navigator is optional for that route. The worksheet does not automatically create the search or send your account brief into the app.

Inspect the literal headers before planning the next step

The public header-only CSV contains eleven column names and zero people. It is an inspectable schema example, not a populated prospect list or a newly recorded export.

Literal header What to check in your actual sample
full_name Whether the name is usable as supplied; inspect unexpected extra text.
first_name Whether it is present and appropriate for your intended use.
last_name Whether it is present; do not infer a missing name.
linkedin_url Whether the record has the intended profile link.
headline Whether the text helps explain the possible function.
company Whether the field is populated and matches the account you are researching.
position Whether the value helps you understand the role; it does not prove project ownership.
location Whether the value is present and relevant to your selection rule.
avatar_url Whether your task needs it at all; a photo is not qualification evidence.
created_at How the field is represented in the actual file; do not assume it means the person joined the company.
civility Whether any value is appropriate to use; a blank field does not need to be guessed.

The presence of a header does not establish that every row is filled. Availability varies by source and record. This sample has no email-address or phone-number column. A LinkedIn URL is not a verified email address, and a company name in a profile is not an independently verified account relationship.

Review the file as research, not as a ready campaign

Open the actual exported file and compare it with your rule. Check whether the profiles relate to the intended company and possible function. Look for blank fields, unexpected values and repeated profile links. A completed download can still contain records that are not useful for your particular task.

If you plan to import into another tool, read that tool’s current requirements and map the fields deliberately. Do not rename a LinkedIn URL column to email or invent an identifier to satisfy a required field. This article does not establish universal CRM compatibility.

Keep your interpretation in a separate working brief. A raw headline is source material. “May know who owns the story programme” is your research hypothesis. Mixing them in one unlabelled field makes later handoffs harder to audit.

A fictional sample-review decision

Illustrative exercise: Northbank Metrics is an invented software company. The following review uses fictional counts and role categories, with no personal records or client results.

An agency tests a rule covering Customer Marketing and Content at that one company. Its exercise file contains six selected records. Two lack a company value, one concerns recruitment content, two appear relevant to the programme question and one relates to a person already in the agency’s conversation history.

The correct next step is not to label the file “six qualified leads.” The researcher checks the missing account context, removes the unrelated role from this task, preserves the existing conversation and investigates which of the two plausible functions could answer the question. No purchasing authority or willingness to talk is assumed.

The review may show that the selection rule needs changing. It may also show that no additional profiles are necessary: one existing contact could already clarify the ownership. Either conclusion is useful before paying for or handling a larger file.

Decide whether more extraction solves the remaining task

Expand only when the sample contains usable information and another specific research task remains. For example, you may need the same function review across several already-selected accounts. That is different from collecting more names because the first group did not reply.

If the task is finite, inspect the current one-time pack offer. If the work repeats, compare the subscription with the features and billing period you actually need. Confirm the account’s current offer and checkout terms rather than treating a dated article as a final quote.

TopTestimonial is a resource from the team behind Leadsforlinked. The product can support selected-profile collection and CSV review. Your company-fit research, relationship history, decisions about appropriate contact and confirmation of project ownership remain separate work. A useful file is a step toward a better conversation; it is not evidence of a commission or a paying customer.

When the research gives you a reason

Have a suitable company?
Build a small contact sample.

Use your own research to choose the companies and possible roles. Leadsforlinked helps you collect selected LinkedIn profile records for review.

Try a free profile sample

Profile records, not verified email addresses. Check the current offer on Leadsforlinked.

Your next practical step
  1. 01Open a regular LinkedIn People search using your criteria.
  2. 02Use the Chrome extension to import selected profiles.
  3. 03Review the audience in the app, then download CSV.

Company fit and buying intent remain your research tasks. The worksheet does not automatically find companies with a proof gap.