Choosing help to populate a new CRM from scattered spreadsheets

Dumping unstructured data into a new CRM is a mess nobody plans for. Spreadsheets that have lived across email threads, shared drives and copied versions pile up with duplicate entries, mismatched column headers, gaps where someone entered "TBC", and dates in three different formats. Rush this, and you'll spend months cleaning live data. Pick the wrong person to help, and you'll get it done faster but wrong—malformed fields, lost records, or entries that don't fit your CRM's logic.

The skill that matters most here isn't generic data entry. It's the ability to read your actual spreadsheets, understand what your CRM expects, and make sensible calls about how to bridge the gap. That's a narrower task than ongoing capture work, and it needs someone who can think, not just type.

Understanding the scope before you hire

Before you talk to candidates, get honest about what "scattered" really means. Pull a sample of your messiest spreadsheet. How many records are we talking? Are all your sources in the same rough format, or is one person's contact list fundamentally different from another's product inventory? How many fields does your CRM have, and how many of your spreadsheets have names, addresses or customer notes that need to map across? Does your CRM have mandatory fields that some spreadsheets will lack?

The person you hire needs to see this upfront. If you describe it vaguely and they quote you blind, you're setting both of you up. A good candidate will ask these questions. A quote given without any clarifying questions about your data or CRM setup is a warning sign, whatever the price. What separates a competent fit from a misfit is whether they can preview the data, spot inconsistencies, and tell you which ones matter. Someone who says "I'll just clean it all up" without asking what "clean" means to your business is guessing. Someone who asks whether you want every duplicate kept, deduplicated by name, or merged by company name first is paying attention.

Technical familiarity with your specific CRM

Have they used the platform before? Not generally—specifically. If you're moving data into Pipedrive, HubSpot, Zoho, Monday or something else, does this person have hands-on experience with that tool's field types, validation rules and import workflows? That matters. A virtual assistant who has mapped data into your CRM five times already will work faster and avoid format mistakes that would take you weeks to untangle. Someone competent but new to your platform will need a day or two to learn the quirks, and might miss subtle issues (like whether your CRM's date field accepts "01/03/23" and interprets it as January or March).

Ask candidates directly: have you imported data into this system before? If yes, ask them to walk you through a tricky field mapping they've handled—date formats, phone numbers, currency, dropdown categories. If no, they should be prepared to learn your system with you and willing to do a small test run before the main job.

Accuracy on the details that matter to you

Data integrity isn't abstract. Ask what they'd do if a spreadsheet has a phone number in the email field, or a company name in the contact name column. Different businesses have different tolerance. You might say "just move it, we'll sort it later"; you might insist on a clean run that flags every anomaly. A strong candidate will ask which matters to you and build the approach around that, not impose their own standard.

Request a sample migration on a small, messy subset of your data—maybe 50 records from your worst-organised spreadsheet. Check not just that the data landed, but that your team can actually use it. Can you run reports? Do the customer names match the phone numbers? If someone's job title is in the wrong field, did they flag it? That real test tells you far more than their resumé.

When you're ready, Strove's verified virtual assistants and data specialists can handle CRM migrations. Look for someone with direct experience in your platform and ask to see a sample migration before committing to the full job.