This tests whether you can manage real database quality issues, prioritize by business impact, and avoid damaging active pipeline data.
Present a prioritization matrix: fix active leads first, merge duplicates using identifiers, fill missing required fields, then re-tag stale contacts. Always work from a backup and get confirmation before mass changes.
Start by asking the agent to confirm the business rules before you touch anything, because a CRM cleanup is only as good as the definitions you use. Say plainly that you will not mass-edit without a backup and without knowing which fields are custom or which tags matter for reporting. Then explain your two-week sequence: week one is for triage, not for fixing everything at once. Prioritize by revenue risk, so active deals with missing emails or last names come first, because those directly affect follow-up and closing. Next, merge duplicates using a unique identifier like phone number or property address, not just the name, since many Filipino contacts share common surnames. After that, re-tag stale leads older than six months into a separate nurture or archive status, and ask the agent whether those should still receive marketing or be purged. Finally, fill missing required fields only where you can verify the data from other sources, and flag anything uncertain instead of guessing. Keep a simple log of every change you make, and give the agent a short daily update so they can catch mistakes early. Be honest about what two weeks can realistically cover, and propose that the deepest cleanup happens in phases.
Filipino candidates sometimes overpromise 'I will finish the whole CRM cleanup over the weekend, sir' or say 'kaya ko gawin lahat, no problem' without clarifying the data. Instead, ask about custom fields, source tags, and which records are safe to merge.
Situation
In my previous virtual assistant role for a small e-commerce seller, I inherited a spreadsheet with 1,200 customer rows and many duplicate entries.
Task
I needed to reduce duplicate contacts and fill key fields before the next email campaign without deleting any real purchase history.
Action
I exported a backup first, then used filters to group records by email address and phone number. I merged rows only when two identifiers matched exactly, added a 'verified date' column, and contacted the owner for a short list of ambiguous entries. For stale 'new' tags older than 90 days with no activity, I moved them into a 'nurture inactive' list instead of deleting them.
Result
Within three days I cut the list by 15% and raised complete email coverage to 95%, and the campaign open rate improved.
Audit in layers with backups, never bulk-delete; protect history and query ambiguous records.
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