Migrate from Lead Perfection to Pipedrive

Lead Perfection stores the primary customer name, email, phone, and address on each Job record. These fields map directly to Pipedrive Person fields. If a Lead Perfection job references a contact already present on another job, FlitStack deduplicates by email before inserting into Pipedrive.

Lead Perfection company records (if separate from the customer job contact) migrate to Pipedrive Organizations. The Organization Name, website, industry, and address fields map directly. Multi-location contractor companies collapse to one Organization with address fields populated from the primary job location.

The Lead Perfection Job is the primary unit of work and maps to a Pipedrive Deal. Job name, estimated value, status (lead, sold, completed, lost), and close date map to Pipedrive Deal name, Amount, Stage, and Close Date. Each Deal is linked to the corresponding Person and Organization.

Lead Perfection job statuses (New Lead, Scheduled, In Progress, Sold, Completed, Lost, Cancelled) map to Pipedrive Deal Stage values. FlitStack creates a Pipedrive pipeline matching the Lead Perfection workflow, then maps each status to a corresponding stage. Probability weights are assigned per stage based on historical conversion rates.

Lead Perfection appointments (date, time, sales rep, location, outcome) migrate as Pipedrive Activities. A site-visit appointment becomes a Pipedrive Meeting linked to the Deal, with the sales rep assigned as the activity owner. Appointment outcomes (Completed, No-Show, Rescheduled) are stored in a custom field on the Activity.

Lead Perfection sales-rep IDs are resolved by email match against Pipedrive user accounts. If a Lead Perfection rep has no corresponding Pipedrive user, FlitStack flags the record before migration — your team either creates the Pipedrive user or assigns the Deal/Activity to a fallback owner.

Pipedrive has no native lead-source field. FlitStack creates a custom pick-list field (Lead_Source__c) on both Organization and Deal objects and populates it with the exact Lead Perfection source values from the CSV export. Sub-source values are preserved as a secondary custom field (Lead_Sub_Source__c) to maintain granular attribution. Pick-list options are created dynamically based on distinct values in your Lead Perfection data, ensuring all historical sources map cleanly without manual configuration.

Lead Perfection product categories (e.g., Windows, Roofing, Siding) migrate as Pipedrive Products. Product name, unit price, and description map directly. If Lead Perfection stores product variants per job, each variant becomes a separate Pipedrive Product linked to the Deal via Deal-Product association.

Free-text notes on a Lead Perfection job migrate as Pipedrive Notes attached to the corresponding Deal. Original timestamps, note authors, and creation dates are preserved in the Pipedrive Note metadata. Rich-text formatting, hyperlinks, and embedded images are simplified to plain text for Pipedrive Notes compatibility. If a Lead Perfection job has multiple notes, each note becomes a separate Pipedrive Note entry ordered by timestamp to maintain the original conversation flow.

File attachments (photos, contracts, proposals) stored on a Lead Perfection job are re-uploaded to Pipedrive Files attached to the corresponding Deal or Person. File size limits (Pipedrive max 50 MB per file on most plans) are enforced during migration. Files over the limit are flagged for manual handling.

Lead Perfection zip-code coverage areas do not have a Pipedrive equivalent. FlitStack creates a Territory_Zip_Codes__c multi-select custom field on the Organization object to preserve coverage-area data for each contractor or office. This field stores all assigned zip codes for a territory, enabling your team to filter Organizations by geographic coverage. If your team uses territory routing, this field can drive Pipedrive automation to auto-assign deals based on customer zip code.

Any Lead Perfection custom fields beyond the standard set migrate as Pipedrive custom fields on the appropriate object. Pipedrive field types (text, number, pick-list, date, etc.) are inferred from the source data format. Custom field key names in Pipedrive are randomly generated hashes — FlitStack handles the mapping by name during migration.