Docs/Workspace Setup

CSV Imports and Templates

CSV imports and templates let a team create clients, properties and appliances in bulk when onboarding a portfolio.

For: Teams onboarding bulk data4 min read6 sections

Import template explorer

Preview required fields and dependency order before preparing a CSV import.

Required fields

  • client_name
  • address_line1
  • city
  • postcode

All fields

  • client_name
  • address_line1
  • city
  • postcode
  • property_type
  • access_notes

Example row

Northgate Lettings, 12 Oakwood Road, Leeds, LS6 2AB, flat, Key safe by side door
Import exampleCustomer-safe walkthrough

Onboard a portfolio without messy data

Imports are fastest when the template columns are exact and the dependency order is respected: clients, then properties, then appliances.

What you see

  • A template with required columns and a clear dependency order.
  • A preview and error report before anything is committed.
  • Created records you can spot-check immediately after import.

How to use it

  • Mirror the template headers exactly; do not rename columns.
  • Clean duplicates, blank required fields, and invalid addresses first.
  • Import in order: clients, then properties, then appliances.
  • Spot-check several records, then correct the source and re-import if needed.

CSV import template

Properties template

client_name,address_line1,city,postcode,property_type
Northgate Lettings,12 Oakwood Road,Leeds,LS6 2AB,flat

Required fields

4

Dependencies

1

Client existsThen appliancesUTF-8

Decision guide

SituationRecommended actionProof it worked
Loading many appliancesImport properties first so property_address resolves.Appliances attach to the right property.
Duplicate names appearCheck for differences in spaces or case before re-importing.No duplicate clients or properties remain.
Addresses look odd in ExcelSave the CSV as UTF-8 and avoid formula-like values.Special characters import cleanly.

Troubleshooting path

  1. 1If a required field error appears, fill every required column before retrying.
  2. 2If records land under the wrong client, fix the source references and re-import.
  3. 3If an import creates duplicates, review the matching identifiers.

Related docs

Clients and propertiesAppliance registersOrganisation and Gas Safe identity

Appliance import rows

CSV sample

Safe example data
property_address,property_postcode,appliance_type,make,model,serial_number,gc_number,location,flue_type
12 Oakwood Road,LS6 2AB,boiler,Worcester,Greenstar 30i,SN4471209,47-311-59,Kitchen cupboard,room_sealed
12 Oakwood Road,LS6 2AB,gas_fire,Valor,Black Beauty,,,Living room,open_flue
property_address must match an existing property exactly.
serial_number and gc_number are what deduplicate an appliance against PlateScan later; property_postcode disambiguates two properties with the same first address line.

Importable Data

CSV imports and templates in Manifold let you load clients, properties, appliance registers, engineers and past invoices in bulk instead of creating each one by hand, using the same column templates whether you are onboarding a brand-new workspace or topping up an existing one.

  • Clients, properties, appliance registers, engineers and past invoices can be loaded in bulk, each from its own list page.
  • Imports are tenant-scoped and should be run by an office user who can verify the output.
  • Templates preserve column names, required fields, and a sensible dependency order.
  • Previews and errors should be checked before relying on imported data.

How The Importer Works

  • Each list page has Download template and Import CSV. The import is a dry run first: the preview lists the first 200 rows (a larger file still imports in full), counts the rows ready to import, and lists rows with errors as will be skipped.
  • Re-validate re-runs the preview after you fix the source. Properties and appliances offer Skip duplicates or Update existing for rows that match something already in the workspace.
  • Matching: clients by name (case-insensitive); properties by address line 1, line 2 and postcode; appliances by property plus serial number; engineers by email.
  • Required columns: name for clients; address_line1 for properties (client_name must already exist, dates as DD/MM/YYYY or ISO); property_address or property_id for appliances (property_postcode disambiguates); full_name and email for engineers.
  • Files are capped at about 15 MB or 10,000 rows. Every client, property, appliance and invoice import can be undone from the result screen or with Undo last import on the list page.
  • Engineer imports are capped at 2,000 rows, cannot be undone, and send no invite emails when the file has more than 50 rows.

Import Checklist

  1. 1Mirror the expected template columns and keep header names exact.
  2. 2Clean duplicate names, blank required fields, and invalid addresses.
  3. 3Import in dependency order: clients, then properties, then appliances.
  4. 4Spot-check several created records immediately after import.
  5. 5Correct the source CSV and re-import only after understanding how duplicates are matched.

Troubleshooting Imports

Troubleshooting

  • Missing required field: fill every required column before retrying.
  • Records under the wrong client: fix the source references and re-import or correct manually.
  • Duplicate records: check whether names or identifiers differ only by spaces or case.
  • CSV opens strangely in Excel: save as UTF-8 and avoid formula-like values in address fields.

Data Quality Standard

Setup records are not just admin. They become the labels, filters, and certificate fields customers rely on later. A small naming or address mistake in setup becomes a compliance or delivery problem weeks later.

  • Use one canonical spelling for every client, property, and appliance.
  • Keep property addresses precise, because they drive the route planner, scheduling, and the printed record.
  • Keep appliance make, model, serial, and GC number accurate so PlateScan deduplicates cleanly.
  • Deactivate former engineers and historical records instead of deleting history that explains past work.
  • Run bulk imports in dependency order: clients, then properties, then appliances.

Customer-Facing Consequences

If a value can appear on a record, in the portal, or in an export, write it as if a landlord or letting agent will read it. Manifold reuses operational labels across customer outputs, so there is no separate translation step at delivery time.

Troubleshooting

  • If a client sees a confusing name, fix the source record so every record generated from now on prints it correctly.
  • If analytics split across duplicate names, choose one canonical record going forward and keep the old ones for history.
  • If an export does not join downstream, check names, identifiers, and relationships in setup before changing the export.

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