When to run this workflow

Use the Import Wizard when your business already has working data in spreadsheets or another platform and you want that information available inside Fencify without retyping every supplier, customer, job or invoice. This is most useful during initial setup, after switching systems, or when one part of the business has been managed outside Fencify and now needs to be brought into the same operating flow.

Fencify supports imports for suppliers, inventory, customers and leads, projects, schedule dates, quotes, invoices, payments and expenses. The wizard also recognises common export patterns from Manual CSV, Jobber, ServiceM8, Tradify, Xero, QuickBooks Online, Simpro, AroFlo, Fergus and Other. That source choice matters because it helps Fencify suggest more useful field matches before you start previewing rows.

The strongest results come from treating import as an operating workflow rather than a one-click upload. Each CSV moves through upload, mapping, preview, commit, summary and history. That structure gives you a chance to catch duplicate records, weak column mapping, mismatched projects, or financial rows that need closer review before they affect live work.

Choose the right import order before uploading anything

The order of import matters because later records often depend on earlier ones already being in place. Quotes work better when the lead or customer information is already clean. Invoice, payment and expense imports work better when the project already exists and can be matched properly. Supplier and inventory imports are easier to trust when they are reviewed before the quoting and procurement team starts using them.

That sequence is especially practical for fencing contractors because it mirrors the way the business already works. Materials and suppliers support quoting. Leads support quotes. Projects support install planning. Financial records support cash and audit review once the underlying job structure is already in place.

Prepare each CSV so the preview stage stays readable

The wizard expects a CSV with a header row, and launch imports are capped at 2,500 rows per file. If you have a large export, split it into logical passes before you upload it. Smaller, purpose-based files are easier to map, easier to preview and far safer to commit.

Good preparation usually means:

• keeping one record type per file wherever possible
• using clear headers rather than shortened internal labels
• removing unused columns that have no operating value
• checking dates, amounts and contact details before the upload
• deciding whether duplicate rows should be skipped, created again, or used to update matched records

For fencing businesses, it is worth paying extra attention to address quality, customer names, supplier item codes, material pricing and project naming. Those are the fields most likely to create confusion later if they come in inconsistently. A customer with two slightly different addresses or a supplier item with two different names may still import, but it makes quoting, procurement and reporting harder afterwards.

Schedule files deserve their own check. If you are importing schedule dates, decide whether the CSV is meant to update lead site visits, project install dates, or both. That keeps the timing changes deliberate rather than accidental.

Upload the file and pick the matching source and import type

When you open the Import Wizard, start by choosing the source platform and the import type before you upload the file. Fencify uses those two choices together to seed source-aware field aliases and show only the destinations that make sense for that import pass.

1. Select the source platform that best matches the export file.
2. Select the import type, such as suppliers, inventory, leads, projects, schedule, quotes, invoices, payments or expenses.
3. Upload the CSV file and continue into mapping.

Finance-related imports are more restricted than general records. Quotes, invoices, payments and expenses require financial visibility. If a delegated user does not have the required access, those options are blocked or rejected before commit. That is helpful when several people are involved in setup and only some of them should be loading commercial or payment data.

Once the file is staged, Fencify creates an import job with row counts, header details and mapping confidence. At this point the data is ready for review, and live records are created later when you commit the selected rows.

Map columns carefully and save templates for repeat files

The mapping screen is where the import starts to become specific to your business data. Every header from the CSV is shown alongside a Fencify field selector and suggested matches. Some suggestions will be strong, especially when the source export is familiar. Others need manual judgement, particularly when the file uses broad names such as Name, Notes, Description or Amount.

Work through the headers with the destination in mind:

• Map operating fields directly when they clearly belong in Fencify.
• Preserve useful extra source fields as metadata when they help future reference but do not belong in a first-class field.
• Skip columns that have no value for your imported records.

Saved templates are one of the most useful parts of the workflow. If you expect to import the same export layout again, tick the option to save the mapping as a reusable template and give it a name your team will recognise later. Fencify can then reuse that template when the same source system, import type and header layout appear again, while still letting you review the mapping before preview.

This is especially useful for recurring supplier price lists, monthly customer exports, or accounting exports that arrive in the same shape each time.

Use preview to catch duplicates, weak rows and risky finance matches

The preview screen is where you decide whether the file is ready to commit. Fencify shows counts for ready rows, warning rows and error rows, then lists each row with normalised data and issue notes. That makes preview the operational checkpoint for the whole workflow.

Warning rows often still import successfully, but they deserve review first. Common cases include possible duplicate suppliers, possible duplicate inventory items, possible duplicate leads, or extra source fields that are being preserved as metadata. Error rows need correction before they can be used.

For import review, focus on these checks:

• Supplier and inventory imports: confirm names, supplier item codes, cost prices and sell prices look clean.
• Lead imports: compare customer details and site addresses closely before allowing duplicate creation.
• Project imports: confirm project names, addresses and install timing are recognisable to the team.
• Quote imports: confirm the customer context is strong enough for the quote to make sense once it lands.
• Invoice, payment and expense imports: confirm the project match is correct before committing any money-related row.

The duplicate policy also matters here. Skip duplicates keeps existing records unchanged. Create anyway adds a new record even where a likely match exists. Update matched record uses the matched record where that import type supports updates. Pick the policy that matches the purpose of that pass rather than using one setting for every file.

If you are importing inventory and the source rows include supplier information, preview can also include an option to create missing suppliers for those rows. Use that only when the supplier names are already clean enough to trust.

Commit in controlled passes instead of one giant sweep

Once the preview looks right, commit selected rows only. Fencify processes selected rows individually, which means one weak row does not have to stop every other usable row in the same pass. That makes the workflow practical for real data clean-up, where one export may be mostly ready with a handful of rows that still need manual attention.

A reliable commit rhythm is:

1. Commit the cleanest record type first.
2. Review the summary immediately after the pass.
3. Open a sample of created records in the relevant Fencify area.
4. Fix any weak source data before starting the next pass.

For example, a fencing contractor moving across from spreadsheets might first commit suppliers and inventory, then check that supplier names and material pricing are sensible. After that, the office can commit leads, confirm customer names and site addresses, then bring in projects and install timing. Quotes and financial records can follow once the team is confident the job structure already matches what is in the field.

Review the summary, use history, and move the imported records into live work

After commit, the summary page shows what happened: how many rows imported, how many were skipped, and which record types were created. Use that page as part of the workflow rather than as a final receipt. It is the fastest place to spot whether the pass finished cleanly or whether a second cleanup round is still needed.

History is just as important once the business is live. It gives you a record of recent import jobs by date, source, type, status, row count, outcome and template name. That helps when two staff members need to confirm whether a file has already been loaded, or when a repeat supplier or accounting export mapped differently from expected.

Once a pass is complete, bring the data into normal Fencify operations straight away:

• use imported suppliers and inventory in your quoting and procurement setup
• review imported leads and move them into the right sales stage
• check imported projects for install timing and operations readiness
• review imported quotes before following up or converting anything
• review imported invoices and payments before using them in collections or sync work

If you need narrower help after this workflow, the quickest follow-up guides to open are Import wizard overview, Upload a CSV, Map import columns, Save mapping template, Preview import rows, Review import warnings, Commit an import, Import summary and Import history.