Does Sigmera connect to my Pipedrive account?

No. There is no connected app, no OAuth grant, and no API access. Sigmera cleans the exported spreadsheet in your browser, and you import it yourself through Pipedrive's own import tool. Nothing about your pipeline is exposed, because nothing about your account is reachable from Sigmera in the first place.

What file format does Pipedrive need for an import?

Pipedrive imports XLS, XLSX, or CSV files, with one tab per import and a header row of column names. The file has to stay under 50 MB and 50,000 rows. If your data is a multi-tab workbook, flatten the sheet you want to a single CSV before you import, since only one tab is read per import.

Doesn't Pipedrive already remove duplicates on import?

It helps, but only so far. At the import preview Pipedrive lets you choose how to handle duplicates and, when it detects them, merge instead of creating new records. That match is on exact values, so duplicates hidden by different casing or a stray leading space across stacked exports can slip past it. Collapsing them in the file first — matching case-insensitively on the email column — leaves Pipedrive far less to merge by hand.

How should phone numbers be formatted for Pipedrive?

Pipedrive accepts a phone number as free text, so a column of mixed formats will import. The reason to standardise it anyway is that the click-to-call dialer and phone-based duplicate matching work best on one consistent shape. Rewriting the column to E.164 — a leading plus, country code, then the national number — dials reliably and lets a dedupe pass recognise the same number written two different ways.

Why did some of my rows fail to import?

When rows are rejected, Pipedrive returns a skip file that lists the reason for each one — an invalid date format is a common example. Rather than correct them individually, open the skip file, standardise the column that caused the failures across every affected row with find and replace, and re-import the corrected file in a single pass.

Is it GDPR-safe to clean my Pipedrive export this way?

Cleaning a contact export is processing under GDPR wherever you do it, and you remain the controller. What changes is who else touches the data. Sigmera reads and rewrites the file with JavaScript in your own browser, so no vendor receives it and no new processor relationship is created. Sending the same list to a cloud cleaner would make that vendor a processor, and Article 28(1) requires a controller to use only processors offering sufficient guarantees of appropriate technical and organisational measures. Browser-side cleaning keeps that link out of the chain.

Clean CSVs for Pipedrive imports

Pipedrive imports stall on ordinary problems: a workbook with three tabs, the same person spread across two exported lists, a date column the importer rejects. Sigmera is not a Pipedrive connector and asks for no OAuth grant — you export the spreadsheet, clean it in a browser tab, and add it back through Pipedrive's own import tool. The contact list never leaves your device on the way through.

How it works

1
Export from Pipedrive, or start from the file you were sent
In Pipedrive you can export from Tools and apps > Export data to pull all data by item type, or from a list view click the gear icon, choose your columns, and select Export filter results — then pick Excel or CSV. The generated export stays available for 28 days. Or just start from whatever spreadsheet landed in your inbox. Nothing needs to be connected: Sigmera has no Pipedrive integration, no connected app, and no API access to your account.
2
Clean it in a browser tab
Drop the spreadsheet into Sigmera. It is parsed by JavaScript running on your own machine, so a file of named contacts and their details is not transmitted anywhere. Deduplicate across your stacked exports, fix the email column, standardise the phone numbers, and flatten a workbook to one sheet — previewing every change before you commit to it.
3
Save a CSV within Pipedrive's import limits
Pipedrive's import reads a CSV, XLS, or XLSX file with one tab per import and a header row of column names, under 50 MB and 50,000 rows. Sigmera writes a plain UTF-8 CSV by default, so accented names arrive intact and the file already matches the shape the import tool expects.
4
Import through Pipedrive's own import tool
In Pipedrive, open the "..." (More) menu, choose Import data, then From a spreadsheet, and upload your cleaned file. Pipedrive auto-maps column names to its fields; drag any unmatched column to the right field. At the preview step, choose how to handle duplicates — merging them instead of creating new records — then start the import and download the skip file if any rows are rejected.

Common Pipedrive clean-ups

Deduplicate a contact list stacked from several exports

Pipedrive can catch duplicates during an import — at the preview step it lets you choose how to handle them and, when duplicates are detected, merge them instead of creating new records. What it matches on is exact values, so the duplicates that survive come from combining exports: a filtered people list, a leads export, and a spreadsheet a colleague sent, where casing and stray whitespace stop two rows reading as the same person. Collapse them in the file first so Pipedrive is not merging hundreds of near-matches by hand.

Stack your exported spreadsheets and open them in the remove-duplicates tool
Match on the email column, ignoring case and surrounding spaces
Review the flagged rows and keep the record you want
Download the deduplicated CSV and import it

Clean the email column Pipedrive matches on

Email is the field most import tools use to decide whether a row updates an existing contact or creates a new one, so a leading space in " [email protected]" reads as a different person and a malformed address imports as a contact you can never reach. Lowercase the column, trim the whitespace a copy-paste leaves behind, and flag values that fail the basic email shape before the file goes anywhere near the import screen.

Trim whitespace and lowercase the email column
Flag malformed addresses and obvious typos
Remove rows with no usable address so they do not import as dead contacts
Download the cleaned CSV

Standardise phone numbers before import

Pipedrive stores a phone number as text, so a column mixing (415) 555-0100, 415.555.0100, and 020 7123 4567 imports without complaint — and then the click-to-call dialer and phone-based duplicate matching misfire on the inconsistent formats. Rewriting the whole column to one shape, ideally E.164 with a country code, makes the numbers dial correctly and lets a later dedupe pass recognise the same number written two ways.

Load the CSV and select the phone column
Set the default country for numbers that arrive with no code
Rewrite the column to a single consistent format
Check the rows that could not be parsed, then download

Flatten a multi-tab workbook into the file Pipedrive accepts

Pipedrive's import takes one tab per import and reads XLS, XLSX, or CSV, with the file under 50 MB and no more than 50,000 rows. A workbook with several tabs, live formulas, or data-linking cells is a common reason an import goes wrong. Export the single sheet you want to a plain CSV, standardise inconsistent values while you are there, and the import lines up on the first pass.

Convert the workbook to a single-sheet CSV
Standardise inconsistent values with find and replace
Confirm the file is one tab with a header row, under the size and row limits
Save the CSV and import it through Pipedrive

Fix the date and stray values that land rows in the skip file

When some rows do not import, Pipedrive returns a skip file listing the reason for each — an invalid date format is a routine one. Rather than fix them one at a time in Pipedrive, correct the pattern across the whole column in the file: rewrite dates to a consistent format and clear the stray characters that break a field, then re-import the corrected rows in one go.

Open the skip file and read the reason on each rejected row
Standardise the offending column — dates, codes, or delimiters — with find and replace
Re-run the import with the corrected file

Sources

Frequently asked questions

Does Sigmera connect to my Pipedrive account?: No. There is no connected app, no OAuth grant, and no API access. Sigmera cleans the exported spreadsheet in your browser, and you import it yourself through Pipedrive's own import tool. Nothing about your pipeline is exposed, because nothing about your account is reachable from Sigmera in the first place.
What file format does Pipedrive need for an import?: Pipedrive imports XLS, XLSX, or CSV files, with one tab per import and a header row of column names. The file has to stay under 50 MB and 50,000 rows. If your data is a multi-tab workbook, flatten the sheet you want to a single CSV before you import, since only one tab is read per import.
Doesn't Pipedrive already remove duplicates on import?: It helps, but only so far. At the import preview Pipedrive lets you choose how to handle duplicates and, when it detects them, merge instead of creating new records. That match is on exact values, so duplicates hidden by different casing or a stray leading space across stacked exports can slip past it. Collapsing them in the file first — matching case-insensitively on the email column — leaves Pipedrive far less to merge by hand.
How should phone numbers be formatted for Pipedrive?: Pipedrive accepts a phone number as free text, so a column of mixed formats will import. The reason to standardise it anyway is that the click-to-call dialer and phone-based duplicate matching work best on one consistent shape. Rewriting the column to E.164 — a leading plus, country code, then the national number — dials reliably and lets a dedupe pass recognise the same number written two different ways.
Why did some of my rows fail to import?: When rows are rejected, Pipedrive returns a skip file that lists the reason for each one — an invalid date format is a common example. Rather than correct them individually, open the skip file, standardise the column that caused the failures across every affected row with find and replace, and re-import the corrected file in a single pass.
Is it GDPR-safe to clean my Pipedrive export this way?: Cleaning a contact export is processing under GDPR wherever you do it, and you remain the controller. What changes is who else touches the data. Sigmera reads and rewrites the file with JavaScript in your own browser, so no vendor receives it and no new processor relationship is created. Sending the same list to a cloud cleaner would make that vendor a processor, and Article 28(1) requires a controller to use only processors offering sufficient guarantees of appropriate technical and organisational measures. Browser-side cleaning keeps that link out of the chain.