How to Connect Pipedrive to Google Sheets

Pipedrive's API is pleasant to work with except for one thing that makes a raw export nearly unreadable: custom fields come back keyed by 40-character hashes rather than names, and their dropdown values come back as numeric option IDs. A deal export therefore arrives full of columns like dcf558aac1ae4e8c… containing values like 47. This guide covers resolving both, plus pagination and the v1 to v2 migration.

The two-minute option: CSV export

In Pipedrive, open Deals in list view, apply a filter, select the columns you want, and use … → Export filter results. The export uses your chosen columns with their proper names, so custom fields arrive readable, which is exactly the work the API leaves to you. Import into Sheets via File → Import.

Pipedrive to Google Sheets for free (Apps Script + REST API)

Find your API token under Settings → Personal preferences → API. It goes on the query string as api_token. Your company domain is the first part of your Pipedrive URL.

The pattern that makes this usable: fetch dealFields once to build two maps, hash to field name and option ID to option label, then translate every deal as you write it.

1function importPipedriveDeals() {2  const DOMAIN = "yourcompany";3  const TOKEN  = "YOUR_API_TOKEN";4  const root = "https://" + DOMAIN + ".pipedrive.com/api/v1";5 6  // Custom fields are keyed by 40-char hashes. Build hash → name, and7  // optionId → label for dropdown fields, before touching any deals.8  const fieldNames = {}, optionLabels = {};9  const fields = JSON.parse(10    UrlFetchApp.fetch(root + "/dealFields?api_token=" + TOKEN).getContentText()11  ).data;12 13  fields.forEach((f) => {14    fieldNames[f.key] = f.name;15    (f.options || []).forEach((o) => { optionLabels[String(o.id)] = o.label; });16  });17 18  // Only the hashed custom fields need translating; standard keys are readable.19  const customKeys = fields.filter((f) => f.key.length === 40).map((f) => f.key);20 21  const rows = [];22  let start = 0;23 24  while (true) {25    const url = root + "/deals?api_token=" + TOKEN26      + "&limit=100&start=" + start;27 28    const body = JSON.parse(29      UrlFetchApp.fetch(url, { muteHttpExceptions: true }).getContentText()30    );31    if (!body.success) throw new Error(JSON.stringify(body));32    if (!body.data) break;33 34    body.data.forEach((d) => {35      const custom = customKeys.map((k) => {36        const v = d[k];37        if (v === null || v === undefined || v === "") return "";38        // Dropdowns return option IDs, possibly comma separated.39        return String(v).split(",")40          .map((part) => optionLabels[part.trim()] || part.trim())41          .join(", ");42      });43 44      rows.push([45        d.title,46        d.status,47        d.stage_id,48        d.value,49        d.currency,50        d.owner_name || (d.user_id && d.user_id.name) || "",51        d.org_name || "",52        d.add_time,53        d.won_time || d.lost_time || "",54        ...custom,55      ]);56    });57 58    // Trust the pagination flag, not the page size: filters can return59    // short pages while more results remain.60    const p = body.additional_data && body.additional_data.pagination;61    if (!p || !p.more_items_in_collection) break;62    start = p.next_start;63  }64 65  const header = ["Title","Status","Stage","Value","Currency","Owner",66                  "Organization","Created","Closed",67                  ...customKeys.map((k) => fieldNames[k] || k)];68 69  const ss = SpreadsheetApp.getActiveSpreadsheet();70  const sheet = ss.getSheetByName("Deals") || ss.insertSheet("Deals");71  sheet.clearContents();72  sheet.getRange(1, 1, 1, header.length).setValues([header]);73  if (rows.length) {74    sheet.getRange(2, 1, rows.length, header.length).setValues(rows);75  }76}

The pagination detail matters more than it looks: checking whether a page came back shorter than the limit is unreliable in Pipedrive, because filtered collections can return short pages with more results behind them. Always read additional_data.pagination.more_items_in_collection.

Limits: Pipedrive rate limits per token, and Apps Script stops at six minutes. Stage and pipeline names need their own lookups from the stages and pipelines endpoints, since deals reference them by ID just as they do custom field options.

The Brooked method

Brooked resolves the hashed custom field keys to their names, translates dropdown option IDs to labels, and looks up stage, pipeline and owner names, so deals arrive as a readable table. Deals, people, organizations and activities can all import into one spreadsheet on a single schedule.

Step 1: Install Brooked

Install Brooked from the Google Workspace Marketplace. Free tier includes 100 imports per month, no credit card required.

Step 2: Connect Pipedrive

Choose Pipedrive in Brooked and authorise, or paste an API token from Settings → Personal preferences → API. Pick deals, people, organizations or activities, optionally filter by pipeline or date, and import.

Step 3: Schedule the refresh

Set the import to re-run hourly or daily so pipeline reports and forecasts reflect current stages rather than whatever they were when the sheet was built.

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Method comparison

Common use cases

• Pipeline forecasting: weighted value by stage and close date in a sheet finance trusts
• Win/loss analysis: conversion rates between stages and where deals stall
• Rep performance: deals created, won and lost per owner over time
• Revenue reconciliation: join won deals against invoices or Stripe data in the same sheet
• Data hygiene: find deals missing owners, close dates or required custom fields

Troubleshooting common issues

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• How to Sync HubSpot Deals and Pipeline Data to Google Sheets in Real Time

Frequently asked questions