June 18, 2024

Pipedrive to Google Sheets

A guide on syncing data from Pipedrive to Google Sheets

Automating Data Sync

Binary vs Structured

Pipedrive, a comprehensive sales tool, allows for an efficient sync and export of diverse data types to Google Drive. Certain data types, like file attachments such as PDFs or images, are referred to as binary data. This term denotes data types that are not textual in nature, but require special software to be read and understood. Binary data syncing is a significant feature as it allows for seamless team collaboration on various documents directly from the Pipedrive platform.

In contrast to binary data, Pipedrive also facilitates the export of structured data, primarily composed of sales tracking metrics. Structured data is highly organized and easily interpretable by computer systems, generally stored in the form of tabulated datasets in relational databases. So, when you are syncing sales tracking metrics from Pipedrive to Google Sheets, you're dealing with structured data. These data provide actionable insights and are essential for sales forecasting, trend analysis, and performance measurement. Balancing both binary and structured data syncing from Pipedrive to Google Sheets can provide comprehensive insights and organizational efficiency, making this feature a critical component of workflow management.

Native vs External

Pipedrive provides decent native analytics.  Many Pipedrive analysts find Pipedrive's built-in analytics to suffice.  But if you want evolve your data-driven decision making and go beyond what Pipedrive offers with any of the following, then you will need to export your Pipedrive data so that specialized analytics can be set up:

  • Finely customize your metrics and visualizations.
  • Combine Pipedrive data with data from other business apps.
  • Present Pipedrive data analytics to stakeholders outside of your CRM context.

You will need to either manually export your Pipedrive data or connect Pipedrive to external services that have been optimized to read Pipedrive data.

Manual vs Automatic

As a Pipedrive user, you are presented with two options for syncing data to Google Sheets. One method you can choose is a manual data export (to CSV or XLSX). This involves downloading the necessary Pipedrive data, then uploading and sorting it into your Google Sheets.

While this approach gives you a hands-on overview of your data, it may be time-consuming and could lead to human errors, a factor to reevaluate especially if your data volume is substantive.

However, there's an alternative option that provides added ease and minimizes errors - the automated ETL (Extract, Transform, Load) service. An ETL tool can placate your task by automating the data synchronization between Pipedrive and Google Sheets. Once set up, the tool automatically extracts the data you require from Pipedrive, transforms it into a format compatible with Google Sheets, and loads it directly into your desired spreadsheet. This approach is highly effective for maintaining consistent and up-to-date data syncing, making it ideal for businesses dealing with copious data.

In-sheet vs Downstream BI

You have the option of setting up your custom analytics directly in Google Sheets, or, if your analytics need to be more sophisticated, you can use Google Sheets as a kind of data warehouse, and then add a downstream business intelligence (BI) app (also called "Dashboarding", "Visualization", or "Analytics" apps.  These names for all intents and purposes are interchangable.)

If you choose to work directly within Google Sheets, an effective functionality available to you is the use of Filter Views. Filter Views are a feature you can use to sort and filter data. Regardless of how frequently or significantly the data refreshes, your settings remain preserved. This means that once you set specific filters for your data, you would not have to reapply them each time the data gets updated, resulting in time saved and consistency maintained.

Some BI apps read directly from Pipedrive and some do not.  Most mainstream, platform-level BI apps do not integrate natively with Pipedrive but the majority integrate with Google Sheets as a data warehouse.

If you want to use a top tier, free, off-the-shelf BI tool like Looker Studio, or run analytics directly on your Pipedrive data within Google Sheets, you will need to use an intermediary app, called an ETL app (Extract Transform Load) (also called "Data Integration") to continusly sync your Pipedrive data to your spreadsheet or another data storage medium, called a warehouse.

Scope Considerations

Google Sheets is limited to 10 million cells.  If you have not already, read through our guides on Defining your Requirements and Selecting a Vendor.

Custom Fields vs Default Fields

Pipedrive offers an advanced Custom Fields system.  If you plan to analyze only default fields in Pipedrive then any ETL service will suffice.  However, if you need to analyze the values of your Custom Fields, look for an integrator that enriches Custom Fields data so that it is understandable for audiences downstream.

Pipedrive by default outputs only the identifiers of custom field values, but not the values themselves.  See the Pipedrive docs for more info.  A data integration service that has been carefully fine tuned to translate these identifiers is a big boost in the analytics context.

Combined Data Sets vs Singular Data Sets

Like all apps, Pipedrive organizes its data into data sets, also called "objects" or "models" or "resources".  Consider the following examples of data sets in Pipedrive:

  • Organizations
  • Deals
  • Persons
  • Products

Most Pipedrive integrators extract a single data set at a time into a single Google Sheet. While this may seem sufficient, it usually is not.

There are vital interconnections between these data sets that are often lost. This is where the magic of combined data sets comes into play. With combined data sets, you have Deals and Products paired together into one comprehensive dataset. Such a dataset can give you integrated, multi-dimensional views, helping you derive insightful, precise analytics that can propel your decision-making process to the next level.

So, when seeking an integrator for your Pipedrive and Google Sheets data syncing, look beyond those that just extract one data set at a time. Search for an integrator that either automatically or manually (through your selection) combines your data sets. This integrated approach will help you unlock the full potential of your data and empower you to make more informed, data-driven decisions.

Raw vs Parsed Data

Google Sheets data can be stored in one of two modes, raw or parsed.  See Google's documenation for technical details

Let's delve into the differences between these two types of data output. In Google Sheets, the way your data is presented can have significant implications for how you use and interpret it.

Raw data refers to the unprocessed, direct-from-the-source data. It could come in various forms such as text for numbers, booleans represented as true or false spelled out, calendar dates shown as text, or financial values as strings. While this retains originality, it might not be as useful to perform calculations or draw conclusions.

On the other hand, parsed data offers a more processed alternative. For example, instead of textual numbers, you see genuine integers.

  • Booleans are not verbal but binary: true becomes TRUE, false becomes FALSE
  • Text dates turn into calendar-based dates, providing a recognizable format for operations like date-ranges.
  • Currency amounts appear as financial values, enabling accurate accounting calculations.

As you sync data from Pipedrive to Google Sheets, consider the implications of each type. With parsed data, you get more versatility for analysis and further processing, while raw data stays true to its original format, which may hold its own advantages depending on your goals.

Look for an ETL service that offers you the option of both raw and parsed data load into Google Sheets.


The best ETL services refresh your entire Pipedrive data set in Google Sheets, as opposed to simply appending new records. This architecture ensures up-to-date information at all times, encompassing all recent changes to your data in Pipedrive. This refresh process commonly occurs during regular automated intervals, but can also be manually triggered if need be.

Google Sheets Scopes

Since Google Sheets are stored inside Google Drive and Google Drive is commonly used to store highly sensitive data, look for an integration service that requests access in a scope limited to your Pipedrive data.  Some apps request overly broad access to your entire Google Drive, and all of your Google Sheets.

Overly broad access request

Find an app that requests access with a narrower scope.

Limited, more secure access request

Solution: Pipedrive - Flatly - Google Sheets

The solution entails leveraging a data automation service such as Flatly to facilitate the synchronization of data between Pipedrive and Google Sheets.


Once a data set from Pipedrive is replicated in Google Sheets, it can be read natively by Looker Studio, and another 20+ downstream BI apps.  See your BI app's documentation for instructions on how to setup the read-access with Google Sheets.  It's usually just a few clicks.

If you are using a true turnkey data integration solution, your Pipedrive data will be refreshed automatically every day, hour or minute, so any changes in your data set will be reflected to your downstream viewers of your analytics/dashboards with no manual work required.

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