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How HubSpot uses Fivetran

ConfirmedVendor case study · Checked Nov 12, 2026
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The use case: how HubSpot deploys Fivetran

HubSpot's People Operations team uses Fivetran to replace fragile DIY pipelines and spreadsheet imports, ingesting data from Workday, Greenhouse, Survey Monkey and FP&A spreadsheets into Snowflake. The centralized data supports workforce planning, hiring forecasts, eNPS analysis and generative AI initiatives on employee performance.

More reported results

Figures published in Fivetran’s case study. They are not independently measured by usedby.

6-10 weeks to under an hour

Reduced pipeline development from 6-10 weeks to under an hour

90-95%

Now, forecasts are 90-95% accurate to what happens.

150%

leading to a 150% ROI

90 percent

Within two days, 90 percent of managers have pulled their personalized eNPS insights.

In the customer’s words

In our first year with Fivetran, we built 40+ different pipelines for nearly 700 tables, which handle nearly 40 million records every month. It took fewer than 40 hours to build it all, saving us nearly 1,000 hours and $100,000 across multiple departments, leading to a 150% ROI.
Sandro Frattura, Analytics Engineering Manager, HubSpot People Operations — Source

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Other companies using Fivetran

Customers across industries, with public evidence.

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More stories

Go straight to the source

Based on Fivetran’s published case study. We check the public evidence; the results are reported by the vendor.

fivetran.com
Last checked
Nov 12, 2026
fivetran.comCaptured Fivetran case study about HubSpotOpen source capture
What the story claims, and what we checked

What we compared with the page.

  • The figure: $100,000Checked

    Printed word for word on the page, near the name of HubSpot.

  • The passage quoted aboveChecked

    Copied word for word from the page, near the name of HubSpot.

  • HubSpot uses FivetranChecked

    Confirmed line.

  • The result itselfNot checked

    We quote it; we did not measure it.

In our first year with Fivetran, we built 40+ different pipelines for nearly 700 tables, which handle nearly 40 million records every month. It took fewer than 40 hours to build it all, saving us nearly 1,000 hours and $100,000
From the page. fivetran.com