3 Fivetran Case Studies That Helped Increase Companies Revenue – Fivetran Consulting
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As more third-party tools provide access to their data sources, companies are looking to build more and more data pipelines that get data into their data warehouses and data lakes.
Therein lies a major problem.
Data engineers, the ones responsible for building those pipelines are often the bottleneck.
Between having to build and deploy multiple new pipelines, building new datasets, and the constant one-off requests to add new columns. All of these requests start to quickly weigh down any data engineer team.
One option is to continually hire new data engineers. However, this is a very expensive endeavor. A data engineer can easily cost a company upwards of 100k per year. That’s a large extra expense to take on.
In this article, we will discuss how this doesn’t have to be the only solution. Instead, we will show how tools like Fivetran can help reduce your costs, technical work first by showing some examples of actual companies applying Fivetran and then discussing why this works.
Fivetran Case Studies
Fivetran recently released a great set of case studies on how they were able to improve companies like MVF, Starva, Square, Falcion.io, and several other companies’ modern data stacks. These companies were able to use Fivetran to reduce their costs as well as increase the speed they were able to get data into their data warehouses.
Let’s look at a few of those use cases.
Some company pipelines can be overly complex and utilize multiple technologies. Like the one in the first example with MVF.
MVF Increases Monthly Income By £400,000
MVF is a customer generation company that helps clients gain leads and delivers massive volumes of high-quality leads on a pay-per-lead basis. MVF’s main focus was it’s customer facing technology.
However, on their data side they had a brittle, error-prone solutions and hacks: Excel, Google Sheets, Access databases and one-off SQL queries. This one system was trying to manage 20-30 different data sources. Including data sources like Amazon S3, Bing Ads, Google Ads, Google Analytics, Iterable, LinkedIn Ad Analytics, MySQL and several others.
All with just two data engineers.
The team at MVF found their solution in Fivetran.
MVF’s Head of Analytics found that “Fivetrans connector coverage is vast, visibility on monitoring alerts is great, and the support has been brilliant — that is key.” MVF was able to take their small team of data engineers and create a large amount of impact. They were able to take two engineers powered by Fivetran and create an increases revenue of about £400,000 per month. All based on new ability to visualize leads.
But that’s not all.
MVF’s team was also able to reduce the maintenance cost of managing their complex pipelines, they were able to reassign engineering time towards bigger picture strategic tasks as well as increase data literacy by creating automated Looker reports.
Fivetran (and similar tools like Fivetran) is a key piece of the modern data stack.
Fivetran helps optimize data engineering time by reducing the need for complex ETL pipelines
Strava Saved $120,000 And Gained Insights Into Their Customers
Building customer 360 tools and digging into a customer’s journey is a necessity in a world with personally targeted ads and the expectation of user personalization.
Strava needed to better understand the customer journey and refine its marketing investment strategy.
There was one major problem. Their engineering team was too small to dedicate an engineer to extract and centralize all siloed data. So they needed a solution that let them easily pull data quickly without dedicating an entire FTE to just pull data from Apple Search Ads, Facebook Ad Insights, Google Ads, Google Play, Google Search Console, iTunes Connect, and Zendesk.
Traditionally this would take a lot of time requiring a custom connector or data pull from all these various sources.
Instead, Strava took advantage of Fivetran.
Using Fivetran, Strava was able to reduce the need to hire an FTE. as put by Michael Li, a data scientist at Starva. “Without Fivetran, we would need an additional full-time engineer to support the marketing team’s data needs, but Fivetran does more than free up time — it enhances our capabilities by enriching our marketing data set.” Again, a single data engineer can cost a company upwards of $100,000 a year(not including benefits).
At the end of the day, Fivetran allowed Strava to centralize their data from multiple external platforms and eliminate the need for an additional full-time engineer to support the marketing team’s data needs. All of this leads to them also being able to quickly and efficiently prioritizes product features and then build an attribution model to better understand user acquisition and map the entire customer journey.
Square Optimizing Limited Engineering Resources
Square suffered from a similar problem that I have seen multiple companies have. The need to do operational data work like adding columns, maintain pipelines, and make add-on tables can quickly divert engineering resources away from more impactful work such as integrating data sets and improving internal tooling.
This is why Square turned to Fivetran. In the words of Guli Zhu, Head of Marketing Analytics, this allowed Square to “spend less time on data plumbing, so we can focus on innovative initiatives like leveraging chatbots for lead qualification. And we’ve significantly elevated our infrastructure capabilities — a necessity now that we’re a $20 billion public company.”
Even large companies are finding Fivetran useful. Square was able too frees engineering resources to focus on innovation and product improvement (e.g., leveraging chatbots for lead qualification, building sales-enablement tools) and easily accommodates maintenance and internal tool improvement requests (e.g., a better SFTP loader) instead of deprioritizing them This all lead to them improving their analytical outcomes with continually updated data.
These were just two of the many case studies that Fivetran put together. If you would like to see some of the rest, then you can find them here.
Why Use Fivetran?
Before you go and click off this article, let’s review some of the reasons Fivetran is useful and why you might want to consider migrating to Fivetran.
There are multiple types of ELT and ETL tools on the market. Everything from Azure Data Factory to Matillion. So what does Fivetran offer and what benefits can it provide you?
Fivetran can help reduce the number of data engineers that need to do mundane work and can help refocus their attention on complex transformations and integrations.
Fivetran Reduce The Number Of Engineers You Need
Working as a data science and engineering consultant can be challenging. Until you start realizing you can improve your impact by working smarter not harder. I personally like tools like Fivetran because it helps me and my teammates spend less time working on mundane work that is error-prone.
We can focus our time on more impactful areas like analysis, algorithm, and dashboard development.
But it’s not just me that has experienced this benefit. As discussed in this article. Several companies like Square and Strava both found they could reduce the need to hire a data engineer to perform mundane tasks by using Fivetran. In turn, this saved Strava $117,000 annually and that was just for one of their teams.
Fivetran Reduce Mundane Plumbing Work
I have personally built Salesforce, Workday, and Zendesk connectors multiple times over. Why not avoid creating a custom bit of code every time. Instead, tools like Fivetran can be used to reduce the repetitive API connection scripts and code with easy to plug and play low code alternatives.
Fivetran’s assortment of connectors makes it easy to avoid this work by allowing data engineers and data scientists the ability to quickly pull in data from external sources without writing any code. Instead, they can just set up a few quick parameters for how the raw data will be loaded and go from there.
Saving teams from having to set up any infrastructure or code, which leads to cost savings.
Overall, Fivetran helps data engineers refocus their efforts on more impactful work. This can be an increased focus on modeling, data quality, and automation.
Fivetran Helps Data Engineers Focus More On Transforms
By reducing the amount of mundane work that needs to be done, data engineers can focus on more impactful work. This includes creating complex transforms, modeling data, and creating better integrations between disparate data sets.
There are a lot of challenges besides just getting data from point A to point B that are often ignored. One major problem is often connecting disparate data sets. This requires a lot of work depending on if the systems talk to each other. Instead of spending time just pulling data into the data warehouse. Data engineers can shift their attention to fixing how systems talk to each other so that data scientists can start making connections across all of a company’s various data sets.
As someone who has worked for multiple companies as a data engineer. I can speak to the struggle of trying to find time to develop new data sets, data products, and metrics while balancing out operational tasks.
Fivetran can help reduce a lot of the work that doesn’t provide large amounts of value but needs to get down. Allowing your data engineers to actually spend time creating value.
Is Fivetran Right For You
Fivetran is a great tool that can help reduce the number of engineering hours your team spends on mundane tasks. It has multiple features that we didn’t even go over that further improve the overall user experience and make it a strong contender when it comes to picking ELT tools.
We believe Fivetran is gaining a lot of steam and is showing lots of promise. Both from its features and its growing user base with larger companies like Square. Fivetran’s ability to manage your data pipelines and a large list of connectors continue to make it a great solution that has both technical and business impact.
If you’re still on the fence and trying to figure out if Fivetran is right for you, then consider contacting us!
Fivetran Consulting Services
Does your team need help setting up their data stack, migrating to Fivetran, or training for hot to use Fivetran? Our team can help today.
Our team has experts in data engineering and data science that can help you take advantage of Fivetran.
So before making the decision on what ELT tool you should use or if you need help migrating to Fivetran. Contact us today and we would be happy to set up a free consultation so you can set up your modern data stack strategy.
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