Dataiku Case Studies Buildertrend: Maximizing Data Project Speed to Value

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	Buildertrend: Maximizing Data Project Speed to Value Dataiku

Buildertrend: Maximizing Data Project Speed to Value

Dataiku

Technology Category	Analytics & Modeling - Predictive Analytics
Applicable Industries	Construction & Infrastructure
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Predictive Maintenance
Services	Data Science Services
Challenge	Buildertrend, a leading construction project management software company, was looking to disrupt the residential construction industry by leveraging data science to improve business operations and make residential contractors more efficient. They were seeking a data science platform that could enhance speed and agility in their data-to-insights process, enable company-wide collaboration on data projects, and empower their data scientists with the right tools and resources. The company was also keen on automating repetitive tasks, improving documentation practices, and increasing the amount of data included in their models. One of their key use cases was churn reduction, where they aimed to efficiently target at-risk accounts to drastically reduce churn. Read More
About Customer	Buildertrend is a leading construction project management software company for home builders, remodelers, and residential contractors. Founded in 2006 and based in Omaha, Nebraska, the company has 550 employees and has been experiencing 40-50% year-over-year revenue growth. The company is on a mission to disrupt the residential construction industry, with data playing a key role in their strategy. They have a collaborative process inspired by agile principles, with regular sprint planning and showcasing meetings that allow them to ideate, align on project priority, and share progress and results in a meaningful way. Read More
Solution	Buildertrend chose Dataiku as their data science platform after an extensive evaluation process. With Dataiku, they were able to drastically improve their speed to value, reducing model deployment time from three days to just three hours. The platform also enabled them to automate low-value tasks such as rerunning models on a weekly basis and enhance collaboration across various groups. Analysts could easily input on models, view version history, and make changes in a safe environment. In terms of use cases, Buildertrend leveraged Dataiku to create a churn probability model that automatically flagged at-risk accounts, leading to a significant reduction in churn. They also used the platform to develop a smart messaging system that identified the right content to push to a certain user at a certain time. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Construction & Infrastructure

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Predictive Maintenance

Services

Data Science Services

Challenge

Buildertrend, a leading construction project management software company, was looking to disrupt the residential construction industry by leveraging data science to improve business operations and make residential contractors more efficient. They were seeking a data science platform that could enhance speed and agility in their data-to-insights process, enable company-wide collaboration on data projects, and empower their data scientists with the right tools and resources. The company was also keen on automating repetitive tasks, improving documentation practices, and increasing the amount of data included in their models. One of their key use cases was churn reduction, where they aimed to efficiently target at-risk accounts to drastically reduce churn.

About Customer

Buildertrend is a leading construction project management software company for home builders, remodelers, and residential contractors. Founded in 2006 and based in Omaha, Nebraska, the company has 550 employees and has been experiencing 40-50% year-over-year revenue growth. The company is on a mission to disrupt the residential construction industry, with data playing a key role in their strategy. They have a collaborative process inspired by agile principles, with regular sprint planning and showcasing meetings that allow them to ideate, align on project priority, and share progress and results in a meaningful way.

Solution

Buildertrend chose Dataiku as their data science platform after an extensive evaluation process. With Dataiku, they were able to drastically improve their speed to value, reducing model deployment time from three days to just three hours. The platform also enabled them to automate low-value tasks such as rerunning models on a weekly basis and enhance collaboration across various groups. Analysts could easily input on models, view version history, and make changes in a safe environment. In terms of use cases, Buildertrend leveraged Dataiku to create a churn probability model that automatically flagged at-risk accounts, leading to a significant reduction in churn. They also used the platform to develop a smart messaging system that identified the right content to push to a certain user at a certain time.

Impact #1	Drastically improved speed to value, reducing model deployment time from three days to three hours.
Impact #2	Automated repetitive, low-value tasks such as rerunning models on a weekly basis.
Impact #3	Enhanced collaboration across various groups, with analysts able to easily input on models, view version history, and make changes in a safe environment.

Impact #1

Drastically improved speed to value, reducing model deployment time from three days to three hours.

Impact #2

Automated repetitive, low-value tasks such as rerunning models on a weekly basis.

Impact #3

Enhanced collaboration across various groups, with analysts able to easily input on models, view version history, and make changes in a safe environment.

Benefit #1	60% churn reduction for a targeted customer cohort.
Benefit #2	Spread internal adoption of their churn reduction model.
Benefit #3	Increased the amount of data they now include in their models, moving from thousands of rows of data to millions.

Benefit #1

60% churn reduction for a targeted customer cohort.

Benefit #2

Spread internal adoption of their churn reduction model.

Benefit #3

Increased the amount of data they now include in their models, moving from thousands of rows of data to millions.

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Overview

Buildertrend: Maximizing Data Project Speed to Value

Operational Impact

Quantitative Benefit