Dataiku Case Studies Showroomprivé: Putting ML-Powered Targeting in the Hands of Marketers

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	Showroomprivé: Putting ML-Powered Targeting in the Hands of Marketers Dataiku

Showroomprivé: Putting ML-Powered Targeting in the Hands of Marketers

Dataiku

Technology Category	Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Retail
Applicable Functions	Sales & Marketing
Use Cases	Predictive Quality Analytics Demand Planning & Forecasting
Services	Data Science Services
Challenge	Showroomprivé, an e-commerce retailer specialized in flash sales, faced challenges in targeting their marketing emails. Until 2016, the team selected the target audience for these marketing emails manually based on what they know about the brand. However, this approach presented several challenges. Brands often have overlapping or broad audiences, which meant touching some prospective buyers multiple times, while others not at all. This also meant casting out a wide net, potentially sending emails to people who were not interested in that particular brand. The ultimate goals of the project was for the marketing team to be completely autonomous in targeting and sending these emails. Read More
About Customer	Showroomprivé is an e-commerce retailer specialized in flash sales. The company has approximately 950 employees and is present in 7 countries across Europe. The company has a data team of 16 members across 4 data teams. Showroomprivé has been at the cutting-edge of leveraging data for improvements both in the product and in customer service as well as on the operational and business side. The company has been working from the ground up to develop its capacity to use data for these improvements. Read More
Solution	Showroomprivé leveraged Dataiku to develop a machine learning-based targeting system for their marketing campaigns. The system, known as Targetor, allows marketers to generate their own machine learning-powered targeting recommendations. The company went through three iterations of Targetor to perfect the system and add additional features over the course of four years. The marketing and data teams were even able to make improvements for a second iteration of Targetor that provided a ranking of users instead of just a homogenous group, allowing marketers to better prioritize their campaigns. After about a year and a half of use by the marketing team, the data team at Showroomprivé was adding so much functionality and so many features that the model was becoming complex. They decided to undergo a project that would streamline the model, allowing them to continue to scale and add functionality for many years to come. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Retail

Applicable Functions

Sales & Marketing

Use Cases

Predictive Quality Analytics

Demand Planning & Forecasting

Services

Data Science Services

Challenge

Showroomprivé, an e-commerce retailer specialized in flash sales, faced challenges in targeting their marketing emails. Until 2016, the team selected the target audience for these marketing emails manually based on what they know about the brand. However, this approach presented several challenges. Brands often have overlapping or broad audiences, which meant touching some prospective buyers multiple times, while others not at all. This also meant casting out a wide net, potentially sending emails to people who were not interested in that particular brand. The ultimate goals of the project was for the marketing team to be completely autonomous in targeting and sending these emails.

About Customer

Showroomprivé is an e-commerce retailer specialized in flash sales. The company has approximately 950 employees and is present in 7 countries across Europe. The company has a data team of 16 members across 4 data teams. Showroomprivé has been at the cutting-edge of leveraging data for improvements both in the product and in customer service as well as on the operational and business side. The company has been working from the ground up to develop its capacity to use data for these improvements.

Solution

Showroomprivé leveraged Dataiku to develop a machine learning-based targeting system for their marketing campaigns. The system, known as Targetor, allows marketers to generate their own machine learning-powered targeting recommendations. The company went through three iterations of Targetor to perfect the system and add additional features over the course of four years. The marketing and data teams were even able to make improvements for a second iteration of Targetor that provided a ranking of users instead of just a homogenous group, allowing marketers to better prioritize their campaigns. After about a year and a half of use by the marketing team, the data team at Showroomprivé was adding so much functionality and so many features that the model was becoming complex. They decided to undergo a project that would streamline the model, allowing them to continue to scale and add functionality for many years to come.

Impact #1	Empowered people, providing a webapp (known as Targetor, which is powered by Dataiku and used 2-3 times per day by the business) that allows marketers to generate their own machine learning-powered targeting recommendations.
Impact #2	Honed data processes, going through three iterations of Targetor to perfect the system and add additional features over the course of four years.
Impact #3	Harnessed technology to make it all happen, using Dataiku from testing to model development to delivery and among both data scientists and marketers alike for true vertical and horizontal collaboration around the initiative.

Impact #1

Empowered people, providing a webapp (known as Targetor, which is powered by Dataiku and used 2-3 times per day by the business) that allows marketers to generate their own machine learning-powered targeting recommendations.

Impact #2

Honed data processes, going through three iterations of Targetor to perfect the system and add additional features over the course of four years.

Impact #3

Harnessed technology to make it all happen, using Dataiku from testing to model development to delivery and among both data scientists and marketers alike for true vertical and horizontal collaboration around the initiative.

Benefit #1	Marketing campaigns that are 2.5x more effective.
Benefit #2	Increased autonomy of the marketing team in targeting and sending emails.
Benefit #3	Improved prioritization of marketing campaigns.

Benefit #1

Marketing campaigns that are 2.5x more effective.

Benefit #2

Increased autonomy of the marketing team in targeting and sending emails.

Benefit #3

Improved prioritization of marketing campaigns.

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Overview

Showroomprivé: Putting ML-Powered Targeting in the Hands of Marketers

Operational Impact

Quantitative Benefit