Dataiku Case Studies Revolutionizing Dynamic Pricing with Pricemoov and Dataiku

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	Revolutionizing Dynamic Pricing with Pricemoov and Dataiku Dataiku

Revolutionizing Dynamic Pricing with Pricemoov and Dataiku

Dataiku

Technology Category	Analytics & Modeling - Predictive Analytics Automation & Control - Human Machine Interface (HMI)
Applicable Industries	E-Commerce Retail
Use Cases	Personnel Tracking & Monitoring Time Sensitive Networking
Challenge	Pricemoov, a yield management solution provider, faced a significant challenge in handling and cleaning data from old SI systems, Oracle, or MySql. The data was dirty and required a full-time developer to perform long ETL (extract-transform-load) steps in PHP for cleaning. Once cleaned, the datasets were painstakingly entered into a model, as they were custom-built pipelines. The replication and deployment process for the next customer was taking weeks. This slow and inefficient process was hindering Pricemoov's ability to provide optimal pricing suggestions and solutions to its customers in a timely manner. Read More
About Customer	Pricemoov is a Plug and Play Yield Management solution provider founded in 2016. It has been experiencing strong growth and its users include car rental services, airline companies, and event organizers. Pricemoov provides a service that delivers optimal pricing suggestions and solutions to its customers by weighing the intrinsic value of the item, its seasonality, and the attributes of the customer himself through detailed segmentation. To do so, Pricemoov collects datasets from its customers that are updated daily through partitioning. Read More
Customer Name	PriceMoov Read More
Solution	Pricemoov adopted Dataiku, a tool that transformed their business by significantly speeding up data cleaning processes and enabling quick replication of existing work. This allowed Pricemoov to run proof-of-concepts for potential customers on short notice and provide better pricing options overall. The Data Department at Pricemoov used Dataiku to replicate existing workflows, speed up data cleaning and exporting, and enable less experienced staff to assist with this process. This left tenured data scientists to focus on modeling rather than data prep and plumbing. Non-technical teams could build their skills and scale their efforts thanks to an intuitive, visual point-and-click interface. Dataiku also helped Pricemoov to better define a specific price per customer that evolves over time by melding data indicating demand with customers’ willingness to pay. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Automation & Control - Human Machine Interface (HMI)

Applicable Industries

E-Commerce

Retail

Use Cases

Personnel Tracking & Monitoring

Time Sensitive Networking

Challenge

Pricemoov, a yield management solution provider, faced a significant challenge in handling and cleaning data from old SI systems, Oracle, or MySql. The data was dirty and required a full-time developer to perform long ETL (extract-transform-load) steps in PHP for cleaning. Once cleaned, the datasets were painstakingly entered into a model, as they were custom-built pipelines. The replication and deployment process for the next customer was taking weeks. This slow and inefficient process was hindering Pricemoov's ability to provide optimal pricing suggestions and solutions to its customers in a timely manner.

About Customer

Pricemoov is a Plug and Play Yield Management solution provider founded in 2016. It has been experiencing strong growth and its users include car rental services, airline companies, and event organizers. Pricemoov provides a service that delivers optimal pricing suggestions and solutions to its customers by weighing the intrinsic value of the item, its seasonality, and the attributes of the customer himself through detailed segmentation. To do so, Pricemoov collects datasets from its customers that are updated daily through partitioning.

Customer Name

PriceMoov

Solution

Pricemoov adopted Dataiku, a tool that transformed their business by significantly speeding up data cleaning processes and enabling quick replication of existing work. This allowed Pricemoov to run proof-of-concepts for potential customers on short notice and provide better pricing options overall. The Data Department at Pricemoov used Dataiku to replicate existing workflows, speed up data cleaning and exporting, and enable less experienced staff to assist with this process. This left tenured data scientists to focus on modeling rather than data prep and plumbing. Non-technical teams could build their skills and scale their efforts thanks to an intuitive, visual point-and-click interface. Dataiku also helped Pricemoov to better define a specific price per customer that evolves over time by melding data indicating demand with customers’ willingness to pay.

Impact #1	The adoption of Dataiku transformed Pricemoov's operations. It enabled the company to quickly submit pricing options to local branches of brick-and-mortar stores, who could then choose to accept the options or not and could seamlessly share feedback to improve the model. It also allowed Pricemoov to deliver specific insight for local branches by quickly applying geo clustering. The use of Dataiku's visual point-and-click interface enabled non-technical teams to build their skills and scale their efforts, with the long-term goal of having them efficiently and independently leveraging website clickstreams and HDFS datasets.

Impact #1

The adoption of Dataiku transformed Pricemoov's operations. It enabled the company to quickly submit pricing options to local branches of brick-and-mortar stores, who could then choose to accept the options or not and could seamlessly share feedback to improve the model. It also allowed Pricemoov to deliver specific insight for local branches by quickly applying geo clustering. The use of Dataiku's visual point-and-click interface enabled non-technical teams to build their skills and scale their efforts, with the long-term goal of having them efficiently and independently leveraging website clickstreams and HDFS datasets.

Benefit #1	Pricemoov had a two-week improvement in the speed at which they could produce pricing and forecast models.
Benefit #2	Created 10 times more scenarios with the help of Dataiku.
Benefit #3	Improved in staff performance and development.

Benefit #1

Pricemoov had a two-week improvement in the speed at which they could produce pricing and forecast models.

Benefit #2

Created 10 times more scenarios with the help of Dataiku.

Benefit #3

Improved in staff performance and development.

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Overview

Revolutionizing Dynamic Pricing with Pricemoov and Dataiku

Operational Impact

Quantitative Benefit