Dataiku Case Studies Revolutionizing Dynamic Pricing with Pricemoov and Dataiku
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Revolutionizing Dynamic Pricing with Pricemoov and Dataiku

Revolutionizing Dynamic Pricing with Pricemoov and Dataiku - Dataiku Industrial IoT Case Study
Analytics & Modeling - Predictive Analytics
Automation & Control - Human Machine Interface (HMI)
Personnel Tracking & Monitoring
Time Sensitive Networking
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.
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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.
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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.
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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.
Pricemoov had a two-week improvement in the speed at which they could produce pricing and forecast models.
Created 10 times more scenarios with the help of Dataiku.
Improved in staff performance and development.
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