Data Science Platform for Retail Companies

Technology innovation, digitalization, and machine learning models have fundamentally changed the retail industry landscape. Making model-driven business decisions and leveraging machine learning with the best-of-breed tools is the key to success in this rapidly changing industry.

“The path that we’re taking at Gap is to leverage third parties like Domino… to help us quickly solve problems that we couldn’t solve on our own”

— Matt Cornett, Senior Director of Data Science Operations and Tools at Gap

Challenges

One-Off Requests
Ad Hoc Requests

Competitors, consumer preferences, fashion trends, and market dynamics are constantly changing. Data scientists at retailers are often asked to work on one-time analyses or meet urgent ad hoc requests, which is inefficient, frustrating, and not reproducible.

Legacy Systems
Legacy Systems

The retail industry has many legacy systems and faces complex data access and management issues around consumer privacy and omnichannel integration, making it difficult to deploy and integrate new technologies.

Deploy models into production
Deployment

Putting models into production is difficult for retailers due to operational and data infrastructure complexibility, constant changes, global scale and supply chain, large network of staff, numerous touch points, and high expectations from consumers.

Benefits for Retail Companies

Personalized Experiences
Personalization

Consumers now expect brands to anticipate their needs, to recommend the products they want, and to communicate through preferred channels with the right price and availability in real time.

Inventory Planning
Inventory

Machine learning algorithms fit nicely with the needs of inventory planning. Data scientists can train models based on the large number of behavioral data to help planners work much faster and more accurately.

Fraud Detection
Fraud Detection

Machine learning can identify anomalies such as unusual patterns in trading data, and alert risk managers for further investigation or trigger automated remediation.

Trusted Throughout the Retail Industry

Leverage data science to understand the rapidly shifting attitudes and sentiments of highly informed buyers across channels. Retailers need to utilize the enormous amount of data to increase conversion rates and revenue. Data science play a crucial role in understanding the consumer in order to get more goods ‘into the basket’ and to the consumer quicker.

Domino provides data scientists automated reproducibility and easy access to the tools they prefer. Domino also enables faster execution by allowing data scientists to quickly deploy models and share results with business stakeholders such marketing team, planning team and store managers.

Gap
Bluestem Brands
FabFitFun
FlexShopper

Lessons learned from modernizing data science and analytics at Gap (PDF) →


Make your business model-driven.

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