Oracle Retail

Advanced Clustering

Today’s consumers are becoming more demanding as they shop

multiple retailers and expect a unique shopping experience in their

channel of choice. Retailers must provide profitable and relevant

assortments, promotions, and prices to compete in an evolving

landscape of pure play, general merchants, and traditional competitors.

Consumers speak to retailers with their purchase patterns, shopping

preferences, and buying behaviors. With a view across stores,

geographies, and markets, retailers can improve store performance and

drive market share with a loyal customer base by understanding and

catering to the unique needs of their customers.

CENTRALIZED ENTERPRISE SOLUTION Oracle Retail Advanced Clustering is a capability that sits atop the Oracle Retail AI

Foundation, which provides analytical insights to drive planning, buying, moving and

selling decisions. These capabilities enable retailers to drive profit and remain flexible to

the changing retail environment.

It is an enterprise-specific clustering solution that leverages data mining capabilities

to create store and customer groupings at various product, customer, and location

levels using multiple inputs. These inputs can include performance data, category

purchase data, product attributes, store attributes, and third-party data such as

demographic and/or market information, as well as consumer or customer

segments.

Using embedded retail analytics and automation capabilities, retailers will be able to

easily identify unique patterns within available data. This allows retailers to create

customer-centric and targeted clusters to be utilized by downstream assortment

planning, forecasting, allocation/replenishment, pricing, and promotions planning

processes.

The analytical insights of Oracle Retail Advanced Clustering acknowledges retail

specific scenarios and complexity when building the modeling approach and applying

algorithms. The retail-specific analytics builds confidence in the recommended

actions and ability solve issues relevant to the complexity of our industry.

A centralized and streamlined approach to the creation of clusters helps to support

and align the business strategy across assortment, pricing, promotion,

replenishment/allocation, marketing, and space specific processes. Integration with

other Oracle Retail applications reduces complexity in creating this centralized view.

The solution offers a range of distance metrics suitable for real-valued attributes,

categorical attributes, profile-based measurements, as well as time-based

performance metrics.

Key Benefits

 Leverage customer insights

through analytics to drive a

notable increase in sales

 Enable the creation of

customer-centric, targeted

clusters

 Increase financial

performance and inventory

productivity when leveraged

in key planning processes

 Improve store operations

 Accommodate dynamic

business priorities with a

flexible solution

 Fully productized advanced

analytics is available

exclusively on the Oracle

Cloud without a heavy capital

investment

https://www.oracle.com/industries/retail/assortment-space-optimization/#:~:text=Optimize%20assortments%20to%20available%20space,optimal%20assortment%20for%20each%20store.

FIT FOR PURPOSE

The Oracle Retail Advanced Clustering provides retailers with multiple approaches and

methods when generating clusters. The system is highly flexible and dynamic to

support a number of different cluster algorithms, depending on your clustering needs.

This comprises of the creation of simple, nested and/or mixed attribute clusters using

multiple methods which support discrete / non-discrete attributes:

 Intelligent clusters utilizing machine learning (Selling Patterns, Attributes,

Demographics, etc.)

 Performance-based clusters (Sales Revenue, Sales Units, Gross Profit %, etc.)

 Product attribute-based clusters (Brand, Color Family, Price Band, etc.)

 Location attribute-based clusters (Store Size, Climate, Population Size, etc.)

 Consumer profile-based clusters (Customer Demographics, Category

Purchase behavior, Customer Purchase Behavior, etc.)

 Combination of one or more of above

The clustering process focuses around a very quick and intuitive 3-step process to

create, review, and approve store clusters for downstream solution use. This includes

providing the ability to define and use clustering templates which can be specific to

given product/location combinations and easy drag/drop of stores into clusters for

overrides. System generated rankings and importance factors help users understand

complex statistical concepts.

Users are also able to access and use rich contextual reporting analysis to review and

drive key decisions related to the clustering process. This includes:

 Assisting retailers to determine what categories or merchandise classifications

benefit most from clustering, what level of customer data, product or location

hierarchy to cluster at as well as what attributes should be leveraged

 Review key details related to the available cluster recommendations; assessing

areas such as cluster composition, performance, attributes as well as store

level scores (in relation to total cluster)

 Cluster scenario comparison; enabling users to visually assess differences

between the respective cluster details

ORACLE CLOUD INFRASTRUCTURE

All Oracle Retail Analytics and Planning cloud services are deployed as cloud-native

Software-as-a-Service solutions within Oracle Cloud Infrastructure (OCI) upon Oracle’s

Autonomous Data Warehouse, and are based upon an architecture and technology

stack that is optimally engineered for rapid, low-cost deployments and exceptional

performance and scalability, and the highest levels of system availability and security -

from storage to scorecard.

ORACLE RETAIL AI FOUNDATION

Core retail AI and machine learning (ML) powers all Oracle Retail Analytics and

Planning cloud services. For example:

Forecasting Engine - Provide an intelligent starting point for your planners, increasing

automation and accuracy. Move to a more touchless and exception management

planning process.

Customer Segmentation - Group customers based on attributes, behaviors, and

transactions to tailor offers, pricing, and assortments accordingly, incorporating

previously hidden patterns in your data.

Advanced Clustering - Cluster your stores based upon traditional approaches of

volume, square footage, region, etc., or leverage machine learning techniques to cluster

stores based upon similar selling patterns, truly creating a customer-centric assortment.

Key Features

 Ability to cluster at multiple

levels within the available

hierarchies

 Dynamic nesting/mixing of

product attributes, location

attributes, consumer

segments, as well as

performance data

 Available scoring logic

provides the ability to easily

identify outliers or areas of

opportunity

 Pre-defined templates to drive

a quick & efficient clustering

process

 Embedded and automated data

cleansing

 Embedded Retail AI Foundation,

powering Oracle Retail Demand

Forecasting Cloud Service with:

o Forecasting Engine

o Customer Segmentation

o Advanced Clustering

o Profile Science

o Attribute Extraction &

Binning

o Customer Decision Trees

o Demand Transference

o Affinity Analysis

o Innovation Workbench

 Further extensibility with:

o Oracle Retail Home

o Oracle Analytics

o Oracle Application Express

o Oracle REST Data Services

o Oracle Machine Learning

Profile Science - Determine the best size ratio for your buys by understanding the true

demand of your sizes while considering stock-outs.

Attribute Extraction and Binning - Extract item attributes from free-form descriptions,

correcting short forms, misspellings, and other inconsistencies, and apply them to

Demand Transference, Customer Decision Trees, Advanced Clustering, and more.

Customer Decision Trees - Understand how your customers are shopping your

assortments to drive attribute-based alternate hierarchies and effectively plan your

assortment the way your customer shops.

Demand Transference - Understand how unique your items are and the incremental

revenue that item brings to determine the most optimal assortment for your customer.

Affinity Analysis - Determine how items interact with each other to drive a more

effective promotional strategy within your financial planning process.

Innovation Workbench - Leverage open source along with your data science team to

create your own AI and ML models. Utilize the language of your choice with

Jupyter/Zeppelin notebooks.

ORACLE RETAIL HOME

Oracle Retail Home is a single access point, to simplify a user’s interactions with the data

and applications that are most relevant to their roles, and to better empower them to

anticipate informed

actions, and to inspire

engagement.

Based on a robust and

flexible portal

framework, Retail Home

is intended first to

provide timely and role-

specific high-level

insights, and second to

enable selectively

drilling into relevant

applications for more

details.

ORACLE ANALYTICS

Oracle Analytics can be used to generate and consume analytics from Oracle Retail AI

Foundation data, and in turn can also surface dashboards to Oracle Retail Home.

Oracle Analytics is a comprehensive platform that parlays data into information to

provide business insights, federating a broad array of features to suit business users,

power users and data scientists:

Governed Self-Service Augmented

 Corporate Dashboards  Data Preparation  Natural Language Processing

 Pixel Perfect Report  Data Visualization  Voice and Chatbot

 Semantic Models  Storytelling  Data Enrichment

 Role-based Access Control  Sharing and Collaboration  One-Click “Explain”

 Query Federation  Mobile Apps  Adaptive Personalization

https://video.oracle.com/detail/video/5828487828001

Beyond the extensibility afforded by the Oracle Retail AI Foundation’s Innovation

Workbench, Oracle Analytics, and Oracle Retail Home, also included are Oracle Data

Store, Oracle APEX, and Oracle REST Data Services.

ORACLE DATA STORE AND APPLICATION EXPRESS

Oracle Retail Data Store can supply data for Oracle Application Express (APEX) apps

and Oracle REST Data Services, which both are included. APEX is a low-code

development platform that enables you to build scalable, secure enterprise apps with

world-class features that can be deployed anywhere.

Developers can quickly develop and deploy compelling apps that solve real problems

and provide immediate value using APEX. You won't need to be an expert in a vast

array of technologies to deliver sophisticated solutions. Focus on solving the problem

and let APEX take care of the rest.

ORACLE REST DATA SERVICES

Oracle REST Data Services bridges HTTPS and your Oracle Database, providing,

among other things, a REST API, SQL Developer Web, a PL/SQL Gateway, SODA for

REST, and the ability to publish RESTful Web Services for interacting with the data and

stored procedures in your Oracle Database.

ORACLE MACHINE LEARNING

Oracle Machine Learning supports data exploration, preparation, and machine

learning modeling at scale using SQL, R, Python, REST, AutoML, and no-code

interfaces. It includes more than 30 high-performance in-database algorithms

producing models for immediate use in applications.

By keeping data inside the database, organizations can simplify their overall

architecture and maintain data synchronization and security. It enables data scientists

and other data professionals to build models quickly by simplifying and automating

key elements of the machine learning lifecycle.

Learn more or request 1:1 demo

CONNECT WITH US

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