デジタル作品

​Data Modeling

Analyze and define customer behavior and purchasing data using machine learning to build emotional customer experience

​Personalization

Personalization is the key to improving the customer experience.  According to Epsilon survey, 80% of shoppers responded they would buy from a retailer that offers a personalized customer experience.  Personalized customer experience drives a competitive advantage of retailers.  At the same time, 53% of surveyed companies responded that they lack the right technology to personalize experiences according to Forrester.   

Data Analytics Solutions for Retailers

A wide range of data analytics needs for retail companies across the value chain.  Embracing the test and learn approach, we help our clients to start small and scale fast.

Production

Procurement

  • Supplier management

  • Purchase order

  • JIT procurement

  • Re-order inventory level

  • Demand forecast

Inventory

Replenishment

  • Inventory turnaround

  • Over stock value

  • Dead stock rate

Retail

  • Sales KPIs

  • Assortment performance

  • Market basket

  • Price elasticity

  • Modular turnover

  • Campaign performance

  • Cashier performance

Customer

Management

  • Customer segmentation

  • Business area

  • Customer satisfaction

  • Customer reach-out

  • Customer needs

Finance

  • Budget analysis

  • Cost analysis

  • Stock depreciation

  • Revenue forecast

Building Personal Touchpoints in the Customer Journey

We define and measure KGIs (Key Goal Indicators) of personal touchpoints in the customer journey.

Customer Acquisition

  • Targeting

  • Profiling

  • Data mining

  • CTR/CVR analysis

Conversion Rate

  • Browsing behavior analysis

  • Purchase history analysis

  • Demography analysis

Retention Rate

  • Basket drop rate

  • Customer satisfaction

Awareness

Acquire

Retain

Advocacy

Traffic Driver

  • Campaign performance

  • Influencer analysis

  • Media channel analysis

Basket Size

  • Campaign performance

  • Coupon usage

  • Bot effectiveness

Building Target Sate Extensible Data Business Model

Building a data business model to embrace insight driven decision making and evolve extended business opportunities.

Continuous Innovation to Existing Business

New Value to Customers

Operation

Excellence

Promotion Enhancement

Customer Offering

Media

Platform

Ecosystem

Partnership

Analyzing purchase history data of customers, improve internal operations in marketing, inventory, merchandising, and replenishment.

Understanding the needs of customers from purchase history data, enhance product recommendations and loyalty programs for customers. 

Leveraging data insights to improve customer offering

Build a media platform business based on data assets in association with customers shopping experience

Reinvent customer experiences by building ecosystem services that enables mutual use of business partners' services