Glossary of Data Science and Data Analytics

What is Retail Analytics?

Informatica
DATA MANAGEMENT

Retail analytics is the analysis of data generated by retail transactions in order to make profitable business decisions. The use of retail analytics has emerged as a response to retail transformation driven by unprecedented changes in customer behavior, intense pressure on margins, changing roles of stores, and intense competition for both online and offline channels.

To survive and succeed in this challenging environment, retailers must improve efficiency and automation in their multi-channel processes. They must stay one step ahead of customer demands and optimize their customer journey to create a frictionless, seamless online and offline customer experience. Many retailers are turning to retail analytics, a broad set of powerful analytics, such as pricing and diversity optimization, location analytics, and customer-driven marketing, to increase their competitive advantage and generate sales and profits.

Retailers must capture large amounts of data (customer, store, financial, product, inventory, employees, and call center) and provide an integrated view of insights into business, trends, and customer behavior across the enterprise. This transformation process begins by implementing an advanced data and analytics environment consisting of an integrated data warehouse (IDW).

Retail analytics helps identify new opportunities, create personalized marketing and communication programs, increase revenue streams with profitable customers, and provide the right products and services that meet and exceed customer expectations. As they see how all aspects of a business relate to each other, retailers can discover answers to critical questions such as:

· What products do my best customers receive and through which channels?

· Am I selling these products at the right price, in the right place in the store, and in the right color, size, and quantity combinations?

· Which products fill the baskets the most in terms of sales volume, earnings or profitability?

· How does provider performance compare to other providers in the category in terms of sales, profitability and service level?

· What is the stock percentage of my best-selling products?

· What would be the best expected price for this product?

· What promotions should we offer to each customer segment, when, for how long and in what channels?

· What is the financial capacity and substitute value of a product based on the customer's browsing behavior versus purchasing behavior?

· Are my jobs planned and programmed efficiently to minimize business costs while maximizing customer service and sales?

· How can I improve customer service and the products I offer based on customer feedback?

· What is the preferred interaction channel for a particular customer tube aimed at different shopping interactions and product categories

· What is the total common benefits obligation of the company and how much has this liability increased or decreased compared to the previous year according to the plan and the demographics involved?

 

Key retail business process areas that can be optimized using retail analytics are:

· Merchandising

· Diversity/Category Management/Product Mix (PMIX)

· Product Pricing and Cost Detail

· Inventory Management

· RFID/Serial Product Tracking and Tracking

· Shipment, Shipment and Requests

· Transportation Logistics (Distribution and Logistics)

· Invoice

· Contracts (Registration and Terms)

· Supply

· Showcase Display Plan

· Promotion Management and Marketing

· Point of Sale Operations

· Detail and Realization

· Catalog Sales and

· Content Management

· Recall Management

· Customer Value, Shopping and Product Buying Behaviors

· Feedback About Quality

· Loyalty and Gift Voucher

· Usage Behaviors

· Warehouse Business and Operations

· Human Capital Management (Human Resources)

· Privacy and Provider Management

· Call Center Productivity

· Integral Channel Trading and Interactions

· Forecasting and Scoring

· Financial Management

· Retail Pharmacy

· Markt

· Textile

· Catering Services

· Kitchen and Waiting

· Time Management

· Service Tips

· Compliance with Reporting

· Compliance with Sales Taxes and Fees

 

Increasingly, data and analytics are the lifeblood of the retail industry, essential to both survival and success. Retailers' challenge is to capture and store exploding volumes and types of data in a cost-effective way, analyze data quickly and reliably, and then deploy insights into every channel retailers touch a customer or supplier.

back to the Glossary

Discover Glossary of Data Science and Data Analytics

What is Self-Service Analytics?

Explore the world of self-service analytics, explore its definition, interaction with big data a self-service business intelligence, and its numerous advantages. Learn how self-service analytics democratizes data and enables businesses to make data-driven decisions quickly and independently

READ MORE
What is Product Lifecycle Management?

Product lifecycle management refers to the examination of a product as it goes through certain stages of its lifecycle.

READ MORE
What is Deep Learning?

Deep learning, also known as deep neural learning or deep neural network, is an artificial intelligence (AI) function that mimics the way the human brain works to process data and create patterns that facilitate decision-making.

READ MORE
OUR TESTIMONIALS

Join Our Successful Partners!

We work with leading companies in the field of Turkey by developing more than 200 successful projects with more than 120 leading companies in the sector.
Take your place among our successful business partners.

CONTACT FORM

We can't wait to get to know you

Fill out the form so that our solution consultants can reach you as quickly as possible.

Grazie! Your submission has been received!
Oops! Something went wrong while submitting the form.
GET IN TOUCH
SUCCESS STORY

Eczacıbaşı - Data and Analytics Strategic Assessment

We launched the Rota project with Eczacıbaşı to implement the data and analytics strategy framework.

WATCH NOW
CHECK IT OUT NOW
5
Data and Analytical Strategy Dimension
6
Holding Company
2022
Analytic Strategies for
Cookies are used on this website in order to improve the user experience and ensure the efficient operation of the website. “Accept” By clicking on the button, you agree to the use of these cookies. For detailed information on how we use, delete and block cookies, please Privacy Policy read the page.
Veri Bilimi ve Veri Analitiği Sözlüğü

Heading

Heading