A TRANSFORMATIONAL JOURNEY SINCE 1999 TOWARDS IT TRAINING ADVANCEMENT, ACHIEVEMENT AND PLACEMENT.
TODAY WE ARE PROUD TO TELL YOU THAT, WE HAVE TRAINED MORE THAN 20,000 STUDENTS.
The document discusses Manthan Retail Analytics, a comprehensive analytics solution designed to improve retail decisions and drive profitable sales growth. It can provide descriptive, diagnostic, predictive, and prescriptive analytics across key retail functions. The solution offers pre-configured analytical insights, dashboards, and self-service analytics capabilities. It has modules for various retail operations and delivers benefits like improved margins, sales growth, inventory reductions, and loss prevention.
Cenacle Research is engaged in building Predictive Analytics Engines for Automotive, Healthcare, Retail, Energy and BFSI sector. This presentation details how our Big data Analytics platform can help retail businesses in a brief manner.
Big Data offers: Actionable Insights that let you make Informed Decisions, with the capability to:
+ Gain Insight
+ Take Proactive action
+ Reduce waste
+ Plan better strategy
To know more, write to us at: http://cenacle.co.in/
This document contains confidential information belonging to AAUM. It discusses various analytical techniques such as customer segmentation, market basket analysis, forecasting, and supply chain optimization that can be applied across industries. Case studies of companies like Tesco, Nieman Marcus, and Food Lion demonstrate how these techniques have been successfully used to increase sales, optimize operations, and improve customer experience.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
This document contains confidential information about AAUM's analytics products and services. It provides an overview of AAUM's capabilities in advanced analytics, competitive intelligence, and livelihood services. It then presents a case study analyzing social media sentiments before and after the release of two Tamil films, Nanban and Vettai, to demonstrate AAUM's social media analytics product called "Ordo Ab Chao." The analysis shows mostly positive sentiment for both films both before and after release.
The document discusses Manthan Retail Analytics, a comprehensive analytics solution designed to improve retail decisions and drive profitable sales growth. It can provide descriptive, diagnostic, predictive, and prescriptive analytics across key retail functions. The solution offers pre-configured analytical insights, dashboards, and self-service analytics capabilities. It has modules for various retail operations and delivers benefits like improved margins, sales growth, inventory reductions, and loss prevention.
Cenacle Research is engaged in building Predictive Analytics Engines for Automotive, Healthcare, Retail, Energy and BFSI sector. This presentation details how our Big data Analytics platform can help retail businesses in a brief manner.
Big Data offers: Actionable Insights that let you make Informed Decisions, with the capability to:
+ Gain Insight
+ Take Proactive action
+ Reduce waste
+ Plan better strategy
To know more, write to us at: http://cenacle.co.in/
This document contains confidential information belonging to AAUM. It discusses various analytical techniques such as customer segmentation, market basket analysis, forecasting, and supply chain optimization that can be applied across industries. Case studies of companies like Tesco, Nieman Marcus, and Food Lion demonstrate how these techniques have been successfully used to increase sales, optimize operations, and improve customer experience.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
This document contains confidential information about AAUM's analytics products and services. It provides an overview of AAUM's capabilities in advanced analytics, competitive intelligence, and livelihood services. It then presents a case study analyzing social media sentiments before and after the release of two Tamil films, Nanban and Vettai, to demonstrate AAUM's social media analytics product called "Ordo Ab Chao." The analysis shows mostly positive sentiment for both films both before and after release.
Predictive Analytics in Retail - Visual Infographic Reportc24ltd
A visual infographic report about Predictive Analytics in Retail, based on our whitepaper "Predictive Analytics in Retail" (link: https://blog.c24.co.uk/2016/08/17/c24-publishes-new-predictive-analytics-whitepaper/).
We explore the ways in which Predictive Analytics is set to change how retailers make use of big data, analytics and insights across their customers, supply chain and stores.
This document provides an overview of Snapdeal and Infibeam, two major Indian e-commerce companies. For Snapdeal, it summarizes their business model as a marketplace, growth in revenue from 2012-2014, investments in supply chain and logistics to improve delivery times, and use of social media marketing. For Infibeam, it outlines their hybrid business model involving both direct sales and as a marketplace, profitability achieved in 2012-2013, investments in their own logistics arm and logistics aggregation platform, and social media promotions.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
This document discusses analytics and retail analytics. It defines analytics as discovering patterns in data through statistics, programming, and research. Retail analytics specifically aims to improve customer loyalty and sales. It does this by identifying valuable customers, understanding their preferences, and creating personalized shopping experiences through offers targeted to individual needs. Retailers can gather customer data through in-store and online analytics to gain insights that optimize performance.
This document describes a webinar that discussed next generation business and retail analytics technologies. The webinar covered challenges with current business intelligence tools, new analytics vendors and tools, trends in retail analytics, and case studies of companies using new analytics tools to improve performance.
State of Analytics: Retail and Consumer GoodsSPI Conference
There is little doubt that Business Analytics will become a core differentiator in consumer industries, but even though Retail and Consumer Goods companies view analytics as extremely strategic, they struggle to effectively leverage it across the enterprise. EKN has studied the adoption and impact analytics in these industries for the last 5 years, and this counterpoint presentation will summarize key trends in analytics and shares fresh 2016 data on the state of analytics. Presented by Joe Skorupa (Editorial Director, RIS News) & Gaurav Pant (Senior VP Research & Principal Analyst, EKN Research) at the 2016 SPI Conference.
The document discusses various analytics techniques used in retail decision making including store layout planning, merchandising, assortment optimization, sales forecasting, inventory management, vendor management, loyalty analytics, pricing analysis, promotion optimization, and market basket analysis. The key goal of applying these decision science techniques is to maximize revenue, sales, footfalls, and profitability through optimal allocation of space, inventory, pricing, promotions and understanding of consumer purchasing behavior.
Inventory management is key for profitability in retail. Disappointing customers by missing trends or not meeting their demand puts retailers in a serious deficit. This report covers .. why harnessing inventory data is critical for success, what KPIs are essential for effective inventory management, which POS reports all retailers should run and when, and more! Enjoy the report, and visit us at springboardretail.com for even more inventory management content.
This document discusses using predictive analytics for retail businesses. It outlines using store clustering and RFM (recency, frequency, monetary) analysis to develop predictive models. Store clusters would be used to design customized planograms and segmentation strategies. RFM would analyze active and expired customers to develop targeted strategies like offering discounts or new products to high value customers or win back lower value, expired customers. The overall goal is to use predictive models to improve planogram performance, customer retention and reactivation, and sales.
The document provides an overview of marketing analytics. It introduces the presenter and outlines an agenda that covers descriptive, predictive, and prescriptive analytics. Marketing analytics are defined as measuring, managing, and analyzing trends to maximize marketing strategy effectiveness. Examples are given of how companies use analytics. The document then discusses measurement sources, applications, benefits, and tools of marketing analytics.
Case Studies - Customer & Marketing Analytics for Retail Gurmit Combo
The document discusses three case studies involving customer intelligence and marketing effectiveness services:
1. A luxury retailer case study where customer segmentation and profiling identified their most valuable customers to focus relationship management efforts.
2. A technology company case study where product association analysis and scoring identified accounts likely to purchase docking stations for targeted cross-selling.
3. A CPG company case study where regression modeling decomposed the impact of price, promotion, competition and cross-category effects on sales volumes, revealing promotion strategy optimizations.
NRF 2019: Retail's Big Show
Sunil Suram, Director of AI and Big Data, Tango
Pranav Tyagi, President and CEO, Tango
Mark Zygmontowicz, SVP, Business Development, Tango
The document discusses how analytics can be used to solve business problems in the retail banking industry. It describes how analytics can be applied to various areas of a bank's profit and loss statement, including acquiring new customers, reducing customer attrition, improving account activation rates, and maximizing revenue from interest, fees, and cross-selling. It also discusses how strategic reporting, marketing analytics, and data-driven insights can be used for segmentation, customer lifetime value analysis, profitability and loyalty analysis, cross-selling strategies, and customer retention programs. The overall aim is to provide a top-down analytical approach to optimize all areas of a bank's operations and financial performance.
SAP WHITEPAPER: Reacting in the Retail Moment, Analyzing Big Data in Real Tim...Beyond Technologies
Under any circumstances, retail is an extremely competitive industry. But today, an uncertain economy and low consumer confidence, coupled with shorter product lifecycles and well-informed, demanding customers, make it especially difficult to execute a profitable strategy.
Retailers have only a narrow window to make the sale and seize the opportunity. Thriving in this environment means maximizing the profit potential of each interaction, transaction, and customer contact.
business analytics and its importance, marketing analytics definition and its importance, how marketing analytics helps to run the organization in effective and efficient manner.
The document discusses the importance of selecting the right retail store location and introduces the OPTILOX model for optimizing location selection. OPTILOX uses behavioral analytics and considers factors like customer demographics, preferences, and footfall patterns to evaluate potential locations and forecast customer numbers. It helps retailers make faster and more informed decisions to maximize the success of new store openings.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
An innovative monetization strategy requires much more than meets the eye. While many organizations focus their efforts on acquiring new customers and filling the funnel, the most successful companies focus instead on retention.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
This document discusses innovative monetization strategies for organizations. It notes that focusing solely on customer acquisition is insufficient, and that retention must also be emphasized through innovative revenue models, pricing strategies, and business models aligned with the customer journey. Examples are provided of companies innovating their monetization approaches through various strategies like freemium, value-based, subscription-based, and pay-per-use models. The importance of data-driven optimization of pricing and understanding customer willingness to pay is also highlighted.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
An innovative monetization strategy requires much more than meets the eye. While many organizations focus their efforts on acquiring new customers and filling the funnel, the most successful companies focus instead on retention.
Big Data in Retail - Examples in ActionDavid Pittman
This use case looks at how savvy retailers can use "big data" - combining data from web browsing patterns, social media, industry forecasts, existing customer records, etc. - to predict trends, prepare for demand, pinpoint customers, optimize pricing and promotions, and monitor real-time analytics and results. For more information, visit http://www.IBMbigdatahub.com
Follow us on Twitter.com/IBMbigdata
This document provides an introduction to the SAS Output Delivery System (ODS) and describes its key features and capabilities. ODS allows users to format output from SAS procedures and data steps and send it to various destinations like HTML, PDF, and output data sets. The document discusses opening and closing destinations, selecting and excluding specific output objects, and using ODS statements and options to control output formatting and delivery.
Predictive Analytics in Retail - Visual Infographic Reportc24ltd
A visual infographic report about Predictive Analytics in Retail, based on our whitepaper "Predictive Analytics in Retail" (link: https://blog.c24.co.uk/2016/08/17/c24-publishes-new-predictive-analytics-whitepaper/).
We explore the ways in which Predictive Analytics is set to change how retailers make use of big data, analytics and insights across their customers, supply chain and stores.
This document provides an overview of Snapdeal and Infibeam, two major Indian e-commerce companies. For Snapdeal, it summarizes their business model as a marketplace, growth in revenue from 2012-2014, investments in supply chain and logistics to improve delivery times, and use of social media marketing. For Infibeam, it outlines their hybrid business model involving both direct sales and as a marketplace, profitability achieved in 2012-2013, investments in their own logistics arm and logistics aggregation platform, and social media promotions.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
This document discusses analytics and retail analytics. It defines analytics as discovering patterns in data through statistics, programming, and research. Retail analytics specifically aims to improve customer loyalty and sales. It does this by identifying valuable customers, understanding their preferences, and creating personalized shopping experiences through offers targeted to individual needs. Retailers can gather customer data through in-store and online analytics to gain insights that optimize performance.
This document describes a webinar that discussed next generation business and retail analytics technologies. The webinar covered challenges with current business intelligence tools, new analytics vendors and tools, trends in retail analytics, and case studies of companies using new analytics tools to improve performance.
State of Analytics: Retail and Consumer GoodsSPI Conference
There is little doubt that Business Analytics will become a core differentiator in consumer industries, but even though Retail and Consumer Goods companies view analytics as extremely strategic, they struggle to effectively leverage it across the enterprise. EKN has studied the adoption and impact analytics in these industries for the last 5 years, and this counterpoint presentation will summarize key trends in analytics and shares fresh 2016 data on the state of analytics. Presented by Joe Skorupa (Editorial Director, RIS News) & Gaurav Pant (Senior VP Research & Principal Analyst, EKN Research) at the 2016 SPI Conference.
The document discusses various analytics techniques used in retail decision making including store layout planning, merchandising, assortment optimization, sales forecasting, inventory management, vendor management, loyalty analytics, pricing analysis, promotion optimization, and market basket analysis. The key goal of applying these decision science techniques is to maximize revenue, sales, footfalls, and profitability through optimal allocation of space, inventory, pricing, promotions and understanding of consumer purchasing behavior.
Inventory management is key for profitability in retail. Disappointing customers by missing trends or not meeting their demand puts retailers in a serious deficit. This report covers .. why harnessing inventory data is critical for success, what KPIs are essential for effective inventory management, which POS reports all retailers should run and when, and more! Enjoy the report, and visit us at springboardretail.com for even more inventory management content.
This document discusses using predictive analytics for retail businesses. It outlines using store clustering and RFM (recency, frequency, monetary) analysis to develop predictive models. Store clusters would be used to design customized planograms and segmentation strategies. RFM would analyze active and expired customers to develop targeted strategies like offering discounts or new products to high value customers or win back lower value, expired customers. The overall goal is to use predictive models to improve planogram performance, customer retention and reactivation, and sales.
The document provides an overview of marketing analytics. It introduces the presenter and outlines an agenda that covers descriptive, predictive, and prescriptive analytics. Marketing analytics are defined as measuring, managing, and analyzing trends to maximize marketing strategy effectiveness. Examples are given of how companies use analytics. The document then discusses measurement sources, applications, benefits, and tools of marketing analytics.
Case Studies - Customer & Marketing Analytics for Retail Gurmit Combo
The document discusses three case studies involving customer intelligence and marketing effectiveness services:
1. A luxury retailer case study where customer segmentation and profiling identified their most valuable customers to focus relationship management efforts.
2. A technology company case study where product association analysis and scoring identified accounts likely to purchase docking stations for targeted cross-selling.
3. A CPG company case study where regression modeling decomposed the impact of price, promotion, competition and cross-category effects on sales volumes, revealing promotion strategy optimizations.
NRF 2019: Retail's Big Show
Sunil Suram, Director of AI and Big Data, Tango
Pranav Tyagi, President and CEO, Tango
Mark Zygmontowicz, SVP, Business Development, Tango
The document discusses how analytics can be used to solve business problems in the retail banking industry. It describes how analytics can be applied to various areas of a bank's profit and loss statement, including acquiring new customers, reducing customer attrition, improving account activation rates, and maximizing revenue from interest, fees, and cross-selling. It also discusses how strategic reporting, marketing analytics, and data-driven insights can be used for segmentation, customer lifetime value analysis, profitability and loyalty analysis, cross-selling strategies, and customer retention programs. The overall aim is to provide a top-down analytical approach to optimize all areas of a bank's operations and financial performance.
SAP WHITEPAPER: Reacting in the Retail Moment, Analyzing Big Data in Real Tim...Beyond Technologies
Under any circumstances, retail is an extremely competitive industry. But today, an uncertain economy and low consumer confidence, coupled with shorter product lifecycles and well-informed, demanding customers, make it especially difficult to execute a profitable strategy.
Retailers have only a narrow window to make the sale and seize the opportunity. Thriving in this environment means maximizing the profit potential of each interaction, transaction, and customer contact.
business analytics and its importance, marketing analytics definition and its importance, how marketing analytics helps to run the organization in effective and efficient manner.
The document discusses the importance of selecting the right retail store location and introduces the OPTILOX model for optimizing location selection. OPTILOX uses behavioral analytics and considers factors like customer demographics, preferences, and footfall patterns to evaluate potential locations and forecast customer numbers. It helps retailers make faster and more informed decisions to maximize the success of new store openings.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
An innovative monetization strategy requires much more than meets the eye. While many organizations focus their efforts on acquiring new customers and filling the funnel, the most successful companies focus instead on retention.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
This document discusses innovative monetization strategies for organizations. It notes that focusing solely on customer acquisition is insufficient, and that retention must also be emphasized through innovative revenue models, pricing strategies, and business models aligned with the customer journey. Examples are provided of companies innovating their monetization approaches through various strategies like freemium, value-based, subscription-based, and pay-per-use models. The importance of data-driven optimization of pricing and understanding customer willingness to pay is also highlighted.
Uncovering an Innovative Monetization Strategy to Keep Your Organization Rele...RocketSource
An innovative monetization strategy requires much more than meets the eye. While many organizations focus their efforts on acquiring new customers and filling the funnel, the most successful companies focus instead on retention.
Big Data in Retail - Examples in ActionDavid Pittman
This use case looks at how savvy retailers can use "big data" - combining data from web browsing patterns, social media, industry forecasts, existing customer records, etc. - to predict trends, prepare for demand, pinpoint customers, optimize pricing and promotions, and monitor real-time analytics and results. For more information, visit http://www.IBMbigdatahub.com
Follow us on Twitter.com/IBMbigdata
This document provides an introduction to the SAS Output Delivery System (ODS) and describes its key features and capabilities. ODS allows users to format output from SAS procedures and data steps and send it to various destinations like HTML, PDF, and output data sets. The document discusses opening and closing destinations, selecting and excluding specific output objects, and using ODS statements and options to control output formatting and delivery.
Risk management principles include defining and mitigating risks to prevent losses. An effective loss prevention program promotes safe working conditions for employees and has clearly defined, performance-oriented objectives. The document discusses principles of risk management, loss prevention programs, and provides a summary of both topics.
Risk Management: Why, How and What Do You Need To Do?Anwar Ahmadabidin
Risk management is about making an effort to have some control over your objectives and what you want to get done. Managing risks while answering the questions of why, how and what to do to manage risk, will make you focus on the big picture and risks that matter most to you and to the people around you.
Stock Shrinkage at retail store and loss prevention methodsPrasanth Pambadi
Loss prevention refers to processes that reduce inventory losses from theft and errors. The main causes of shrinkage are employee theft (42.9%), shoplifting (37.4%), administrative errors (10.8%) and vendor fraud (8.9%). Shoplifting involves stealing merchandise from a retail store, while kleptomania is a disorder where people feel compelled to steal useless items. Common loss prevention measures include training staff, using surveillance cameras, security checks, and defining entry and exit processes to reduce shoplifting and employee theft.
Priyangani Jayasundara conducted a four-day "Train the Trainer" workshop in Zimbabwe from December 10-14, 2007 to train 13 trainers from Empretec Zimbabwe to deliver the International Trade Centre's modular learning system on international purchasing and supply chain management. The workshop was held at Empretec in Harare, Zimbabwe. Empretec is an independent business organization that provides training to small and medium enterprises. The participants were from various backgrounds and were enthusiastic about applying what they learned to their own organizations. Plans were made to launch the modular learning program in Zimbabwe soon.
The document discusses opportunities for organized retailing in India due to changing demographics, lifestyles, and increased discretionary incomes. Key opportunities include many underserved product categories and retail formats. Emerging trends in Indian retail include the importance of size, flexibility, and global supply chains. Winning retail strategies will revolve around differentiation through price, product, service, quality, and convenience over time. Best practices for Indian retailers include focusing on location, assortment, availability, and using IT to improve operations and supplier relationships.
Organization Retail Industry study presentation is a valid real time survey based presentation.This is very much useful for business students and persons who are working in the retail sector.
The retail sector has never been more competitive, so it’s essential to understand what’s behind every dip or hike in sales within your business.
Experian FootFall’s Site Analytics for Retailers scientifically monitors and accurately analyses in-store customer behaviour to help retail businesses pinpoint areas where profits can be improved.
Our unique retail technology and analysis solutions enable retail businesses to identify and understand customer shopping habits, to drive performance. You can pinpoint profit opportunities in areas such as customer conversions, queue management, sales, marketing and merchandising.
New Site Analytics interface for mobile – empower store managers to make actionable real-time decisions that drive store performance.
India is the country having the most unorganized retail market.
The contribution of retail industry to India’s GDP is more than 13%.
More than 99% retailer’s function in less than 500 square feet of shopping space.
India's retail sector is on its way of modernization. Traditional markets are making way for new formats such as departmental stores, supermarkets and specialty stores.
With the growth in income levels, Indians have started spending more on health and beauty products.
India's retail sector is estimated to touch US$ 833 billion by 2013 and US$ 1.3 trillion by 2018.
Confirmative, re – organized or unorganized/ dental continuing education coursesIndian dental academy
Indian Dental Academy: will be one of the most relevant and exciting
training center with best faculty and flexible training programs
for dental professionals who wish to advance in their dental
practice,Offers certified courses in Dental
implants,Orthodontics,Endodontics,Cosmetic Dentistry, Prosthetic
Dentistry, Periodontics and General Dentistry.
The “best” price for a product or service is one that maximizes profits, not necessarily the price that sells the most units. This presentation uses real-world examples to explore how Excel’s Solver functionality can be used to calculate the optimal price for any product or service.
Big Data Analytics and its Application in E-CommerceUyoyo Edosio
Abstract-This era unlike any, is faced with explosive
growth in the size of data generated/captured. Data
growth has undergone a renaissance, influenced
primarily by ever cheaper computing power and
the ubiquity of the internet. This has led to a
paradigm shift in the E-commerce sector; as data is
no longer seen as the byproduct of their business
activities, but as their biggest asset providing: key
insights to the needs of their customers, predicting
trends in customer’s behavior, democratizing of
advertisement to suits consumers varied taste, as
well as providing a performance metric to assess the
effectiveness in meeting customers’ needs.
This paper presents an overview of the unique
features that differentiate big data from traditional
datasets. In addition, the application of big data
analytics in the E-commerce and the various
technologies that make analytics of consumer data
possible is discussed.
Further this paper will present some case studies of
how leading Ecommerce vendors like Amazon.com,
Walmart Inc, and Adidas apply Big Data analytics in
their business strategies/activities to improve their
competitive advantage. Lastly we identify some
challenges these E-commerce vendors face while
implementing big data analytic
SAS was founded in 1976 and is headquartered in Cary, North Carolina. It provides software for business intelligence, analytics, and data management. SAS has over 11,000 employees worldwide and annual revenue of over $3 billion. It prides itself on high-quality software and excellent customer service.
BigData & Supply Chain: A "Small" IntroductionIvan Gruer
In the frame of the master in logistic LOG2020, a brief presentation about BigData and its impacts on Supply Chains at IUAV.
Topics and contents have been developed along the research for the MBA final dissertation at MIB School of Management.
The document summarizes retail shrinkage and methods to prevent it. It notes that India has the highest retail shrinkage rate in the world at 2.7% primarily due to shoplifting and employee theft. Common shoplifter behaviors are outlined. Methods to reduce shrinkage discussed include using CCTV, checking employees and customers, and installing EAS (Electronic Article Surveillance) systems which use radio frequency tags and antennas to detect unpaid items at exits and prevent theft.
This webcast discusses new thinking for retail security and loss prevention. It provides an overview of current trends challenging loss prevention leaders, such as reduced staffing and budgets. Topics discussed include fighting organizational fires with fewer resources, demonstrating ROI to justify technology investments, and combating organized retail crime. The speakers also cover litigation avoidance strategies and video surveillance trends. Attendees were invited to submit questions during a 10-minute Q&A session at the end.
Transforming the City of New York: New Platform for Public-Private Cooperatio...Cisco Services
The document introduces City24/7, a new platform that aims to transform cities through public-private cooperation and smart technologies. City24/7 is an interactive platform that integrates information from open government, businesses, and citizens to provide knowledge on any device. It intends to inform, protect, and revitalize cities by connecting people and improving safety, commerce, and tourism through access to real-time, local information on smart screens and mobile devices. The document outlines challenges cities currently face and how City24/7 seeks to address them through new economic models and technological connectivity between citizens.
This document provides an executive summary and business plan for Metromart, a proposed retail chain in India. It outlines Metromart's value proposition as providing consumers access to a wide range of products under one roof through a multi-channel distribution network. The initial focus will be on Mumbai, targeting 1 million consumers through stores, web, mail, and phone orders focusing on consumer necessities. Future plans in the next 3-5 years include expanding the store network to other major cities. The document provides details on sales and marketing strategies, market analysis, costs, partnerships, and financial projections.
V. Prasad has owned a retail store in Vizianagaram, India since 2008. Over the years, the business has grown steadily at a rate of 12% annually as customer traffic has increased. The store focuses on customer satisfaction over formal goals and aims to offer both shopping and convenience goods at competitive prices through cost-oriented and demand-based pricing. While the location and large size of 7,000 square feet are strengths, greater brand awareness could help the store attract more customers and become the top retailer in the area. Maintaining strong customer relationships and service will be key to retaining their competitive advantage against other stores like Spencer's that have entered the market.
This document discusses a study on the low pricing strategy of Big Bazaar, a large retail chain in India. It provides background on India's rapidly growing retail sector and the importance of modern pricing strategies. Big Bazaar has been very successful with its strategy of offering world-class products at affordable prices. The study aims to analyze how Big Bazaar's low pricing approach has contributed to its success and led it to become one of the largest hypermarket chains in India.
The document compares the marketing strategies of Big Bazaar and Vishal Megamart, two large retail chains in India. It finds that Big Bazaar's innovations like special offers and stabilizing store operations before expanding helped it succeed, while Vishal expanded too quickly without proper capitalization and supply chain management, leading to its downfall. The SWOT analyses show Big Bazaar's strengths were its brand, infrastructure, and product variety, while Vishal's were its value retail segment understanding and distribution network, but it faced threats from category killers and store performance issues.
Some important notes about retail industry such as:
Strategic Levers of Retailing,
Functions Performed by Retailers,
Types of Retailers,
Customers Perception and Buying Behavior,
Merchandise Management,
Issues with Merchandise Management.
Reliance Retail is changing its market strategy in response to the evolving Indian retail sector. While it had traditionally focused on smaller stores, it is now expanding into larger "big-box" stores carrying a wide range of products. It is also hiring executives from global retailers like Walmart to help drive these strategic changes. Reliance Retail plans to raise funds to open more stores across a variety of formats, focusing on expanding into consumer durables and apparel. It now operates over 1,300 stores across 18 states in India.
This document discusses the retail market in India. It notes that the retail market is growing at 13% annually and organized retail penetration is projected to reach 14% by 2015. It also discusses challenges like high real estate prices and regulatory hurdles. Global retailers are entering through partnerships with domestic players. Rural retail is a large opportunity, though kirana stores remain popular for their convenience and credit. The document analyzes Reliance Fresh's business using the 7P framework and provides recommendations on areas for improvement like customer service. It also discusses learning from global leaders like Aldi.
Big bazaar customer relationship managementAman Bansal
This document is a project report submitted by Rishi Sharma for the degree of Bachelor of Business Administration from Noida International University. The project focuses on analyzing customer relationship management practices at Big Bazaar, a large retail chain in India. It includes an introduction to CRM and its importance. It also discusses the advantages of CRM for Big Bazaar, such as providing better customer service and increasing revenues. Some challenges in implementing CRM at Big Bazaar are inaccurate product information, lack of product knowledge among sales staff, and difficulties in updating pricing and product details. The report aims to assess how CRM influences customer satisfaction levels and the store's overall success.
Growing Your Business In A Hyper Competitive MarketAndrew Samrick
The keynote address at the 2011 TEANA conference, this presentation details the forward expectations of manufacturers and distributors, as well as the operating and commercial activities those in the transportation industry will need to master to remain competitive in a highly fragmented market space.
1) China has a larger retail market than India, but India's retail industry is still underdeveloped, leaving significant room for growth.
2) India's retail industry is growing rapidly due to factors like rising incomes, urbanization, and the growth of e-commerce. However, e-tailers have focused only on acquisition metrics like market share rather than retention.
3) To succeed, retailers must understand customers' full shopping journey and satisfy customers' needs across different shopping mindsets, both online and offline. The future is in effectively blending online and offline retail models.
FASHIONING A WINNING TRAIL - How to build sustainable business models in Indi...Kanvic Consulting
The elusive nature of success in India’s apparel retail industry has left many of its incumbents struggling, while still many more have fallen by the wayside during the economic turbulence of recent years. This report looks at the root causes of failure in the sector and highlights the persistent weakness of the surviving players. It then moves on to address the six key areas where Indian apparel retailers need to take action if they are to build the sustainable business models that will win in the future.
The Indian retail sector has traditionally consisted of small neighborhood stores but is now undergoing rapid transformation and growth. Modern retail formats like supermarkets and malls are expanding rapidly due to factors like liberalization of the economy, rising incomes, and changing consumer preferences. Organized retail makes up only 3% of an estimated $200 billion retail market in India, indicating huge growth potential. Major domestic and global retailers are looking to expand in India through various strategies like foreign direct investment or franchising.
The document discusses blue ocean strategy and provides several key concepts:
1. It compares red ocean strategy, which focuses on competition, to blue ocean strategy which creates new market space and makes competition irrelevant.
2. Value innovation, pursuing differentiation and low cost simultaneously to create value for buyers and the company, is the cornerstone of blue ocean strategy.
3. The strategy canvas tool is used to analyze current industry factors and identify which to eliminate, reduce, raise, and create to shift to an uncontested blue ocean.
4. Pioneer-migrator-settler maps are used to plot current and planned business offerings to identify blue ocean strategic moves as pioneers in new markets.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
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2. India is the fifth largest retail market globally, with a size of INR 16
trillion, and has been growing at 15% per annum.
Organized retail accounts for just 5% of total retail sales and has been
growing at 35% CAGR.
India’s robust macro- and microeconomic fundamentals, such as
robust GDP growth, higher incomes, increasing personal consumption,
favourable demographics and supportive government policies, surely
increased the growth in the retail sector but it all couldn’t helped in
stopping the operational costs thus reducing in the overall margins.
2
3. We have structured the report broadly into three
categories:
(1)Learning from the past
(2) Consolidation
(3) Critical issues
(4) View on future
3
4. During 2005-2007, the sector was in a hyper growth phase. In pursuit to capture market,
companies made strategic as well as operational errors which has been broadly
classified as follows:
Race for increasing retail space resulting in haphazard growth.
Unviable formats.
High lease rentals.
Manpower costs and productivity issues.
Poor backend infrastructure.
Entry of too many new players.
4
5. 1) Race for increasing retail space resulting in haphazard growth: Organized
retailers entered the race of adding retail space without proper due diligence
on the catchment area, mall density and acceptability of organized retail.
2) Unviable formats: Large players entered numerous formats, some of which
proved to be unviable.
3) High lease rentals: Retail is a tough business to operate, PAT margins are
as low as 2-3%. Indian organized retail follows the lease rental model due to
high real estate costs and paucity of quality malls. Lease rentals should ideally
be 3-6% of sales depending upon the format.
However, rentals in a few specialty stores touched Rs 300/sq feet/month
during the heydays - in a period of two years, lease rentals in general
increased 50-70%. The increase was more evident in FY08 and FY09 due to
decline in same store sales growth. Currently, the price/sq feet can reach in
thousands.
5
6. 4) Manpower costs and productivity issues: As trained manpower was scarce,
salaries of experienced retailing professionals went through the roof.
5) Poor Backend infrastructure: Retailers focused all their energies on store
openings and neglected the backend.
6) Entry of too many new players: Viewing it as a sunrise sector, too many
players entered organized retail and some have perished.
6
7. In the global slowdown phase starting from 2007, the Indian retail players paused,
to realize their past mistakes and took time and efforts to re-organize themselves:
Focus on profitable growth
Exit from unprofitable stores/formats
Rental renegotiation/revenue sharing arrangements
Reduction in salaries/ higher manpower productivity
Significant investments in backend
Exit of unsuccessful new entrants
7
8. 1) Focus on profitable growth: Retailers paused and realized their errors and started
using analytics for insights into the business, but analytics used was only
concentrated towards the finding of most feasible location to open a new store.
2)Exit from unprofitable stores/formats: whole new set of formats and store sizes, with a
view to capture consumption and increase share in consumer wallet. The industry has
tried to control costs and address the issue by way of store closure, exit from formats,
restructuring of format, Change of location.
3)Rental renegotiation/revenue sharing arrangements: After touching the unprecedented
highs, lease rentals softened, revenue sharing arrangements came into picture.
4) Reduction in salaries/ higher manpower productivity: stopped paying fancy salaries to
attract the top talent.
5) Significant investments in backend: Post the slowdown, retailers have been making
huge investments to strengthen their backend systems.
6) Exit of unsuccessful new entrants
8
9. Soaring real estate prices.
Intense competition : customers, now have the option to select any of the
stores they want.
Reduction in customer loyalty: customers, are now smart enough in saving
their time and money, only increase in per capita income or GDP doesn’t
always help.
No cheap labor.
Exponential increase in operating costs like electricity bills, salary for the
staff, vendor management costs, relationship building costs and other
miscellaneous but mandatory costs.
9
10. Standard Cost reduction scenario:
Air India used silver spoon from 1948 to 1962, gradually they came down to stainless steel and finally a
plastic spoon.
Transformational Change:
Apple changed the way people used to think about music, with proper planning they are the leaders in the
market now.
Retail industry should now have to act smart and move towards the transformational changes.
10
11. Since, the fixed operating costs can’t be reduced for any retail, hence this research
revolves around the following questions:
How to achieve the maximum positive footfalls?
What is the buying behavioral pattern of a customer?
What is the customers’ psychology while going to any retail store?
What if, the cost can be reduced through following a eco-green building
model?
This research will aim at attracting new customers as well as retaining old ones, and
suggest possible future models to increase profit and provide better value to a
customer
So we started this project to help reduce operating cost of existing retail business
and suggest possible future model to increase profit and provide better value to
customer
11
12. Questionnaire: Prepared to meet our objective.
Pilot testing: Data collection to validate and verify the research objective.
Survey: Data collected using offline and online methods.
Data Validation: Cleaning and extracting useful data.
Data Exploration: To analyze which store has maximum footfalls based on
gender, age group and marital status.
Clustering and Segmentation: To understand the shopping behavior of
customers, like the preferable time and which day of the week they shop.
Regression Analysis: For the SWOT analysis of the retail stores, based on
the parameters in the questionnaire.
Correlation Analysis: Finding the relationship between the variables.
Summarizing the results.
12
13. Tools used:
Microsoft Office Excel 2007
Bas SAS 9.1
SAS Enterprise Miner 6.1
SAS Enterprise Guide 4.2
13
18. Clustering: Dmart appeared as the top priority of the customers.
Dmart reduced its operating cost and connected more closely to
customers and become most preferred retailer which Big Bazaar used
to be.
As the focus is shifting towards Dmart and other retailer will have to
reduce their operating cost and think for implementing future preferred
model to do better business and give more value to customers.
Dmart Reliance Fresh Dorabjee Big Bazaar Others
47%
15%
9%
15%
14%
18
19. STRENGTHS:
o Believes in providing more value to customers with attractive discounts.
o Efficient cost effective model.
o Usually located in the residential area.
o Moderate store size, though it provides wide variety of cost effective goods.
o Highly motivated staff
WEAKNESS:
o Lesser parking space.
o No rest rooms
o Compact store size, makes the in-store suffocating during peak times.
o No Customer loyalty programs.
OPPORTUNITIES:
o Heavy customer base, can still make it strong through various other models.
o Strongly headed for price sensitive population.
THREATS:
o Must concentrate more towards the hygiene and other convenient clean
o factors for its customers. It can help in attracting new buyers.
o Need to come up with an strategy to tackle peak hours.
19
20. STRENGTHS:
Strong supplier tie-ups.
Huge advertising budgets, having potential to have new customers.
WEAKNESS:
Lesser savings comparatively to D-Mart.
Lesser variety of goods.
Discounts and offers are released for about to expire goods.
OPPORTUNITIES:
Should use the supplies efficiently.
Must concentrate on the quality of goods offered.
Should use the customer card in analyzing their buying trends.
THREATS:
Price sensitive population are continuously ignoring the store.
Major threat is for its survival.
20
21. STRENGTHS
Owns the tag :: “entered first into this business”.
Big customer base.
Huge advertising budgets.
WEAKNESS:
Lesser savings comparatively with other competitors.
Poor arrangement of goods makes it difficult to search.
Few product racks are out of reach for some customers.
OPPORTUNITIES
Must know how to tackle large crowd specially “Sabse Bada Din” and other special days.
Must concentrate on the quality of goods offered.
THREATS
Price sensitive population are continuously ignoring the store.
Major threat is for its survival.
21
22. The graph shows the customers’ expectation from a retail store.
22
23. Majority customers coming on Saturday and Sunday.
Based on the feedback during the research, there were many people visiting the
stores weekdays unwillingly so as to avoid the weekend rush.
23
25. Based on day and time preference by most of customers we have suggested below solutions to retain
customers more happily coming on weekend and can reduce their operating cost.
HAPPY HOURS: Since the majority customers visit during weekends, after 3:00 PM, so the concept of happy
hours might help, which retailers can introduce from morning to 12:00 Noon and can start store little early in
morning on weekend or holidays.
EXPRESS COUNTERS: Increase the minimum items in express counters. In this way more customer will be
handled in express counter.
REDUCE MANPOWER AND ENERGY ON LEAST SHOPPED DAY: Retailer can return to old working style.
Keep store close on least shopping day and give more value to existing customers and can build long
relationship. So saving in operating cost and retaining customers.
CUSTOMER LOYALTY PROGRAM: Introducing customer loyalty programs to study the buying behavior of the
customers. Retail companies should work more towards customer satisfaction, e.g. wishing them on their
special days, offer special discounts to them on those days.
TOKEN SYSTEM: Retailers can introduce token system, to the customers standing in queue. Customers can
hang the token in their trolley and collect their goods later when they are called. In this way customer would
be happily retained.
25
26. Retailers must select the proper channel to reach the customers. DMART believes
in people visiting their stores, thus it is reducing its operating costs.
26
27. Below future models will help retailers utilize their existing space and
resources to attract more customers and better satisfy existing customers.
Based on our research, we conclude that people are interested for:
Mobile Application Home Delivery: 88.04%
Mobile Application Order and Pick-up: 92.39%
Shop and Drop: 97.82%
Online Home Delivery: 55.6%
Home Delivery Extra pay: 78.3%
Hence, we can assume that people are more interested towards the
online model, moreover they are also willing to pay some extra for the
same. Above model can help increasing customers and also retaining
customers happily for longer time.
27
28. Order-Pick-up and Online model is the top preference for married couples. Married have prime
responsibility for grocery so retailer should think to act for such segment.
Lesser working days preferred by many married males if better offers are made available. While
unmarried has no such priority whether a store is functioning for all 7 days or 6 days.
Females influence more instead of males for shopping the grocery items, So retailers should think
whom to focus more.
Online model found to be more preferred among the population. Still, females were in favour of
rejecting the online model for the grocery item as they can’t look and feel the items online, but at the
same time they wish branded products can be home delivered.
Based on our research, people are also even ready to pay extra for the home delivery.
28
29. ORDER AND PICK UP: A process in which people can call and block their
order, the goods can be collected while returning on their way home. This
process can be implemented through online, mobile application or a small
call centre.
SHOP AND DROP: A process in which people visits the store, shops and in
turn has the option of delivering the goods at their doorstep.
ONLINE MODEL: This model can include both website and the mobile
application. Based on the analysis major population is even interested in
paying extra for home delivery.
29
30. Green building can help reducing operating cost primarily in air conditioning and light.
Retailer can also opt for carbon credit too. Below building consume very little electricity in
lighting but it is without air conditioning but feel like centrally air conditioned.id retailers
can opt for carbon credit too.
30
31. We have covered only operating cost and future option but many analytic
area is there in retailing which should also be taken care for better
business:
ASSORTMENT OPTIMIZATION AND SHELF SPACE ALLOCATION - Using analytics
to determine what products to offer in what quantities.
CUSTOMER DRIVEN MARKETING - Use of customer data to segment, target,
and personalize offerings.
INTEGRATED FORECASTING - The use of statistical forecasting to support
multiple functions.
LOCALIZATION AND CLUSTERING - Tailoring multiple aspects of retailing to
local stores or similar clusters
31
32. MARKETING MIX MODELLING - Determining which marketing investments
work, and which are less effective.
PRICING OPTIMIZATION - Using analytics to determine the optimal pricing
of products and services through their lifecycles.
PRODUCT RECOMMENDATION - Using analytical approaches to recommend
product offerings for particular customers.
WORKFORCE ANALYTICS - Optimization of staffing with regard to cost,
customer shopping patterns, and locations
32
33. STORE LEVEL EMPOWERMENT - Giving store managers and employees
the ability to analyze their businesses.
ANALYTICAL PERFORMANCE MANAGEMENT - Predicting financial
performance from nonfinancial and intangible performance factors
MULTI CHANNEL ANALYTICS AND DATA INTEGRATION -
Integration of data and analytics across multiple customer channels or
touch points.
33
35. Given the current retail environment, it may take a bit longer for retailers to
transform themselves into precision analytical machines.
However, the overall trends are clear: retail is a data-intensive industry, and
taking advantage of all that data to operate and manage the business better
requires analytics.
The good news—and the bad—for retail analytics is that most retailers have
only scratched the surface of what is possible.
The food on the analytical table for retailers is both bounteous and delicious; all
that remains is for retail executives to revive their appetites, and eat heartily!
35
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36
Editor's Notes
Club graphs from 14 to 18
Reduce manpower : Retailers have change habit by keeping store opened for all 7 days and providing luxury to attract customers. But now this habit is becoming burden on retailers. So retailer will have to build old habit by providing comparatively less luxury and more value for log relationship with customer.
Mobile application is on top instead of internet orders. Both are online but seems growth of high end mobile, low cost mobile internet and its portability have put mobile application on top. So retailers should take action based on current most preferred technology to grow in online orders.