Welcome!

News Feed Item

Consumer Attitudes and Online Retail Dynamics in India, 2013

LONDON, Jan. 9, 2014 /PRNewswire/ -- Reportbuyer.com just published a new market research report:

Consumer Attitudes and Online Retail Dynamics in India, 2013

Product Synopsis

Provides in-depth analysis of the latest trends in online consumer shopping, covering factors driving online shopping, consumer insights, market dynamics (covering 25 product categories), and reviews of latest best practice in online retail site design.
Based on the latest data, the report not only provides details of the size and growth of this increasingly important channel, it also provides essential context on the penetration of online sales by product groups, how growth has developed over time, and key factors that will drive this market in the future.

Introduction and Landscape

Why was the report written?
"Consumer Attitudes and Online Retail Development in India, 2013" is the result of Canadean's extensive market research covering the online retail industry in India. It provides the magnitude, growth, share, and dynamics of the online retail market in India. It is an essential tool for companies active across India's online retail value chain and for new companies considering entry into India online retail market. It provides data for historic and forecast online retail sales, and also includes the business environment and country risk related to India online retail environment. By examining best practice from leading national large-scale online retailers (but specifically excluding the likes of Amazon, whose sites are well-known and vary little by country), as well as reviewing innovative approaches from smaller companies, the report provides insights and ideas about how best to approach growing online sales for your business.

What is the current market landscape and what is changing?
Online retailers was the fastest-growing retail channel with a CAGR of 39.15% during 2007–2012, followed by general retailers with a CAGR of 13.13%, specialist retailers with a CAGR of 11.87%, and value retailers with a CAGR of 11.09%.

What are the key drivers behind recent market changes?
Online retailing is booming in India with the rise in internet penetration, smartphone penetration, digital literacy, purchasing power, urbanization, and awareness among Indian consumers.

Key Features and Benefits

Understand the consumer behaviour and online trends in India.

Understand which products will be the major winners and losers in the coming years.

Learn from best practices approaches outlined in the case studies of leading online retailers.

Improve market and strategic planning using highly granular, forward-looking market data. Detailed category coverage is provided, covering 25 products, across eight product groups that include: Apparel, Accessories, Luggage and Leather Goods, Book, News and Stationery, Electricals and Electronics, Food and Grocery, Furniture and Floor Coverings, Home and Garden Products, Music, Video and Entertainment Software, and Sports and Leisure Equipment.

Assess the impact of economic recession and recovery on market growth.

Key Highlights

Online retailers have been trying to attract Indian consumers by providing exclusive discounts during the festive season.

Online Grocery retailing is one of the emerging growth categories in online retail in India.

Online retailing was previously limited to metro cities; however, now it has also gained widespread popularity in the Tier II and Tier III cities.

1 Introduction
1.1 What is this Report About?
2 Market at a glance
3 Consumer Insight: Online Shopping Attitudes and Behaviors
3.1 Overview of India Online Shopping Environment
3.1.1 Despite low internet penetration, Indian online population is third largest in the world
3.1.2 Government plans to increase broadband penetration across India
3.2 Consumer Attitudes and Behavior
3.2.1 Online retailers adopting Marketplace model to survive
3.2.2 Cash on delivery most popular mode of payment but eating up retailers' margin
3.2.3 Online Retailing is going beyond metropolitan cities
3.2.4 M-commerce is minimal but expected to grow with the rise in smartphone internet users
3.2.5 Food and groceries is expected to be the emerging growth category group in online retailing
3.2.6 Celebrity fashion driving the sales of online fashion retailers
4 Online Channel Dynamics
4.1 The Online Channel's Share of Total Retail Sales
4.1.1 India online vs. offline channel forecasts
4.1.2 Online penetration: global and regional comparisons
4.2 Channel Dynamics
4.2.1 India retail channel dynamics - future performance
4.2.2 Channel group share development
4.2.3 Individual channel performance
4.3 Category Dynamics
4.3.1 Online vs. offline retail sales comparison by category group, 2012
4.3.2 Online retail market dynamics by category
4.3.3 Online retail sales share by category group
4.3.4 Online retail sales growth by individual category
4.3.5 Food and grocery categories: market size and forecasts
4.3.6 Electrical and electronics categories: market size and forecasts
4.3.7 Music, video, and entertainment software categories: market size and forecasts
4.3.8 Apparel, accessories, luggage and leather goods categories: size and forecasts
4.3.9 Books, news and stationery categories: market size and forecasts
4.3.10 Sports and leisure equipment categories: market size and forecasts
4.3.11 Furniture and floor coverings categories: market size and forecasts
4.3.12 Home and garden categories: market size and forecasts
5 Case Studies: Leading Online Retailers in India
5.1 Retailer 1: Flipkart
5.1.1 Business Description
5.1.2 Site Experience
5.2 Retailer 2: Myntra
5.2.1 Business Description
5.2.2 Site Experience
5.3 Other Innovative Retailers in India
5.3.1 Yebhi - Provides try and buy service in India
5.3.2 Lenskart - Provides home try on services
6 Appendix
6.1 Definitions
6.1.1 This report provides 2012 actual sales; while forecasts are provided for 2013 - 2017
6.2 Summary Methodology
6.2.1 Overview
6.2.2 The triangulated market sizing method
6.2.3 Industry surveys in the creation of retail market data
6.2.4 Quality control and standardized processes
6.3 About Canadean
6.4 Disclaimer

List of Tables

Table 1: Online Retail Sales in India
Table 2: India Online vs. Offline Retail Sales and Forecast (INR bn), 2007-2017
Table 3: India Online vs. Offline Retail Sales and Forecast (USD bn),2007-2017
Table 4: India Online vs. Offline Retail Sales and Forecast (% Share), 2007-2017
Table 5: India Online Sales vs. Global Average
Table 6: India Online Sales vs. Asia-Pacific
Table 7: India Overall Retail Segmentation (INR bn) by Channel Group, 2007-2017
Table 8: India Channel Retail Sales and Forecast (INR bn) by Channel Group, 2007-2017
Table 9: India Channel Retail Sales and Forecast (USD bn) by Channel Group, 2007-2017
Table 10: India Channel Retail Sales and Forecast (% Share) by Channel Group, 2007-2017
Table 11: India Channel Retail Sales and Forecast (INR bn) by Channel, 2007-2017
Table 12: India Channel Retail Sales and Forecast (USD bn) by Channel, 2007-2017
Table 13: India Retail Sales Split (INR bn), Online vs. Offline, 2012
Table 14: India Retail Sales Split (USD mn), Online vs. Offline, 2012
Table 15: India Online Retailers Market Dynamics by Category Group, 2007-2017
Table 16: India Online Retail Sales and Forecast (INR bn) by Category Group, 2007-2017
Table 17: India Online Retail Sales and Forecast (USD mn) by Category Group, 2007-2017
Table 18: India Total and Online Retail Sales in Food and Grocery Categories (INR bn), 2007-2017
Table 19: India Total and Online Retail Sales in Food and Grocery Categories (USD mn), 2007-2017
Table 20: India Total and Online Retail Sales in Electrical and Electronics Categories (INR bn), 2007-2017
Table 21: India Total and Online Retail Sales in Electrical and Electronics Categories (USD mn), 2007-2017
Table 22: India Total and Online Retail Sales in Music, Video and Entertainment Categories (INR bn), 2007-2017
Table 23: India Total and Online Retail Sales in Music, Video and Entertainment Categories (USD mn), 2007-2017
Table 24: India Total and Online Retail Sales in Apparel, Accessories, Luggage and Leather Categories (INR bn), 2007-2017
Table 25: India Total and Online Retail Sales in Apparel, Accessories, Luggage and Leather Categories (USD mn), 2007-2017
Table 26: India Total and Online Retail Sales in Books, News and Stationery Categories (INR bn), 2007-2017
Table 27: India Total and Online Retail Sales in Books, News and Stationery Categories (USD mn), 2007-2017
Table 28: India Total and Online Retail Sales in Sports and Leisure Equipment Categories (INR bn), 2007-2017
Table 29: India Total and Online Retail Sales in Sports and Leisure Equipment Categories (USD mn), 2007-2017
Table 30: India Total and Online Retail Sales in Furniture and Floor Coverings Categories (INR bn), 2007-2017
Table 31: India Total and Online Retail Sales in Furniture and Floor Coverings Categories (USD mn), 2007-2017
Table 32: India Total and Online Retail Sales in Home and Garden Products Categories (INR bn), 2007-2017
Table 33: India Total and Online Retail Sales in Home and Garden Products Categories (USD mn), 2007-2017
Table 34: India Exchange Rate INR-USD (Annual Average), 2007-2012
Table 35: India Exchange Rate INR-USD (Annual Average), 2013-2017 Forecasts
Table 36: Canadean Retail Channel Definitions
Table 37: Canadean Retail Category Definitions
Table 38: Canadean Retail Country Coverage

List of Figures

Figure 1: Online Retail Sales in India
Figure 2: Number of Internet Users and its Penetration, June 2012
Figure 3: Broadband subscribers in India, 2012
Figure 4: Comparison of Marketplace Model Over Inventory Led in India
Figure 5: Cash On Delivery Eating Up Retailers Margin
Figure 6: Growth of smartphones and m-commerce in India
Figure 7: Collections Matching to Celebrities Fashion
Figure 8: India Online and Offline Retail Sales and Forecast (USD bn), 2007-2017
Figure 9: India Online Sales vs. Global Average (% of Total Retail)
Figure 10: India Online Sales vs. Asia-Pacific Countries Average (% of Total Retail)
Figure 11: India Overall Retail Market Dynamics by Channel Group, 2007-2017
Figure 12: India Retail Sales and Forecast (INR bn) by Channel Group, 2007-2017
Figure 13: India Retail Sales, Online vs. Offline, 2012
Figure 14: India Online Retailers Market Dynamics by Category Group, 2007-2017
Figure 15: India Online Retail Sales and Forecast (USD mn) by Category Group, 2007-2017
Figure 16: Flipkart: Home Page
Figure 17: Flipkart: Product View
Figure 18: Flipkart: Product Comparison
Figure 19: Flipkart: M-Commerce
Figure 20: Myntra: Home Page
Figure 21: Myntra: Product View
Figure 22: Myntra: Product Availability
Figure 23: Yebhi: Home Page
Figure 24: Lenskart: Homepage
Figure 25: The Triangulated Market Sizing Methodology

Companies Mentioned

Flipkart, Myntra, Yebhi, Lenskart

Read the full report:
Consumer Attitudes and Online Retail Dynamics in India, 2013
http://www.reportbuyer.com/consumer_goods_retail/e_commerce/consumer_attitudes_online_retail_dynamics_india_2013.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=e-Commerce

For more information:
Sarah Smith
Research Advisor at Reportbuyer.com
Email: [email protected]  
Tel: +44 208 816 85 48
Website: www.reportbuyer.com

SOURCE ReportBuyer

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

Latest Stories
You think you know what’s in your data. But do you? Most organizations are now aware of the business intelligence represented by their data. Data science stands to take this to a level you never thought of – literally. The techniques of data science, when used with the capabilities of Big Data technologies, can make connections you had not yet imagined, helping you discover new insights and ask new questions of your data. In his session at @ThingsExpo, Sarbjit Sarkaria, data science team lead ...
The IoT has the potential to create a renaissance of manufacturing in the US and elsewhere. In his session at 18th Cloud Expo, Florent Solt, CTO and chief architect of Netvibes, will discuss how the expected exponential increase in the amount of data that will be processed, transported, stored, and accessed means there will be a huge demand for smart technologies to deliver it. Florent Solt is the CTO and chief architect of Netvibes. Prior to joining Netvibes in 2007, he co-founded Rift Technol...
If there is anything we have learned by now, is that every business paves their own unique path for releasing software- every pipeline, implementation and practices are a bit different, and DevOps comes in all shapes and sizes. Software delivery practices are often comprised of set of several complementing (or even competing) methodologies – such as leveraging Agile, DevOps and even a mix of ITIL, to create the combination that’s most suitable for your organization and that maximize your busines...
Struggling to keep up with increasing application demand? Learn how Platform as a Service (PaaS) can streamline application development processes and make resource management easy.
New Relic, Inc. has announced a set of new features across the New Relic Software Analytics Cloud that offer IT operations teams increased visibility, and the ability to diagnose and resolve performance problems quickly. The new features further IT operations teams’ ability to leverage data and analytics, as well as drive collaboration and a common, shared understanding between teams. Software teams are under pressure to resolve performance issues quickly and improve availability, as the comple...
The proper isolation of resources is essential for multi-tenant environments. The traditional approach to isolate resources is, however, rather heavyweight. In his session at 18th Cloud Expo, Igor Drobiazko, co-founder of elastic.io, will draw upon their own experience with operating a Docker container-based infrastructure on a large scale and present a lightweight solution for resource isolation using microservices. He will also discuss the implementation of microservices in data and applicat...
See storage differently! Storage performance problems have only gotten worse and harder to solve as applications have become largely virtualized and moved to a cloud-based infrastructure. Storage performance in a virtualized environment is not just about IOPS, it is about how well that potential performance is guaranteed to individual VMs for these apps as the number of VMs keep going up real time. In his session at 18th Cloud Expo, Dhiraj Sehgal, in product and marketing at Tintri, will discu...
Join IBM June 8 at 18th Cloud Expo at the Javits Center in New York City, NY, and learn how to innovate like a startup and scale for the enterprise. You need to deliver quality applications faster and cheaper, attract and retain customers with an engaging experience across devices, and seamlessly integrate your enterprise systems. And you can't take 12 months to do it.
Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, will discuss how research has demonstrated the value of Machine Learning in delivering next generation analytics to im...
This is not a small hotel event. It is also not a big vendor party where politicians and entertainers are more important than real content. This is Cloud Expo, the world's longest-running conference and exhibition focused on Cloud Computing and all that it entails. If you want serious presentations and valuable insight about Cloud Computing for three straight days, then register now for Cloud Expo.
As you respond to increasing requests for new analytics, you need fast and flexible technology in your arsenal so that you can deploy the right workload to the right platform for the need at hand. Do you need self-service and fast time to value? Do you have data and application control and privacy needs, along with strict SLAs to meet? IBM dashDB™ is data warehouse technology powered by in-memory computing and in-database analytics that are designed for fast results, scalability and more.
SYS-CON Events announced today that SoftLayer, an IBM Company, has been named “Gold Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. SoftLayer, an IBM Company, provides cloud infrastructure as a service from a growing number of data centers and network points of presence around the world. SoftLayer’s customers range from Web startups to global enterprises.
So, you bought into the current machine learning craze and went on to collect millions/billions of records from this promising new data source. Now, what do you do with them? Too often, the abundance of data quickly turns into an abundance of problems. How do you extract that "magic essence" from your data without falling into the common pitfalls? In her session at @ThingsExpo, Natalia Ponomareva, Software Engineer at Google, will provide tips on how to be successful in large scale machine lear...
Up until last year, enterprises that were looking into cloud services usually undertook a long-term pilot with one of the large cloud providers, running test and dev workloads in the cloud. With cloud’s transition to mainstream adoption in 2015, and with enterprises migrating more and more workloads into the cloud and in between public and private environments, the single-provider approach must be revisited. In his session at 18th Cloud Expo, Yoav Mor, multi-cloud solution evangelist at Cloudy...
IoT device adoption is growing at staggering rates, and with it comes opportunity for developers to meet consumer demand for an ever more connected world. Wireless communication is the key part of the encompassing components of any IoT device. Wireless connectivity enhances the device utility at the expense of ease of use and deployment challenges. Since connectivity is fundamental for IoT device development, engineers must understand how to overcome the hurdles inherent in incorporating multipl...