E-Commerce Forecast 2017: A Digital Disruption is Coming to a Store near You
- Date:November 02, 2017
- Author(s):
- Michael Moeser
- Report Details: 31 pages, 18 graphics
- Research Topic(s):
- Tech & Infrastructure
- PAID CONTENT
Overview
The expansion of e-commerce retailing continues to grow unabated, accelerating with each new digital retailer born, every new expansion of physical delivery services, and the intensifying desire of consumers to shop when, where, and how they want. E-commerce (mobile and PC/laptop) sales exceeded a half-trillion dollars in 2016 ($518 billion) and are forecast to grow to more than $700 billion by 2021. This report examines the growth of e-commerce, both mobile and online (PC/laptop), and how it is continuing to reshape the U.S. retail landscape. It also explores the impact that certain retailers, such as Amazon, and particular trends (e.g., development of IoT and digital expansion into grocery) are having on the growth of e-commerce. Finally, it explores how payment options for e-commerce are evolving as the market grows.
Key questions discussed in this report:
- How is the overall growth of e-commerce trending?
- How much share does e-commerce have of total retail sales?
- What is social media’s role in e-commerce?
- How will the various payment types for e-commerce change between 2016 and 2021?
- What role does Amazon have in the growth of e-commerce?
- What defines the power users of e-commerce?
- What effect will the Internet of Things (IoT) have on the growth of e-commerce?
- What is the opportunity for e-commerce to disrupt the grocery business?
Methodology
The consumer data in this report was primarily collected from the following:
- A random-sample survey of 3,200 respondents conducted online in October 2016. The overall margin of error is +1.74 at the 95% confidence level. The margin of error is larger for subsets.
- A random-sample survey of 3,200 respondents conducted online in October2015. The overall margin of error is +1.74 at the 95% confidence level. The margin of error is larger for subsets.
Industry card and reward programs data were derived from industry interviews, with supplementary data from secondary sources such as The Nilson Report and public websites.
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