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For years, retailers have experienced double-digit growth in online sales. In many cases, just being online with a working web store guaranteed decent sales numbers. However, as the market has begun to mature, the growth rates are beginning to plateau and will slow down over the next 3-4 years. JupiterResearch predicts that US retail e-commerce sales growth will slide from 16% in 2007 to just 8% in 2011.
To remain competitive in this market, retailers need to increase client conversion and decrease drop-off. In addition, they must take customers away from competitors, motivate them to spend more and retain their loyalty. With the total number of online shoppers expected to peak at about 156 million in the next five years, it will be essential for retailers to have a strategy in place to drive repeat business.
One way retailers are looking to gain this necessary competitive advantage is by changing their clients’ shopping experiences. The limitations that retailers have faced in differentiating themselves online, both in terms of technology and client acceptance, are slowly dropping. In addition, many retailers today have collected the data and have the business intelligence to understand their clients’ behaviors. They have ideas about how to differentiate their brands and reflect the nuances of the retail experience electronically, as they have with their traditional stores. The challenge for retailers lies in balancing eCommerce spending, typically 5-8% of their total sales volume and deployment times with return on their investments. This balance is a critical one, as it can make or break a company. This paper will look at the benefits of adding richness to eCommerce process, including the impact that this change can have on a retailer’s bottom line. In addition, it will present options for moving forward that leverage current technology investments to provide retailers with the biggest bang for the smallest investment.
Rich internet applications combine many of the features and functionality of desktop applications, but are delivered over the web. These applications combine the best of both worlds – the power and rich content of the desktop with the connectivity of the internet.
The key differentiator between an RIA and a website is that an RIA is focused on a task. When you apply this in the context of eCommerce, that task is typically focused around finding, customizing, and ultimately purchasing a product. Another difference with RIAs is the way they handle and process information. Traditional desktop applications today rely exclusively on client-side processing. When a task is initiated, the local system’s resources are leveraged to process the request. In contrast, a web application relies exclusively on the server-side technology to process a request. With RIAs the load is shared by both client-side and server-side technology.
With an HTML website, when a user fills in data, changes options, or checks boxes, the page must be submitted to the server for data validation and then the screen is reloaded with the new data incorporated. This model is the basis for many eCommerce sites today. Users navigate through a series of pages to find the products they want and another series of pages to actually buy them.
With RIAs, the data is partially processed by the client, so a full page refresh and return trip to the server is not necessary for every action performed. Beyond breaking the mold for page-by-page data presentation, RIAs also open up a number of other possibilities for enhancing eCommerce.
At a high level, RIAs can improve the overall client experience and provide the continuity that’s lacking in many of today’s eCommerce sites. Today, when a customer arrives at a website and is faced with the task of finding a product, there are really two ways this can be accomplished, by browsing or searching. If the site has a relatively small or highly focused product offering, then browsing can be an effective way to navigate. However, if the retailer offers a wide variety of products, particularly ones with very different characteristics, then searching may be a more effective option.
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