New Report Shows Retailers Slow to Make Use of Social Commerce Big Data

The third annual Social Commerce IQ (SCIQ) report, based on survey results from 872 retailers regarding data from seven popular social platforms, shows that retailers have been slow to take advantage of the opportunities available to them in data from online consumers on brand awareness, traffic, and social CRM.

The new report, prepared by social discovery pioneer 8thBridge, reflects the volume of information coming to the retailers from various social networks, as well as each retailer's volume of followers and interactions with them. Another measure in the report attempts to reflect how extensively each retailer integrates social media capabilities and information into its eCommerce platform.

Report Findings

According to the report, maintaining a dynamic presence on social networks and taking action to drive consumer engagement are the twin hallmarks of capabilities that retailers are trying to make the most effective use of. More than coincidentally, these same retailers tend to provide more interesting and compelling social experiences on their websites, often utilizing such techniques as customer curation of information, crowd-sourced recommendations, and loyalty programs.

Most importantly, the report shows that many popular brands have not yet learned to take full advantage of the data available via social networks and social marketing interactions. To move further into this realm, companies will have to persuade online visitors to participate in particular social media events and activities.

For example, brands that allow visitors to log on using their Facebook accounts—rather than the traditional login form—tend to be able to collect myriad details about those visitors' online preferences, activities, habits, and histories.

According to the report, approximately 89 percent of respondents to the survey request access to a visitor's Facebook friend list, yet they gain little value from this information. Savvy retailers could, however, use the friend list to glean important insights about the visitor and also to identify other people who might be interested in learning more about the retailer's products.

In addition, Twitter and Instagram have proven extremely popular among individuals who spend time on social media. Yet large numbers of online retailers are basically invisible on these networks, with fewer than about 10 percent of survey respondents indicating that these networks provide them with important volumes of traffic.

Big Data analytics applied to social media interactions can give rise to new forms of intelligence-driven security, allowing automated assessment of risks and defense against advanced threats.

Metrics

This year's Social Commerce IQ report surveyed 872 web retailers selected from the Internet Retailer 2013 list of the top 500 online retail sellers, plus additional retail firms that were deemed "up and coming" in the online commerce environment.

The analysis considered 52 different social data points reflecting each retailer's activity on Facebook, Twitter, Pinterest, YouTube, Instagram, Google+, and Vine. Analyzed data included upstream traffic from the social networks, engagement metrics such as each retailer's number of followers, the raw volume of retailer interactions with individual consumers, and metrics intended to reflect the extent to which each retailer is making use of social networking capabilities and features within its proprietary eCommerce sales funnel.

The report shows that retailers can gain access to rich data via social media and that those who do so can leverage this information to get additional brand lift and conversion of visitors to customers.

There are, or soon will be, opportunities for Big Data analysis of social media and other interactions to aid in network security monitoring, user authentication, fraud detection, and more. These new capabilities will create opportunities and requirements for organizations to rethink their security efforts, from conception to implementation, supporting a unified security architecture and strengthening the application of data science to security efforts.

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