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What social networks will need to do however is tread the line between keeping and growing user trust vs. monetizing their content. Trust within social networks and online communities have been studied for decades with the results showing transparency is critical for trust to continually be strengthened (Beth, Borcherding, Klein, 1994). There are several strategic directions that social networks could go with the data captured, yet by far the most valuable will be creating an entire suite of data sets deliverable through APIs (which were discussed earlier) to any company needing it for their SCRM systems. This data service model is a catalyst of growth for Salesforce.com, now a $1B+ providers of Software-as-a-Service (SaaS) CRM applications.
Analyzing the CRM Marketplace based on this study's Research
Even in periods of economic recession, companies continue to invest in CRM software and systems as they have proven to be solid contributors to revenue growth by retaining the most profitable customers a business has (Ernst, Hoyer, Krafft, Krieger, 2011). The two greatest challenges to creating CRM applications are gaining rapid and complete access to customer data that is compatible with the system(s) being developed, and second, changing the behavior of those employees who will need to rely on the systems for their daily tasks. The vendors who dominate enterprise-class CRM systems have exceptional expertise in data integration yet lack the ability to quickly tailor their applications to the needs of users, matching how they work and think. Figure 2, Comparing Dominant Enterprise CRM and SaaS Vendors by Software Performance illustrates this point.
Comparing Dominant Enterprise CRM and SaaS Vendors by Software Performance
Usability, the most critical element in ensuring adoption of a CRM system, is dominated by Software-as-a-Service (SaaS) vendors. The analysis indicates that the SaaS platform is more agile in responding to user needs and therefore leads to a more agile and flexible user interface design. Analysis of how social networking data is used also highlights that this aspect of social networks, their SaaS-based platform components, are what is responsible for their exponential subscriber growth over time as well (Bernoff, Li, 2008). It is interesting to note that the vendors in Figure 1 with the fastest revenue growth over the last five years are those that have deliberately used SaaS as a means to align their product strategies to how CRM users prefer to work, offering metrics of performance showing their progress over time using the CRM software. Combining competency and trust is an essential aspect of a value proposition that encompasses ethics, which is exactly the dilemma that social networks face in using the massive amounts of subscriber data for CRM today (Jonsson, 2011). The ethics of using prospects' data for CRM data needs to be resolved on a social networking site by site basis to be effective in defining a more utilitarian solution to this complex problem (Jonsson, 2011). This will also lead to a greater level of governance in how the data continually capturing in social networks is used as part of the company's own innovation efforts as well. It is clear that the magnitude of the opportunity for social CRM based on social networking data is very significant with research firm Gartner Group claiming the market will be $2B by 2012 for this class of CRM software (Sarner, 2010).
Based on the analysis completed, it is evident that social networking companies see the CRM market drastically different than the traditional vendors shown in Figure 1. As the basis of social networks is rapid updates and a wealth of data being shared about locations, preferences or "likes" and comments to friends and associates, there is a much more communicative, collaborative and fluid approach to CRM emerging than has been the case in the past (Beck, 2011). This is particularly evident in how quickly these traditional CRM vendors including Oracle, Microsoft, SAP and others are adopting the social networking-based graphical interface and usability guidelines and lessons learned (McKay, 2011). Social networks are rejuvenating CRM and making it more relevant as a software category while working to bring greater immediately of customer data into companies who are early adopters of social CRM systems. Research firms whose business models are based on selling services to these vendors have been quick to capitalize on this opportunity, going so far as to create a Magic Quadrant for Social CRM software, which is shown in Figure 2. This is a snapshot of how the majority of social networking companies also see the CRM market today; more collaborative, less hierarchical; more defined by smaller, egalitarian workgroups that are managed by transformational leaders, not purely driven by transactionally-based leadership styles.
Figure 2: Gartner Social CRM Magic Quadrant, 2010
Social networking vendors are showing increased interest in investing in or acquiring many of the social CRM vendors in the Gartner social CRM Magic Quadrant including Lithium and Jive Software for example (McKay, 2010). This will continue to escalate as social networks continue to accumulate customer data, evaluate, and pursue options for creating CRM applications and suites. Analyzing the current direction of investment and level of new product development in social networks provides the following table of potential areas where CRM will first be launched by these sites. Defined by Sales, Customer Service and Marketing, the table shows that there is significant room for social networks to enter the mobility and smartphone market, configure, price, quote (CPQ) and master data management (MDM) areas. These are critical for companies looking to sell through multiple channels, which is how social networks continue to look to use their aggregated data. In addition, social media for marketing, sales lead or opportunity management, mobile marketing and integrated marketing management are all areas that are potential growth areas for social CRM.
Figure 3: Analysis of Social CRM Opportunities for Social Networks
The use of social media data from an ethical, legal and marketing standpoint is going to be continually debated for decades, with intellectual property attorneys arguing that consumers deserve the right to know when their profile data is sold for profit. Social network companies will conversely argue that the data has been shared on an open forum and there is public data, an asset they can resell, package, analyze and in general build business models on. Between these two extremes is reality. The intent of this paper is to illustrate that for social networking companies, the greatest profits are to be made in the area of providing automated updates of highly targeted and specific data sets for use in Social CRM (SCRM) systems. As every company struggles with how to best manage the relationships with customers they have, the challenge all of them face is how to gain the greatest potential insight at the lowest possible cost. Social network providers realize this and are working to create APIs, data sets, advanced analytical tools and programs that add the greatest value to their data sets without degrading the latency and speed at which they can be delivered. All of these factors are taken into account in this analysis, and despite social networking sites claiming to use the data for improving their own applications, the reality is that the advertising business models generating over $1B in revenue for Facebook alone are crucial for their survival. This will continue and the data sets, analytical frameworks and accuracy of data capture will increase further driving sales. The concept of what CRM will also change, as a true 360-degree view of the customer will emerge for the first time.
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Theoretical Framework The balancing of social media data for optimizing the customer experience online vs. its use for advertising and selling, including the reselling of the data to other companies anchor the two continuums of the ethical spectrum. For the continuum to stay in balance there must be collaboration and disclosure of just what the data is being used for and how its success is being measured over time. An equilibrium
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