Social Media for Enterprises, the Next Phase

The volume of data that is mined by today’s enterprises is almost unthinkable in traditional terms. The information collected from social media alone is greater than all the customer data available to businesses only a few short decades ago. In 2009 that social networking passed email as the main form of online communication. Organizations can have data stores in the petabytes, and numbers like this can only be expected to grow, if previous trends are realized.

The amount of data you can analyze as it allows the analyst to find relationships that permit her or him to make more accurate predictions of marketing trends, social movements, and legal and regulatory probabilities that will affect how does a business function. Much can be predicted about customer behavior and preferences, and while some data will have to be governed by privacy and other regulations, unquestionably the potential value of this data is too high for businesses to ignore it, or fail to develop strategies to deal with it in the future.

However, having discovered the key information available from social media online, businesses are integrating this business wisdom further, from interacting with the public through social media to making social networks available on intranets, where additional data can be collected and reused to improve business practices. The intranet, formerly a fairly informal hosting environment for local applications and short-term file transfers, frequently includes social features as well as hosting timekeeping, project planning, and employee self-service portals.

A Brief History of Businesses and Social Media:

Clearly getting value out of such a vast store of data is a huge challenge, but by this challenge we can also define the benefits to big business of big data – and identify some big trends.

Big data is often characterized by “the four V’s”:

• Volume because the amount of data dwarfs previous measures;
• Variety because the data comes from a variety of sources from creation in-house to being gathered from social media;
• Velocity because not only is data generated extremely fast and round the clock, but also has the power to produce instantaneous – “viral” – reactions.
• Veracity or Validity because with such varied sources the quality of the data must be verified in some way.

For a very long time, business focused heavily on this volume as an end in itself – to collect as much data as possible whether or not there was an immediate use for it. A certain amount of trust was placed in the future abilities of software to analyze and make sense of this vast store of data. The amount of the business intelligence could be derived from somehow sorting through the millions of online conversations, public and private, was too tempting – in theory – to let go of data that could be of marketing or competitive value...someday.

However, making sense of data requires technologies geared up for the enormous volume, variety, velocity, and business requirements while remaining cost effective has been an elusive goal. In the meantime, they could see what people were saying about them, and react quickly.

Now that some time has passed since business’s first love affair with big data, some realities have set in, including the difficulty of doing anything meaningful with data stores of that size. In addition, organizations face the issue not just of finding what is meaningful in a huge store of social media data, but understanding what is possible to be inferred from it. It is not enough to utilize listening tools and public sentiment analytics; it has been necessary to include the intuitive abilities of human intelligence to allow companies to filter out noise from meaningful dialogue. And even with this kind of filtering, making sense of vast amounts of data is still difficult.

Faced with an impossible task of making sense of what was little more than a proliferation of unclassifiable data, organizations have changed their social media presence and strategies in a number of meaningful ways in order to derive social business intelligence – business intelligence gained specifically from social media. And even then the data we were able to collect grew, fueled by the powerful computing power of the Cloud. Both by its size and by its distributed nature, the Cloud is especially well-positioned to provide the computing power needed by harnessing a multiplicity of machines to perform tasks in parallel, able to analyze volumes of data as never before.

Making Sense of Big Data:

1. Well-Defined Goals. What are the goals of the organization’s social media presence? It seems naïve to think of it now, but for a long time many organizations had no real sense of needing or wanting a social media strategy, though it was clear that having one was a desirable thing to do. Young teams were deployed to manage social media sites, admirably dealing with customers in new and creative ways, but the value of the social media site took some time to be understood by many organizations, and so the sites originally functioned in an ad hoc manner, frequently delightfully, but not particularly goal-driven.

Organizations have begun to recognize the value of having goals attached to their social media presence, and have moved from a haphazard presence to explicit, stated goals. Typical goals for an organization to define for its social media presence include:

• Accelerate innovation by predictive technologies
• Improve customer service
• Lower customer service cost
• Get feedback on products and services
• Better understand the customer experience
• Improve public opinion
• Draw people to the site as an advertisement
• Enhance hiring practices by helping identify people who are enthusiastic about your brand and are customer-service oriented
• Focus recruitment efforts on your skilled employee pool through social network sites like LinkedIn
• Reinforce branding throughout a large organization


2. Data governance. Collecting a lot of data is valuable only if the data if valuable, so companies are more focused than ever on ensuring that they can classify their data meaningfully, which leads to:
• Better, more productive searches and better-located data
• Appropriate storage and security based on data type
• More meaningful connections between data


3. Measurement. Businesses depend on meaningful and extensive measurement and have done so long before the digital age.
• Correlate social media strategies with key performance indicators to determine ROI from social media presence.


4. Intranet Social Networks. Large organizations frequently run social networks, benefitting in a number of ways.
• Coworkers have an opportunity to meet and engage even in a large company with many locations.
• Self-help and self-service networking sites ease the load on technical support staff.
• The sites provide greater opportunities for collaboration.
• Intranet initiatives encourage mass participation and team communication.


5. Controlling and Securing Data. One reason organizations engaged in such a data craze was the awareness that privacy concerns would eventually become a consideration for organizations collecting a large store of data on its customers or potential customers.
• Privacy concerns and regulatory requirements will grow, requiring companies to be careful about what data they collect, how they use it, and how they store it.
• Security has become a crucial issue where protecting customer privacy and protecting the integrity of a business is needed. Therefore, it is required to install Cheap EV SSL Certificate help to protect from phishing and malware attacks.


6. Software for the New Era. There are a few of types of software tools that are fairly effective in analyzing unstructured data from social media posts, and with some investment in these tools, organizations are better able to make use of their data.
• Software can analyze and mine data using applications that plug into social media networks to learn about users based on their behavior: who they interact with, and how they behave. Based on this data, the technology returns contextualized recommendations for content, conversations, and personalized searches that customize the social network experience for many users.
• LinkedIn’s search does real-time updates in which the time between when a user updates his or her profile and another user being able to find that person by the updated information is nearly instantaneous.
• Another high-profile model for enterprise social applications is OpenSocial. OpenSocial is an open standard that was originally sponsored by Google. It is a set of APIs to build social application across different websites. The Apache project has been a major enabler of OpenSocial in the enterprise.

The value social networks bring to sites in making them communities has driven thousands of Web sites and applications to include social networking in their architecture.

CONCLUSION:

The approach to big data and social media has to cross a generational divide for acceptance of social media as a viable tool, and a technical divide to effectively sort, store, and analyze such large amounts of data. But one can already see a difference in how companies treat their social media sites as legitimate generators of a great deal of valuable data, and are already doing different things with data now than they’ve done in the past. Savvy companies recognize that big data offers more unique algorithms based on customer behavior that allows personalized experiences, placing them ahead of their competitors.</>