Modern business cannot ignore social networks. Regardless of their size, companies create accounts on Facebook, Twitter, and LinkedIn. They then they use them on various purposes. The specific character of social networks and the extensive growth of their audience creates a new challenge for business in that now accounts and profiles are needed not just to attract new users, but to work with an already existing client base.  

A Few Facts:

  • In 2016 “The State of Social” report revealed the data, according to which 54% of all companies support their clients through social networks.
  • According to internal data of the Sprout Social specialists,  in search for support, customers first turn to social networks, and only afterward look for other possible communication channels. In 2015-2016 the number of users searching for support via companies’ accounts in social networks increased by 18%.
  • Experts from the University of Hartford and the University of South Carolina have revealed an interesting pattern: the more actively a company works with its customers through social networks, the stronger users associate it with the brand. In addition, these customers often demonstrate their loyalty and interest in the services and products of the company.

CRM Systems for Business Analysis

Social networks for business is a relatively new, little-studied channel of interaction with users, which is almost deprived of anonymity, – users have their own accounts with the filled in information. If necessary, you can create a profile for each client by collecting the available information about him.

Analyzing such large amounts of information is not so easy, and over time there will be even more data. Its growth will be avalanche-like, as users spend more and more time online and their communication mostly takes place in social networks. Online life is becoming an integral part of real life. Leading social networks are facing a powerful influx of new users. According to the statistics, over 2 billion people in total use social networks today.

This entails serious consequences for companies. If the customer is not satisfied with the service, he can always leave a negative comment on his page. For him, it is much faster and easier than trying to reach the company’s support service. This is how a high degree of mistrust towards the traditional ways of solving problems arises. The old practice of ignoring questions and providing sample answers by email simply just won’t cut it anymore.

Companies that value their online reputation (Wait. And who doesn’t?) should continuously monitor negative comments in social networks, respond to them in time and transform negative customer experiences into positive ones. Ignoring users’ messages is a straight way to lose all loyal customers. The processing of negative responses in social networks can be done manually by small and medium-sized businesses – it does not carry any particular difficulties. However, big companies, which have numerous branches, territorial divisions, and retailers, scattered in different cities, cannot cope with this problem in such a simple way.

Monitoring customer reviews in social networks is similar to the analysis of requests through other channels (email, support forums, etc.). However, in case of social networks, all comments become visible immediately. Only in rare cases, are the reviews positive. Most often you have to work with the negative ones. All this opens up a new activity field for business – analysis of large volumes of incoming data. To do so modern technologies based on Big Data are required.

Analyzing Big Data in Social Networks

There are quite a fair number of solutions for monitoring social networks at the market. For example, there are social analytics platforms as and However, the main problem is that they all provide a different set of analytical options depending on the solutions, the platform, and the country. Some companies prefer to use cloud technologies for this purpose, others are reluctant to use any kind of external services.

The majority of these solutions are focused on the needs of medium and small businesses. Whereas large companies have specific requirements for systems to work with data. In large enterprises, there are usually call centers and special services which work with social networks. Such enterprises strive to minimize the number of applications that their employees work with. Therefore, the customer often wants to work within his own CRM-system, which often doesn’t have access to the Internet. However, not all SaaS applications have the opportunity to integrate into the complex internal architecture of the customer. In addition, customers are not always comfortable with the idea that the analysis takes place outside of their domain. In such cases complex, personalized solutions appear at the market.

Methods of Content Analysis in Social Networks

Big Data specialists have created solutions for analyzing the content of social networks, which allow you to compile information about the comments and requests of specific users. The most successful solutions are closely connected with CRM systems. Any comments and feedback left by users in social networks can be immersed in CRM for examination and processing. Advanced platforms and solutions support all popular social networks.

An interesting feature of platforms for analyzing and processing content in social networks is the ability to group profiles and comments across all social networks into a single client card. In the future, you can open the card, see all comments, clarify information about the client, find out his preferences, interests, hobbies, etc. The detection of the same user profiles in different social networks is based on Big Data technologies. To understand whether accounts belong to the same user, the platform analyzes a number of different factors and attributes. For example, it can be used to find similar publications, deanonymize the client, etc. Such platforms collect public users’ information available in social networks and insert it into a separate database, where these data are subsequently compared and analyzed. Traditional CRM systems are not capable of none of the above.

The use of machine learning technologies allows one to analyze the activity of users in leading social networks, study social profiles and track any feedback and comments left by customers of the company. Users’ profiles can be segmented by social activity, demographic data, interests, and more.

The prognostic component of such systems defines the mood of the comments (negative or positive response), their priority, focus, and other features. Continuous learning helps the system to improve itself and improve the accuracy of its work. Understanding the essence of the response allows you quickly transfer it to the right unit responsible for processing and increase the speed of solving all support requests.

The analysis of users’ feedback in social networks helps companies not only work with negative responses but also attract customers to improve the product line. If the company plans to make any changes to its sales proposals, it can contact customers directly and get their opinion. Such dialogue is characterized by high transparency and a maximum degree of personalization.

Another advantage is the ability to track how strongly users are satisfied with the brand. Direct communication with clients in social networks helps companies maintain their reputation at a high level. Information obtained from social networks can also be used to solve other related tasks.

Impact of Big Data Analysis on Business

Analysis of users social activity is an important link between marketing, security and work with users’ feedback. With the help of marketing data, you can send users individual offers, discounts, and promotions. Work with feedback implies a search for negative comments in various social networks. Recently, companies have sought to cover not only social networks but also thematic resources (communities, forums, etc.).

Maintaining a solid reputation is an important aspect of the existence of any company. Identifying negative feedback on social networks and prompt response to them allow you to win and keep customer loyalty for a long time.