The ever expanding use of social media and mobile technologies has dramatically changed how we communicate and how we interact with the companies that sell to us. As channels of communication expand to include social media networks, blogs, forums and chat rooms, digital and physical lives are intersecting more than ever. What people do online provides an increasingly accurate picture of their customer profile, including lifestyle choices, buying preferences and brand perception. 

This technology evolution provides companies with an almost endless supply of data to help them better understand and respond to the needs of consumers. As a result, information is becoming business’ new currency and the basis for true competitive differentiation, value creation and risk management.  

Value can be extracted from all sources and types of information, including structured and unstructured, internal and transactional, external and social as well as private and shared. Recognizing the value of these sources and leveraging them appropriately, though, is a relatively new challenge for many organizations. While they recognize that value that can come from harnessing social media, most companies don’t have a strategy to organize and take action on this information. Many also lack the resources to execute on such a strategy.

Social intelligence provides deeper knowledge of customers by combining insights into customers’ social media behavior with traditional customer intelligence gleaned from conventional marketing and customer relationship management. This allows enterprises to manage real-time, or near real-time, conversations with customers, listen to their points of view and deliver contextual, relevant and engaging communications. Increasingly, these connections can be made through mobile devices that provide content exactly when people need it.

To create an effective social intelligence strategy, companies have to deal with new heterogeneous data sources, new technologies, new ways of working, new ways to measure and a new way of thinking. In many organizations, senior leaders are turning to their IT departments to get control of the volume of data and turn it into actionable insights. To help their organizations achieve their goals, IT teams need to learn how to aggregate, analyze and act upon insights found in social media streams. 

Before they embark on such a program, an IT team needs to assess its organization’s level of involvement in social media. Here are some things to consider:

  • Is the company leveraging social media today? If so, how? 
  • To what extent is the company integrating social data with other customer data?
  • Is there a defined workflow to respond to, escalate and disseminate findings?
  • Is integrated customer data utilized at the point of interaction with customers?
  • Is the current IT infrastructure struggling to keep up with the volume, variety and velocity of the data? 
  • Is the company investing in human resources who understand social media channels, their various uses and how to integrate those channels into business operations? 
  • Has the company published a social media governance policy?

Answering these questions will provide a baseline on the organization’s social media activities and will help establish objectives moving forward.
Other crucial steps include defining what the target state looks like and ensuring it is aligned with the business strategy.  For example, some companies will use the data in an attempt to influence existing customers, while others will use it to try to gain new customers and increase sales. Still others will embark on this project to alter public opinion of their brand, product or company. Some may simply want to provide improved customer service or maybe conduct research at a lower cost.

After determining the focus of the program, it’s time to build the plan.

The social intelligence plan should specifically detail what needs to be accomplished, as there are literally thousands of different processes that might be affected and there can be so many potential next steps. The plan should take the self-assessment into account and include a highly detailed definition of the target state, which should be validated with industry specific benchmarks. . A best practice is to create a proof of concept program that brings together structured and unstructured data, and then determine what is valuable and what is not.

Traditional business intelligence approaches lack the flexibility, timeliness and mobility required meet the real-time demands of this new environment. Legacy business intelligence solutions cannot support analysis of social media data sources, nor can they integrate these sources with existing customer information. It’s very important to address IT transformation, detailing what tools will be needed to make the IT environment compatible with the social intelligence plan. The plan should outline which business processes will be changed and which will be introduced, what steps the IT transformation will follow and estimate the time and cost involved.

Once the plan is in place, it’s time to execute.

The first step to a successful execution is to begin listening for relevant chatter on social media sites and communities. This can be done manually or using software tools that automate and scale listening activities to review vast quantities of social media data.  Next, teams should analyze the data gathered to filter out the noise and extract useful, relevant information. Analytical tools for this purpose already exist and more are coming soon. Finally, teams should use the information gathered to better engage with customers – enabling the lines of business to more quickly, decisively and appropriately respond to their needs.  Insights may also be gained into new and improved processes for managing customer interactions.

One area that is often overlooked is governance. New governance processes will need to be devised that take into account the need for real-time analytical insights at the point of customer interaction. Companies will need to design a governance model that aligns with the overall organization.

Measurements to gauge the effectiveness of a social intelligence initiative will vary by type of business or public sector, and will depend on the original goals that were set. Overall, success means being able to identify and act upon trends, recognize patterns and ultimately anticipate customer behavior that is first signalled in social media streams and to do this in real time.  For example:

  • A consumer goods company could leverage social media data to better understand how a product is perceived by different market segments, including positive and negative attributes, quality issues and so forth.  Company marketers could use the data to track the impact of a particular marketing campaign and adjust the campaign accordingly. The value derived may be incremental, but for a large company, even a one percent improvement in sales results can be huge.
  • Following a new drug launch, a pharmaceutical company could analyze brand perception and use blogs and health forums to support patients. Online sources can be used to monitor for side effects and to gauge customer acceptance. Drug makers can use these insights to respond before any negative feedback becomes widespread.
  • A telecom provider could make use of social network analysis to obtain information on customer migration and churn. This would help the provider identify new customer decision paths, which it could use to gain greater market share. The provider could also identify the most relevant social communities for its marketing activities.
  • A financial services company might use a real-time CRM solution that integrates both structured customer data and unstructured social media data to improve its prospect targeting and to make more relevant offers via social media channels. The company might also use the data to generate more social interactions and improve their brand image with their younger customers.
  • An automotive manufacturer could complement manual efforts to gather and report quality information and identify product defects by analyzing social media buzz to more quickly identify customer problems . The car maker could also engage with customers online and provide servicing recommendations.
  • Online and social gaming operators already collect massive quantities of player engagement and interaction data. This is used to perform complex, real-time analytics to enhance the gaming experience, direct advertising, improve customer retention and support cross-selling and up-selling activities. 

It’s important to test different approaches, processes and strategies to see how they impact key metrics, applying the learnings in the context of the overall plan.
Social media will pose a significant challenge over the next few years, upending traditional ways in which IT works with its stakeholders. But by systematically gathering, structuring and extracting actionable information from social data in real time, IT also has an enormous opportunity to bring great value to the business. 

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