As the name signifies, Social Media Analytics is the practice of consolidating data from blogs and social media websites such as Twitter and Facebook, and analysing that data to improve business. There are several advantages of Social Media Analytics but the most common use is gauging customer opinion for the betterment of customer service activities.

Nowadays, for any organisation, it is very important to know what’s being said, where it’s being said, by whom it’s being said and what impact it is having on your business. For any of the Social Media activities instigated, you must be able to measure its impact and analyse if it can be improved. Whenever a company makes an investment in Social Media, it hopes for a Return on Investment (ROI) in terms of Sales, visitors, fans, followers, etc. If the company is not getting the anticipated results, Social Media Analytics helps the company to decide where it should spend time and money to improve the results.

Implementation of Social Media Analytics

Social Media Analytics can be implemented in three steps. They are as follows:

Object Identification : The first step in Social Media Analytics is to determine why you would like to get involved in Social Media at all. Objectives vary from company to company. Typical objectives are increasing revenue, reducing customer service costs, crowdsourcing, getting feedbacks on products and services, improving public opinion of your company or a combination of all such objectives. Most objectives can be categorized as follows:

  • Exposure
  • Engagement
  • Influence
  • Action/Results

Identification of KPIs (Key Performance Indicators) : Once you have identified your objective behind Social Media, you should identify the factors that can be used to evaluate your performance. These factors are known as Key Performance Indicators or KPIs, for example you can evaluate customer engagement through number of followers on your corporate Twitter account. Other KPIs are:

  • Number of fans and friends on Facebook
  • Number of Twitter followers
  • Number of LinkedIn followers
  • Number of mentions of your company in tweets and updates
  • Number of YouTube subscriptions
  • Digg links

KPIs for different types of Objectives have been listed below:

  • Exposure

    • Search engine rank
    • Unique visitors
    • Increase in traffic
    • Pay-per-click ad impressions.
  • 2. Engagement

    • Page views per visitor
    • Time spent on site/blog/Social Media
    • Click-throughs
    • Repeat visitors
    • Comments
    • Messages
    • Reviews
    • Ranks
    • Posts
    • Social bookmarking
    • Fans
    • Followers
    • Friends
  • 3. Influence

    • Retweets
    • Recommendations
    • Bookmarks
    • Sent to a friend
    • Links to your site/blog/page
  • 4. Action/Results

    • Purchases
    • Leads
    • Contacts
    • Increase in sales
    • Calls
    • E-club sign-ups
    • Conversions
    • RSS subscriptions and track-backs
    • Requests to be a fan/follower/friend
    • Savings in customer service or market research
    • Number of resumes submitted or number of candidates interviewed

Evaluating Return on Investment (ROI)

To keep a track on your investment there are certain stats that must be evaluated beforehand like

  • Revenue and time spent on customer services through Social Media
  • Revenue and time spent on market research through Social Media
  • Revenue and time spent on recruiters for recruitment through Social Media

After measuring the investment, the ROI can be calculated using the KPIs mentioned above. But it should always be kept in mind that quality triumphs quantity every time, hence the quality of result must be taken into consideration, for example, you may have several Twitter followers but they are useless if they are not interested in your products and services.

Chosing the right tool

There are several Social Media Analytics (SMA) tools that include applications to identify the best Social Media sites to serve your purpose, applications to harvest relevant data and analyze it. The best feature of these SMA tools is text analysis and sentiment analysis which helps to analyze unstructured data such as tweets and facebook posts.

Advantages of Social Media Analytics

Following are the advantages of using Social Media Analytics:

Gain a Competitive Advantage : Social Media Analytics (SMA) tracks your organization’s portfolio, competitor activity, how customers use your products and services, problems with your products and how your organization is being viewed by the people. Thus SMA provides a competitive advantage by understanding how your company is perceived in comparison to your competitors.

Learn from Your Customers : You can use customer support for expanding your business. Customers are now providing solutions to an organization’s problems and to other customers. The vendors can exploit their customer base to endorse the brand.

Enhance Your Products and Services : SMA analyzes the blogs, tweets, comments, etc to find out the sentiment about products and services. Thus the organisation can understand the issues and problems that the customers face and make them better. SMA identifies the problem, finds who or what is to blame and even presents options to resolve the issue, thus enhancing your product.

Better Target Marketing Efforts : Organisations are looking for ways to optimise their marketing efforts. The information collected by Social Media Analytics helps the organisation to understand whether their marketing campaigns have yielded desired results and if not, how it can be improved.

Market Innovation : Organisations can mine the user feedback via Social Media sites to discover faults in their market and come up with innovations based upon customer suggestions.

Limitations of Social Media Analytics

Social Media Analytics has a lot to offer but the technology used in it is not very effective. Hence it cannot analyze the customer reaction accurately every time. Sometimes the human conversation is too complex to be analyzed through softwares. For example, “sick” means “unwell” in conventional sense but it is also slang for “cool”. Sentiment analysis tools should be sophisticated enough to include context in evaluation like sarcasm. Only then Social Media Analytics can be fully effective.