Making sense of social media

If you want to know what someone thinks, just ask. Better yet, just listen. Unsolicited feedback is everywhere and oftentimes people will tell you what they’re thinking without any prompting.

The world is a noisy place and the advent of social media has resulted in nearly non-stop dialogue in countless locales. In fact, we’d go so far as to say that we live in the ‘Age of Over-Sharing’.

Social media has unleashed the power of self-expression. Gone are the days of the internal monologue. Today, people share everything online – from medical ailments to stories about their kids and pets to recipes to life’s aggravations to their favorite (and more often least favorite) restaurants, brands and products.

This over-sharing might seem useless to some, but this ‘babble’ actually has incredible hidden meaning, relationships, patterns and trends.

Companies today would be shortsighted to ignore what their customers are saying about their products and services, in their own words. Those opinions are essential nuggets and reveal much more insight than traditional demographic or transactional data.

The challenge in analyzing customer feedback used to be in gathering enough data to make informed decisions. Social media has created a new challenge: understanding the rich content from endless streams of unstructured data.

Create relationships, build advocacy, and improve loyalty

Smart organizations leverage social media to gain insight into consumer opinions and spot trends related to products and brands.

New technology has become available to help these companies analyze ‘online buzz’. Social media analytics solutions allow them to listen to, measure and analyze large volumes of publicly available social media content from billions of blog posts, thousands of online forums and discussion groups, as well as publicly available content on Facebook and Twitter.

Businesses increasingly recognize that the vast amount of critical data resting within these social media sources is important for them to capitalize on, and that it offers an opportunity to extract knowledge to better understand and respond to customer opinion and feedback.

For example, if a retail merchandising manager from a high-end fashion line wants to gain better visibility into how a newly released woman’s print dress is being received by consumers, social media analytics can identify, capture and report on millions of pieces of social data to provide instant feedback on that particular item.

Managers can now use this critical feedback by analyzing keywords found associated with the dress to better understand buying trends and consumer sentiment – if the red print dress is being described as too loud or too bold, brands can now make recommendations to the designer on creating the dress in black instead of red in order to adjust to customer preferences.

It also helps organizations analyze the success of their marketing campaigns, such as what are consumers saying and hearing about my brand? What are the most talked about product attributes in my product category? Is the feedback good or bad? How are consumers responding to our new advertising campaigns? What is my competition doing to excite the market?

For example, what if a famous pop star is doing more harm than good as the spokesperson for the brand? Brand campaign managers can now evaluate data from prime social sources to make smarter decisions around advertising campaigns moving forward and tweak current campaigns.

All of this information can be easily displayed on a dashboard with tables and crosstabs, as well as pie charts and trend charts to easily understand and share what is being said in the social media landscape.

Analyzing online buzz to increase viewer involvement

A great example of an organization which is effectively making use of online conversations is the Dutch entertainment company RTL Nederland.

In order to evaluate its television programs such as X Factor, RTL decided to capture viewer opinions from user-generated comments on social media by using analytics software. By analyzing, interpreting and successfully responding to audience feedback from social media sources, it was able to better understand viewer needs and preferences and hence increase viewer involvement.

The insight obtained on viewer likes and dislikes, for instance on the jury, the choice of music, the themes of the live shows and the contestants themselves, allowed RTL Nederland to optimize its product offering and quickly adapt the program accordingly.

A truly 360 degree view of customers

It is relatively easy for organizations to analyze transactional data to learn which customers spend the most on their goods and services. Adding demographic and attitudinal data from a satisfaction survey can help further segment customers into meaningful groups and thus drive different responses or communication strategies.

The cherry on top is social media data. It provides even richer insights into customers’ true feelings because they’re speaking in their own words and by their own initiative. The ability to now incorporate social media data into predictive analytics solutions gives businesses a comprehensive understanding of their customers.

By understanding customer preferences and buying patterns, businesses can build predictive models to better determine future outcomes with a great deal of confidence. Knowing that customers who complained about customer service tend to leave for competitive offerings, businesses can preemptively act to retain those customers.

Active listening

Marketing no longer has a mute button. With social media analytics software, organizations are better enabled to transform their customer relationships by actively listening to what customers are saying on public social media channels.

Most customers expect (and demand) greater levels of intimacy from the companies with which they choose to do business. The analysis of social media data moves organizations one step closer to the goal of achieving truly scalable one-to-one marketing. By turning up the volume, organizations are more agile, precise and responsive to market and customer demands.

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Colin Shearer is the Senior Vice President of Strategic Analytics at SPSS – an IBM company. Colin has Co – Founded and Directed his own solutions company and has held a Principle Consultancy role at Quintec Systems. Due to his experience, Colin has some valuable and original opinions about how companies should be using social media to shape business models.