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Social Media Listening

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Social Media Listening

Social Media Analytics is the practice of gathering data from blogs and social media websites and analyzing that data to make business decisions. The most common use of social media is to mine customer sentiment. Social media analytics is a powerful tool for uncovering customer sentiment dispersed across countless online sources. This analysis is often called Social Media Listening or Online Listening. The analytics allow marketers to identify sentiment and identify trends in order to better meet their customer’s needs.

When it comes to social media and implementing it into an organization, the one constant question is: “How can I quantify my ROI?” A good example of how a company can test whether a social media solution would work for it is to consider the experience of a telecommunication company that proactively adopted social media recently. The company had launched Twitter-based customer service capabilities, several promotional campaigns built around social contests, a fan page with discounts and tech tips, and an active response program to engage with people speaking with the brand. In social-media terms, the investment was not insignificant, and the company’s senior executives wanted quantifiable ROI, not anecdotal evidence that the strategy was paying off. As a starting point, to ensure that the company was doing a quality job designing and executing its social presence, it benchmarked its efforts against approaches used by other companies known to be successful in the social media field. The telecommunication company advanced the following hypotheses:

  • If all of these social-media activities improve general service perceptions about the brand, that improvement should be reflected in a higher volume of positive online posts.
  • If social sharing is effective, added clicks and traffic should result in higher search placements.
  • If both of these assumption hold true, social-media activity should help drive sales—ideally, at a rate even higher than the company could achieve with its average gross rating point (GRP) of advertising expenditures.

The company tested its options. At various times, it spent less money on conventional advertising, especially as social-media activity ramped up, and it modeled the rising positive sentiment and higher search positions just as it would using traditional metrics. The results were quite conclusive: social-media activity not only boosted sales but also had higher ROIs than traditional marketing. Thus, while the company took a risk by shifting emphasis toward social-media efforts before it had data confirming that this was the correct course, the bet paid off. Just as importantly, the company had now created an analytic baseline that gave the company confidence to continue exploring a growing role for social media.

Starbucks has also developed a metric it believes is able to quantify the value of its social media marketing in terms of media spend–the company’s 6.5 million Facebook fans are worth the equivalent of a US$23.4 million annual ad spend, according to calculations by SM specialists Virtue, reported in Adweek. The firm has worked out that, on average, a fan base of 1 million translates to at least $3.6 million in equivalent media over a year, or $3.6 per fan. Virtue arrived at its $3.6 million figure by working off a $5 CPM, meaning a brand’s 1 million fans generate about $300,000 in media value each month.

The first step in a social media analytics initiative is to determine which business goals the data that is gathered and analyzed will benefit. Typical objectives include increasing revenues, reducing customer service costs, getting feedback on products and services and improving public opinion of a particular product or business division.

Once the business goals have been identified, key performance indicators (KPIs) for objectively evaluating the data should be defined. For example, customer engagement might be measured by the numbers of followers for a Twitter account and number of retweets and mentions of a company’s name.

Through social networks like Twitter and Weibo, organizations can pick up customer satisfaction in real time. Social media is enabling companies such as Coca-Cola, Starbucks, and Ford to go beyond standard customer satisfaction data gathering to innovate by setting up and participating in communities to gain feedback from customers.

When looking at what objectives companies were seeking when implementing customer analytics technologies with social media data, TDWI Research found that gaining a “deeper customer understanding” topped the list at 56%. “Social media listening can provide an unprecedented window on customer sentiment and the reception of an organization’s marketing, brands, and services.

For more sophisticated sentiment analysis, text analysis tools play a big role. “These tools employ lexicons, word extraction, natural language processing, pattern matching, and other approaches to examine social media users’ expressions. Sentiment analysis can give organizations early notice in real time of factors that may be affecting customer churn.” Sentiment analysis is also important to understand competitors’ relative strengths and weaknesses in the social sphere.

“One of the biggest challenges can be simply deciding which social media sites’ data to analyze. Organizations have to research where their customers are most likely to express themselves about brands and products. They need to spot influencers who have networks of contacts and take it upon themselves to play an advocacy role." About 20% of respondents are interested in differentiating influencers from followers in social media. “Link analytic tools and methods specialize in identifying relationships between users in social communities and enabling organizations to measure users’ influence." “With some tools, data scientists and analysts can test variables to help identify social communities as ‘segments’. Then, as they implement segmentation models for other data sources, they can integrate these insights with social media network analysis to sharpen models and test new variables." 

Analytics are critical for enabling organizations to make the right decisions about when, where, and how to participate in social media. It isn’t enough to just listen; organizations much insert themselves and become part of the conversation. Smart companies will start viral campaigns, for example, using Twitter Hashtags for a topic; the campaign could be a component of a larger marketing strategy. Business could then monitor social media to see what people say and analyze how the campaign is playing among influencers and across networks.

TDWI Research’s found that Facebook (31%) and Twitter (25%) are the most common social media data sources that respondents currently access, while internal interaction records such as the voice of the customer (VOC) logs are just below Facebook at 31% as well. This suggests both the understandable immaturity of organizations’ pursuit of social media data sources for analysis as well as a desire to apply advanced analytics tools and methods to internal customer information sources they may view as more important.