Social media, mobile technologies and cloud computing have disrupted traditional business environments and operating models over the last few years. Keenly aware executives and leaders, around the globe and across industries, are increasingly searching for innovative ways to interact with their customers to drive more growth.

Social media has already changed the game for CMOs and become an essential part of the marketing toolkit due to its response speed, low entry costs and audience reach. All signs point to the fact that a formidable investment in a strong social media strategy will go from a nicety to a must-have in 2014.

Social media strategies, like all marketing strategies, should be planned, executed and managed. However, due to social media’s disjointed past, many executives are struggling to harness social media to achieve their business objectives and drive superior performance. Additionally, many organizations are looking for answers that could help them measure the ROI on the social media activities which they run within the organization. While most companies diligently establish Twitter feeds, branded Facebook pages and forums/blogs, only a few truly understand exactly how social media interacts with consumers to expand product and brand recognition, drive customer acquisition and retention, and engender loyalty.

Introducing the Social Media Effectiveness Index (SEI) Model

To determine true social media effectiveness, organizations must capture the full breadth of social media and incorporate metrics that are useful in understanding business impact.

Blueocean Market Intelligence conducts a reoccurring global study that evaluates social media effectiveness and identifies top performers among brands using the Social Media Effectiveness Index (SEI) model.

SEI first captures conversations happening on social networks and in online communities, correlates their impact against key metrics, and then directly measures the outcome of business-to-consumer interactions in social media, including how top influencers on Twitter and engagement on Facebook drive site visitors and purchase behavior.

The methodology is specifically designed to measure impact by integrating social media analytics, measurement and monitoring with multichannel analytics, and consists of four distinct layers:

  1. Data Collection: Using a combination of best-in-breed enterprise-class listening assets, social media is captured from a corpus of more than 250 million sources, which includes major social networking platforms like Facebook, Twitter, Pinterest, Google+, YouTube, Flickr, Quora, etc. and blogs, forums, communities and country-specific social networking platforms. Global and country-specific search engines are used to cover those platforms that are otherwise not captured by the listening engines.
  2. Data Filtration and Text Mining: Industry-specific rules are created and fed into a text-mining engine to process millions of conversations captured in the data collection stage. The primary objective of this stage is to remove noise, refine sentiments, build stories and themes and filter conversations.
  3. Analysis (SEI Parameter Calculation Engine): Deep analysis into the five key SEI parameters, defined as:
  • Share of VoiceThe number of relevant conversations about a company versus its competitors/market. It is crucial to track the volume of conversations about one’s brand. As we know, the more people talk about a brand, the more exposure it gets – and with more exposure comes more visibility, one of the most primitive goals of branding and marketing.
  • Engagement RateThe number of interactions divided by the total number of fans and multiplied by 100. The engagement rate is a measurable result of online performance and can support social media professionals as they fight the traditional convention to simply grow their numbers. It allows an engagement comparison between organizational Facebook pages with pages that have different audience sizes.
  • Customer Touch Rate – The number of acknowledgements/replies provided by the brand in comparison with the total number of issues raised on Facebook and Twitter. If customer issues are not recognized (and sometimes immediately), then all the social media efforts and resources invested won’t yield returns. With customers increasingly seeking control of their relationships with companies, reaching out to customers on the platform of problem origination will further define the customer experience strategy of the brands.
  • Influencers and Advocates – Influencers are the number of individuals or Web entities that have a strong following/readership within the social media channels. Using a Big Data-like approach to topic search and marketing analytics based on deep, comprehensive analysis of millions of Tweets, the influencer identification framework reveals who is most influential for the target brand. Data analysts and scientists specifically monitor keywords, track trends and influencing opinions related to the company’s products or areas of interests.

Influencer Identification Approach

  1. Relevance: Conversations from the selected influencers are monitored and relevancy is evaluated based on a pre-defined set of relevant topics and brand mentions.
  2. Reach: An analysis of a person’s immediate (direct) audience and broader (indirect) audience is completed to determine how far information can travel across the customer’s social graph and network at large. This includes measurements of popularity, affinity and potential impact.
  3. Resonance: This is measured through the speed and degree at which a network responds to information shared by the influencer. This includes measurement of duration, rate and interactivity levels with the content.
  4. Social Network Analysis (SNA): By using the social data, profiles with high reach and resonance are analyzed and validated to quantify social influence within their network.


Advocates are the number of individuals who are recommending the brand/products/services on the social channels. Advanced machine learning techniques like natural language processing (NLP) are applied across the entire data set to automatically determine the context of advocacy in every conversation.

  1. Net Sentiment – Sentiment analysis, or opinion mining, offers valuable intelligence by tracking sentiment of the conversations— the tone of a written message (Tweet, Facebook update, etc.) — and then tagging that text as positive, negative or neutral. The process typically involves a large amount of text mining and natural language processing. Quantifying sentiment has the ability to improve customer interactions and allow organizations to better understand the needs of the social consumer. Net sentiment score is then calculated using the NLP technique and assigned.
  2. Quality Control Layer: Data analysts apply a random stratified sampling process to validate the scores derived from above steps and stringent quality checks for each step ensure correct indexing.

Each of the Analysis parameters are then linked to key business metrics, such as social media market share, brand awareness, marketing strategy, customer experience, brand perception and revenue. Companies are assigned a net sentiment score assessing their true effectiveness of social media outreach. If the net sentiment of the brand is negative, then it’s best to revisit the strategy.

Aligning social media activities with core business objectives differentiates the SEI model from traditional analytic tools and ranking methodologies.

Rethinking Measurement

When companies begin to measure social media effectiveness, it’s easy and instinctive to turn to popular social media analytics tools. However, many such tools lack reliable data, accurate sentiment analysis and overall depth. If the primary objective of social media outreach is to increase brand awareness, build brand reputation and ultimately generate leads, then measurement efforts need to be aligned accordingly.