What to Look for in a Social Media Analytics Tool

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What to Look for in a Social Media Analytics Tool

Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.

November 2010

SOCIAL BUSINESS COLLABORATION

2Proprietary and confidential. Not to be used or distributed without the consent of Collective Intellect, Inc.

The importance of implementing a social media analytics tool is critical to your overall social media strategy. Whether you are just getting started “listening” to your customer, or want to fully integrate a solution as part of a Social CRM model, there are three areas you may want to consider:

1.Data Refinement2.Data Associations3.Actionable Insights

You may also want to consider the type of technology that is performing the data configuration: keywords or Boolean term expressions, Linguistics Rules-Based Natural Language Processing (NLP) or Latent Semantic Analysis (LSA)

If you have other tips or suggestions, drop us a line at jennifer dot roberts at collectiveintellect dot com.

Our View



Required to provide structure and clean the data for more in-depth analysis, focusing only on conversations that are relevant.

1. Data Refinement – Tidy things up a bit


Clean – Scrub the data to eliminate duplicate/invalid or incomprehensible content.

Attribute Extraction - Identifies and extracts core attributes from conversations to enable baseline trending and analysis, including: buzz activity, themes, authors, day-part analysis, gender, generation (age), and geography (country, state, city, ZIP), consumer affinities and associations on topics.


Enable deeper analysis, including a combination of advanced sentiment definition, semantic analysis, topic creation and influencer identification.

2. Data Association – First, Let’s Get to Know Each Other


Theme – Identify semantically similar content groups by extracting true contextual meaning from within and across “like”-conversations.

Sentiment Definition - Identify the tone of posts, verify meaning and context.

Semantic Analysis - extract precise contextual meaning from consumer conversations. Selects conversations based on their meaning and not just the occurrence of specific terms.


2. Data Association – We have More to Say on This One


Topic Creation – A combined semantic and keyword technique to achieve a high degree of accuracy, minimizing the occurrence of false-positives and false-negatives.

Influencer Identification - A deep profile on content authors that enables us to rate degrees of influence against specific topics over time. Trendsetting activists and detractors.


While it is interesting to listen to and analyze social media conversations, the ultimate goal is to create actionable insights that can drive areas such as marketing, public relations and overall business objectives.

3. Actionable Insights – Now, Let’s Dance


Sentiment - Automatically detect the writer’s opinions.

Emotional & Rational Adoption Associations - Ability to identify growing / shrinking trends in time by identifying related themes in time

Whitespace analysis - identify ways people are using a brand’s products which the brand is unaware of

Brand Characteristics - Taste, features, quality, etc


3. Actionable Insights – Now, Let’s Dance


Consumption Metrics - Intent to watch, buy, loyalty, ritual connections

Consumer Associations - Economic, quality, selection, trust, authenticity, etc

Influencer Identification - Deep profile on content authors that enables the user to rate degrees of influence against specific topics over time.

Projection - Customer will be able to project a trend or an insight discovered to a larger population (twitter, facebook, blogs, etc).

Prediction - Using historical data, ability to predict with a certain margin of error and certitude what will occur.


Technology Choices


Ok. Now, that we know what we want out of our tool. We need to have an understanding of the technology that is driving the data configuration that is providing these actionable insights.

The three primary methods are:

•keywords or Boolean term expressions•Linguistics Rules-Based Natural Language Processing (NLP) •Latent Semantic Analysis (LSA)


Technology Choices – Keyword or Boolean Term Expression


Pros •Easy to use as they behave just like a search engine

•Less Expensive

Cons •Requires exactness in word choice and specific knowledge of the information sought after.

•Expressions quickly become unmanageable as negative terms are added in an attempt to exclude references to unwanted content


Technology Choices – Linguistics Rules-Based Natural Language Processing (NLP)


Pros •Can be a competitive differentiator

•More sophisticated than keyword

Cons •Costly. Takes time to develop the complex models involved, and to process each textual item.

•Requires additional linguistics rule sets anytime the context of conversation shifts. Difficult to apply to extremely unstructured textual data sets like social media.


Technology Choices – Latent Semantic Analysis (LSA) & our favorite


Pros •Provides contextual understanding of conversations. Understands the difference between Coke (the drink) and coke (the drug)

•Minimizes mis-categorizations (false positives) and inappropriate rejections (false negatives)

•more relevant terms carry a higher weight creating more accurate analysis of what and how consumers are talking about areas, like category, brand, or product.

Cons •Can be more expensive to use and learn


Analyzing social media conversation is becoming increasingly more important as company’s begin to engage more with their customers. Having insights into where customers are talking, what they are saying and, if possible, audience details is critical for establishing an engagement strategy.

Whichever solution you ultimately select will influence your market strategy, how you interact with customers, customer service cycles, etc. So, having a better understanding of the quality of the data and how it is configured is a good foundation for a comprehensive social media strategy.

Good luck and thanks for reading!

Final Thoughts
