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How to leverage Social Media Analytics for your business?

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Introduction

Conventional media, such as television, radio or newspapers transmits information only in one direction. Users can consume the information which the media offers, but they have very little or no ability to share their own views on the subject.

Now-a-days, digital mediums has made it possible to have a two-way form of communication that allows individuals to interact with the information being transmitted. This is known as Social media which encompasses a wide variety of online content, from social networking sites like Facebook, Twitter, YouTube etc to interactive encyclopedias.

For example, social video sites like YouTube allow users to share video content and interact through video comments etc. The two-way communication through social media has created opportunities for lots of organization to communicate with their end consumers directly.

 

Table of Content

  1. What is Social Media Analytics?
  2. How are different companies using Social Media Analytics?
  3. What are the benefits derived from Social Media Analytics?
  4. How can Social Media be used for Lead Generation?
  5. Tonality / Sentiment Analysis
  6. Lead Generation
  7. Tools used for Social Media Analytics

 

1. What is Social Media Analytics?

As the name suggests, Social media analytics involves analyzing data on social media to take business decisions. Data is usually gathered from blogs, forums and social media websites (like Facebook, Twitter, Youtube etc.). It is then analyzed by converting the qualitative data to quantitative data with the help of different text mining and NLP techniques.

The most common use of social media analytics is to mine customer sentiment in order to support marketing and customer service activities. Typical Social Media Analytics objectives include:

  • Amplify the business presence
  • Running campaign through Social Media
  • Reducing customer service costs with proper Social Media monitoring process
  • Getting feedback on products and services
  • Track public opinion for a particular product or business division.

 

2. How are different companies using Social media analytics?

Most of the organizations today have dedicated social media practice team to help brands expand on and off the web.

Now-a-days, consumer goods manufacturers, personal technology makers and companies that rely heavily on word-of-mouth referrals to generate business find social media analysis tools crucial to their business strategies.

Social media provides retailers with a wealth of information about their consumers that they might never get through traditional media. Since social media creates a two-way interaction between the brand and the individual, retailers can quickly get an understanding of which of their products are favored by buyers, what features of the brand customers can relate with them etc.

Things get really useful when marrying social media data with internal data of the organization. Displaying custom results for example, for one of the online bookstores based on what a visitor had tweeted about that day might push up sales. Perhaps a large percentage of their Facebook followers under the age of 30 are suddenly searching for particular things on your website, raising the possibility of a targeted campaign.

Following are the main use of Social media by different business entities:

  • Flame detection (bad rants)
  • New product perception
  • Brand perception
  • Reputation management
  • Trend Spotting
  • Analyzing virality of the content
  • Effectiveness measurement of Social campaigns
  • Lead Generation
  • Social listening for Government

 

3. What are the benefits derived from social media analytics?

Social media listening / monitoring process helps in identifying real-time conversations happening on social media about a product, or a brand so you can respond in a timely manner. Since social media has empowered customers to speak about their experience about a product or brand, it is essential for businesses to assess what is going on in the inter webs by carving out a time to listen for brand/product-related conversations. Here are few benefits:

  • Any organization with proper social media monitoring process, can use Social Media as awareness generation and amplification tool by sharing knowledge or expertise – where and when needed and if appropriate.
  • Find out what consumers are talking about in the target market. Spot trends, themes / topics and discover pain points.
  • Track sentiment regarding own and competitor brands, or product. Identify the tone of voice of what others are saying –positive, negative or Neutral etc.
  • Discover spaces where your customers and your competitors are hanging out. Where is the discussion happening? Which social media platform? What blog? What forum? What groups?
  • Find key influencers in your niche market through Network and Author level analysis
  • Find out if anyone from the company may be participating in discussions and is posting information without company’s approval.
  • Identify old and new competitors and find out what they are doing using competitive landscape analysis. Who’s talking to them? What terms do they use?
  • Identify areas in the business process that may need to be developed, or needs improvement.
  • Recruit/hire right people.
  • Understand the path leads to “customer loyalty”.
  • Build a community of brand ambassadors.
  • Determine areas that could be a “threat” to the company.
  • Evaluate the effectiveness of different marketing campaigns on Social Media.
  • Improve product features that the consumers are talking about.
  • Find sales opportunities (lead generation mainly useful for high-cost products).
  • Check what type of content is performing well

In this article, I will focus on how Social media can be deployed for lead generation. Following are the details.

 

4. How can Social media be used for lead generation?

With the introduction of social media, humongous amount of unstructured data is produced every second on the internet. This data contains very relevant & useful information about brands, competitors, Industry, consumers’ perception about different product, brands, services, etc.

Now-a-days, social media is the connection between brands and consumers. However, most marketers think of social media as a brand amplification or awareness generation tool (and not sales). But social media is an integral part of today’s sales process which helps to know the prospects and establishing relationships.

For high-cost product marketers (for example, very high-cost modular kitchens), it is all about lead generation. The sales team is more interested in good and high-quality leads than anything else. The extensive reach of social media grants it potential as one of the most powerful lead generation tools, as social media allows sales people to see what prospects are saying about their brand and competitors. But the enormous size and dis-organized nature of the data makes it very cumbersome to generate actionable insights manually. Luckily, we can overcome this situation easily with the help of Analytics.

Social analytics taps and analyzes consumers’ opinions converting them into insights, which helps businesses & marketers in identifying potential leads, areas of customer satisfaction or any customer grievance for a product etc.

Solution Approach


Keyword Generation: To start with one needs primary inputs about the category to get idea about different keywords to be used for data pulling. For example, for premium Modular Kitchen segments we need information like number and name of the brands, features in different brands, prevailing models’ name etc. One also needs to create a list of noise words so that it is easier to remove the irrelevant conversation. For example, for premium Modular Kitchen, if we use only “Kitchen”, it can capture post like “@XXX – all competition! Brand-YYY @Kitchen_Art #TheLifesWay” which is irrelevant for the context of Modular Kitchen.

Data Extraction & Data Cleaning: Once the keyword list is finalized, one needs to formulate the query in proper manner to capture right content. To avoid the problem mentioned in previous example, we need to mention the query in proper order comprising of keywords and noise words (for example Kitchen and not competition or Modular Kitchen & Brand XXX Or Brand YYY etc.).

Also, one needs to select the right sources. For example, for premium Modular Kitchen category, forum like “Houzz.com”, “planned5d.com”might be more helpful than “Generic blogs” etc.

Converting Qualitative data to Quantitative data: Next, we need to convert qualitative data to quantitative data using text mining as well as Natural Language Processing (NLP) based techniques. Below are the examples of converting Qualitative data to Quantitative data:


The taxonomy needs to be fine-tuned based on test & learn approach. For example, the taxonomy for the purchase intent for premium Modular Kitchen looks like:


Purchase Intent & Basic Listening Taxonomy Creation & Fine Tuning: 
To analyze the purchase intent, one needs to create an initial taxonomy (the science concerned with classification of texts) based on some secondary researchers or sample data scan.


5. Tonality / Sentiment Analysis

Analyze the tonality to understand consumer expectations as well as pain points. Since Social Media data is more inclined towards Neutral content, predictive models alone will not suffice as a classification technique to classify “Positive”, “Negative” and “Neutral” tonality.

An ensemble approach comprising of predictive modeling along with custom classification rules based on Naïve Bayes Classifier would help to achieve higher accuracy (>80%).

Please find below the description of tonality calculation process:

 

6. Lead Generation

Once the Purchase Intent & tonality analysis are over, we can classify the content as:

  • High Probability Lead
  • Medium Probability Lead
  • Low Probability Lead

We can figure out the Author Name corresponds to High Probability Lead & “Medium Probability Lead” and analyze their needs & pain areas based on the conversation and accordingly design the communication strategy to target them.

 

Operating Model of the Solution

Every time, there is new data, the data will be automatically classified based on existing rules. It is advisable to validate the rules in every three months.

 

7. What are the tools used for social media analytics?

There are a variety of social media analytics tools to help marketing experts do all the analysis. Few of them are Radian6, Sysomos, Poly Analyst (Megaputer), HootSuite, etc.  They can be used for multiple channels, while others focus on particular networks such as Twitter/ Facebook etc. All tools are useful for converting the qualitative data into the quantitative format as well as social media monitoring work.

There are also statistical tools like R, SPSS Text Miner, SPSS Modeler and SAS which helps in different advanced analytical work like predictive modeling, Naive Bayes Classifier is used to boost-up the accuracy of Sentiment / tonality analysis.

 

End Notes

With the help of Social Media Analytics, organizations can identify social leads, influencers and advocates on a daily basis. The potential leads can be segregated into different segments based on the conversation themes and tonality. This “Persona Analysis” helps to understand the demographics and psychographics of the prospects and influencers.

Social Media Analytics can capture profiles of prospects based on the well-defined taxonomy. Generally, the social media experts / analysts verify the leads and sort them into different segments as per business requirement and create personalized communication strategies.

Social media is a powerful way to grow your followers, gain trust, and increase overall revenue by acquiring more customers. Using Social Media Analytics, one can definitely increase the ability to grow to the maximum potential through social networks.

 

About The Author

Anjanita is a dynamic results oriented professional with blend of Analytics Consulting, Business Intelligence and project management experience comprising of 11 years from project scoping to entire execution, in several successful shared services organizations in India in technology, CPG & retail sector.

 

 

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2 Comments

  • Tim says:

    Hello Anjanita,
    nice article. You mentioned to create 100 different variants of the concept for data mining. How much traffic would it take to make it meaningful? What should be the minimum requirements (visibility, traffic, follower) of an company to start a analysis like this?

    Thank you in advance,
    Tim

  • scsraj says:

    NIce one, well articulated.

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