Challenges faced by Companies in Social Media Analytics
Social media has revolutionized the world & opening the new unexplored areas, which world has never seen earlier. Unethically defaming the products, services, organizations, celebrities, government policies, politicians, etc., has seen a drastic surge. Arab spring is a classic example of the shear strength of social media to uproot the decades of strong rule of dictatorship. However, the same logic is applied by extremists to motivate the innocent into wrongdoing. Social media analytics has hence become the powerful tool to bring to light these kinds of wrong doings. Social media has turned into a viral marketing platform to reach millions of customer in a short span of time. This poses another challenge to the companies in using advanced analytical tools to perform data mining & drawing meaningful business insights from unstructured data. Identifying each word used in the advertisement content contributes to it appearing in the social media when people search for their specific interests.
How will analytics solve these problems
Text Mining & Natural Language Processing are the social media analytical techniques, which are extensively used in drawing insights from unstructured data. Sentiment analysis is performed to identify the negative & positive things, which the world is speaking about various interests. Quick anomaly detection will help counter the outbreak of events, which cause severe harm. By making products smarter by avoiding features, which customer hate the most, organizations can become profitable. By analyzing the negative trend of brands, companies can avoid massive fiascos. By analyzing the hate comments, the radicalization of innocents can be avoided. By analyzing the data, support for political parties can be understood & corrective actions can be taken. By analyzing movie trends, sequels & prequels can be produced with better box office collections. By analyzing customer’s social media usage, better products/interests can be recommended & the list will go endlessly. In short, we all can live in a happy world with the right application of social media analytics.
Why Innodatatics?
Innodatatics, which is a startup company in analytics boasts of data science professionals & big data architects from top FT B-Schools & technology colleges. Also, we have a strong pool of Ph.D. professionals with thorough domain expertise, doing research on futuristic products & solutions. Word Clouds, Sentiment Analysis, Latent Dirichlet Allocation, Topic Extraction, Semantic Analysis, Network Analysis, NLP tools, Speech & Natural Processing, etc., are the text mining techniques in which Innodatatics has a strong control on. With the usage of open source tools, the price of implementing solutions would be extremely low & with world-class experts, the accuracy will be high & with the strong domain expertise business applicability of solutions is guaranteed.
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Business Problem Statement :
With the increase in digitization, the amount of accessibility to social media for a common persn has increased manifold. Advent of technology not only comes with the advantages, but also the disadvantages. Many people who have access to the internet do not restrain from giving to-the-point feedbacks, and are not at all shying away. But sometimes, these reviews/feedbacks are given only because of the unhealthy competition. At times, this is creating a lot of trouble to the genuine products/manufacturers, risking them to drop the plans of manufacturing those products. It also results in dropping of rating of those products.
Business Challenges :
- Increase in the complexity in deriving insights out of Opinionated Text
- Very hard to find the genuinity of the opinion on social media such as Twitter
- Complexity in reading unstructured data
- Relying on external surveys, consultants and other related groups
- Heavy cost is incurred in finding the sentiment associated with product
Business Solutions :
- Text Mining/Web mining performed on the twitter handle pertaining to the product to get accurate image of the brand/product
- Genuinity of the reviews are derived using the most advanced techniques involved in Natural Language Processing (NLP)
- Sentiment Analysis is performed at the highest level of accuracy to infer the perception associated with the Brand/Product
- Built classification model to increase the signal-to-noise ratio by classifying the tweets/comments on social media as very risky, risky, neutral, etc.
- Drawing meaningful business insights based on word clouds, semantic networks, cluster word clouds & dendrograms
Business Impact :
- Innovative features are incorporated into the product
- Scope for automation increased
- Improvisation in Brand Image due to proactive redressal of issues
- Around 10% improvement in Customer rating
- Improved customer retention rate
Business Problem Statement :
Living in the internet era & social media brings with it a flurry of new challenges. With the increase in rapid sharing of information (good, bad, ugly) about the companies & its products/services, the focus has seen a sudden surge. Negative messages are getting shared at a rapid pace – “Making a mountain out of a molehill”. These messages blowing out-of-proportion is leading to a lot of fiasco & shaming the brand image to such an extent that reversal of the negative mindset of customers is taking years together in-spite of everything being ethically correct.
Business Challenges :
- Negative vibes on social media were rising, thereby impacting the brand image of the organizations in spite of decades of strong presence
- Existence of too many online free–to–post forums where people can express, or debate about products, services, organizations, celebrities, etc.
- Identify the genuine concerns of the customers from the humongous junk data on social media
- Increase in risk of brand vulnerability because of increase in social media penetration
- Insignificant issues being blown out of proportion because of fast outreach of social media
Business Solutions :
- Live streaming of social media data based on Twitter hash tags & Twitter handles and performing sentiment analysis to identify negative words
- Capturing data from top 2 social media websites to identify anomalies by pattern recognition
- Built classification model to increase the signal-to-noise ratio by classifying the tweets/comments on social media as very risky, risky, neutral, etc.
- Drawing meaningful business insights based on word clouds, semantic networks, cluster word clouds & dendrograms
Business Impact :
- Increased customer satisfaction by 6%
- Reduction in number of times the product, service, organization, person was in media for negative reasons
- Improved brand image due to proactive redressal of issues
- Increased in customer retention rate
- Increased bottom-line & top-line
- Identification of issues beforehand lead to innovation
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Problem Statement
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Problem Statement
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Solutions
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Solutions
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Challenges
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Challenges
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Impact
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Impact
Business Problem Statement :
Living in the internet era & social media brings with it a flurry of new challenges. With the increase in rapid sharing of information (good, bad, ugly) about the companies & its products/services, the focus has seen a sudden surge. Negative messages are getting shared at a rapid pace – “Making a mountain out of a molehill”. These messages blowing out-of-proportion is leading to a lot of fiasco & shaming the brand image to such an extent that reversal of the negative mindset of customers is taking years together in-spite of everything being ethically correct.
Business Challenges :
- Negative vibes on social media were rising, thereby impacting the brand image of the organizations in spite of decades of strong presence
- Existence of too many online free–to–post forums where people can express, or debate about products, services, organizations, celebrities, etc.
- Identify the genuine concerns of the customers from the humongous junk data on social media
- Increase in risk of brand vulnerability because of increase in social media penetration
- Insignificant issues being blown out of proportion because of fast outreach of social media
Business Solutions :
- Live streaming of social media data based on Twitter hash tags & Twitter handles and performing sentiment analysis to identify negative words
- Capturing data from top 2 social media websites to identify anomalies by pattern recognition
- Built classification model to increase the signal-to-noise ratio by classifying the tweets/comments on social media as very risky, risky, neutral, etc.
- Drawing meaningful business insights based on word clouds, semantic networks, cluster word clouds & dendrograms
Business Impact :
- Increased customer satisfaction by 6%
- Reduction in number of times the product, service, organization, person was in media for negative reasons
- Improved brand image due to proactive redressal of issues
- Increased in customer retention rate
- Increased bottom-line & top-line
- Identification of issues beforehand lead to innovation
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Problem Statement
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Problem Statement
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Solutions
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Solutions
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Challenges
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Challenges
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Impact
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Business Problem Statement :
World is now experiencing highest internet penetration ever. Companies without online presence hardly survive. In this context, increasing online visibility, especially when netizens perform search on search engines is at its prime. There is fierce competition among companies to be viewed on the first page & being on the top of search results; this is because people hardly ever move to pages beyond first page to explore the results. Both top-line & bottom-line of companies are now greatly dependent on,
- a) How prominently your website appears in search results.
- b) What should be done to be on the first page?
- c) How should the first slot attained be sustained?
- d) How to keep abreast of the search engine algorithms, which change at a rapid pace?
There are many other questions, which the top executives across the globe are deliberating upon.
Business Challenges :
- Customers most often browse the websites, which appear on the first page of the search engine, leaving heavy competition for usage of relevant keywords, thereby triggering paid advertisements
- Decrease in the click-through rate making the ad irrelevant & impacting the quality score of ad, thereby not showing the ad at all
- Decrease in the transaction conversion rate leading to increased cost per click but customer not buying the product
- Lack of statistical way of identifying the keyword, which will increase the chances of lead conversion
Business Solutions :
- Developed statistical techniques to identify the keywords, which will increase the ad quality & thereby chances of clicking on the ad
- Statistically analyzing the ad quality & landing page quality & determining on which of these has to be strategically improved
- Calculating probability of conversion of leads who click on the ad by multiplying click-through rate with transaction conversion rate
- Building a prediction model to determine what parameters are relevant for increasing the conversion rate of the leads
Business Impact :
- Increased ranking of the advertisement on search engine
- Improvement in revenue due to lead conversions
- Increased profit margin after removing the cost per click expenses
- Increase in number of website visitors, which contributed to better branding of the organization
Business Problem Statement :
Too many movies are being directed without knowing about what really catches the viewers spellbound. With time, the budget spent on movie production is inflating beyond imagination & a flop at the box office would mean that the entire crew will be pushed out of race for atleast a few years. There are many scenarios where the entire production houses were shut down because of producing flop movies. Careers of the cast is at stake if they feature in a flop movie. Lack of unique, new, interesting storyline is always adding to the misery of the industry.
Business Challenges :
- Lack of different story lines for movie production due to vast number of movies being produced
- Only a small fraction of new movies break even, leading to huge losses
- Lack of insights on movie tastes due to ever changing demographics of the new population
- Only a small segment of film professionals are able to come up with blockbusters, on which the whole industry piggyback rides
Business Solutions :
- Used Arcs & Motions of natural language processing to understand the various emotions of the movies across the time series duration of the movie
- Analyzing the positive & negative emotional valence of all the blockbuster movies to understand about, which emotion at specific time periods will constitute to highest viewership
- Combining the social media reviews to understand on what aspects the movies are being liked, leading to a much superior story-line for sequel/prequel than the present version
Business Impact :
- Reduction of the routine boring story-lines thereby reducing losses
- Increasing the probability of success of movies by directly accommodating the opinions of the viewers
- Increasing the number of newer ideas for the film industry crew
- Increasing the opportunity for new crew to venture into film industry
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Challenges
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Problem Statement
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Solutions
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Challenges
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Impact
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Business Problem Statement :
Too many movies are being directed without knowing about what really catches the viewers spellbound. With time, the budget spent on movie production is inflating beyond imagination & a flop at the box office would mean that the entire crew will be pushed out of race for atleast a few years. There are many scenarios where the entire production houses were shut down because of producing flop movies. Careers of the cast is at stake if they feature in a flop movie. Lack of unique, new, interesting storyline is always adding to the misery of the industry.
Business Challenges :
- Lack of different story lines for movie production due to vast number of movies being produced
- Only a small fraction of new movies break even, leading to huge losses
- Lack of insights on movie tastes due to ever changing demographics of the new population
- Only a small segment of film professionals are able to come up with blockbusters, on which the whole industry piggyback rides
Business Solutions :
- Used Arcs & Motions of natural language processing to understand the various emotions of the movies across the time series duration of the movie
- Analyzing the positive & negative emotional valence of all the blockbuster movies to understand about, which emotion at specific time periods will constitute to highest viewership
- Combining the social media reviews to understand on what aspects the movies are being liked, leading to a much superior story-line for sequel/prequel than the present version
Business Impact :
- Reduction of the routine boring story-lines thereby reducing losses
- Increasing the probability of success of movies by directly accommodating the opinions of the viewers
- Increasing the number of newer ideas for the film industry crew
- Increasing the opportunity for new crew to venture into film industry
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Problem Statement
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Problem Statement
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Business Problem Statement :
Citizens are reporting to posting messages on social media & web to vent out the frustration or happiness associated with the daily activities going around. There is no transparency on how many promises were done by political party members at the time of election. Lack on clarity on the performance of the elected representatives leading to some sections misguiding the society with false claims.
Business Challenges :
- Dissatisfied & frustrated citizens resorting to social media to crib about the unhappiness
- Top leadership of Political parties are unable to identify the rogue elected representatives
- Unable to identify the good & bad of the different locations under the jurisdiction of elected representatives
- Unable to predict on whom should be given the party ticket based on popularity
Business Solutions :
- Scarped the web & social media to extract the data pertaining to the various political parties, elected representatives & performed Natural Language Processing to determine the issues which people are happy/unhappy about
- Used Support Vector Machine on the cleansed data to determine the anomaly of the positive/negative trend
- Predicting the popularity score to determine the success of the person winning elections
Business Impact :
- Quick review of performance of political parties
- Quick review of politicians’ performance to citizens & party leadership
- Great insight for news channels for exit poll analysis
- Increase citizen involvement & healthier society because of transparency
