52 BIG DATA ANALYTICS- A BOOST FOR BUSINESSES BASED ON SOCIAL MEDIA
Naman Shrivastava
Daly College of Business Management
Abstract - Nowadays, businesses adopt ever-increasing precision marketing efforts to remain competitive and to maintain or grow their margin of profit. As such, forecasting models havebeen widely applied in precision marketing to understand and fulfill customer needs andexpectations.Big Data Analytics (BDA) is being harnessed for predicting customer buying patterns and boosting sales. With the advancements in information technologies and improved computational efficiencies, big data analytics (BDA) has emergedasa means of arriving at more precise predictions that better reflectc us tomer needs.
The social media has been providing a platform for conducting business using the predictive big data analytics as an essential tool. The amount of data being generated every day by the millions of users is relentlessly analyzed and useful information is churned that can enable and boost businesses. The data from users of Facebook, Instagram and the search history of Google are a powerful indicator of choice and preference of millennial generation.
Keywords: Big Data, Facebook, Instagram, Google, Small Businesses.
1 INTRODUCTION
Social media today is swaying decisions of our daily lifestyle. The online content has today has taken so much of our mental space that even the smallest of decisions are being taken after consultation on the freely available information. The three major players in the social media game are Facebook, Instagram and Google.
FIGJAM (acronym), standing for "F*** I'm Good, Just Ask Me" is atrack by Australian band Butterfingers which refers to the above acronym.At the risk of sounding conceited I introduce a new full form “Facebook, Instagram, Google- Just Ask Me”. This is the truth of today that every user uses at least one of these platforms for any query that cannot be resolved locally.
With 2.6 billion monthly users and approximately 1.73 billion daily active users across the globe Facebook is the largest congregation of people at a single platform. India has the highest number of Facebook users at a whopping 260 million.
Instagram follows with 1 billion monthly and 500 million daily active users.
Instagram is gaining momentum and is on way to become at par with Facebook.
However, the interesting fact is that both these platforms cover almost 65.42% of the internet users.
The prevalent advantage of this user base is being taken not just by big corporations but also by small businesses that have found this platform an alluring one. The massive user base combined with the fact that an average user spends 28 minutes on Instagram and 26 minutes on Facebook make these and ideal place for generating business. The following table enlists various ways the businesses are using the features of these two social media platforms to their advantage.
Feature Platform Exposure Time of
Audience
Posts Facebook, Instagram ∞
Stories Facebook, Instagram 24 hrs.
Reels Instagram 30 sec per view
IGTV Instagram 60 min
Live Facebook, Instagram 4 hrs.
Marketplace Facebook ∞
Table 1
53 When compared to the small exposure of 4-5 seconds on the traditional media platforms combined with the fact that the exposure is not traceable the social media emerges as a clear winner in the business generation game.
2 DATA FOR NEW BUSINESSES
The Big data can be defined as 5V data that features the following-
High Volume
High Velocity
High Variety
High Value
High Veracity
Volume refers to the extensive size of data collected from multiple sources over an extended period of time. Velocity refers to the speed of data collection, reliability of data transferring, efficiency of data storage and excavation speed of discovering useful knowledge as relate to decision-making models.
Variety refers to generating varied typesof data from diverse sources such as the Internet of Things (IoT), mobile devices, and social networks. Value refers to the nature of the data that must be discovered to support decision-making. Veracity refers to the quality of data, which must be accurate and trustworthy, with the knowledge that uncertainty and unreliability may exist in many data sources.
Figure 1 Various data gathering points on social media platforms
The key application of BDA is to provide accurate forecasting, especially demand forecasting with the aim to predict accurate buying patterns and generate convertible leads. The data points are numerous as cited above and thus this research focuses on the data from social networks. The data is culled from various parameters and the complex algorithms then predict the possible purchase opportunities by in turn predicting what next to show to the user. The features listed in the above table attract a multitude of users and the views, likes, number of replays, hashtags and the comments can be analyzed for predicting what to do next.
3 APPROACHES AND TOOLS FOR DATA ANALYSIS
The three very common analysis tools applied in the prediction of demand are Clustering Analysis, K-nearest-neighbor (KNN) and Artificial Neural Networks. Clustering analysis is a data analysis approach that partitions a group of data objects intosubgroups based on their similarities. Several applications of clustering analysis have beenreported in business
Social Media Big
Data
Posts
1. Likes 2. Comments 3. Shares
Stories
1. Views 2. Replays 3. Swipe Up
Reels
1. Views 2. Replays 3. Profile Visits
IGTV
1. Full Views 2. Profile Visits 3. Replays
Live
1. Number of people joining 2. Comments
Marketplace
1. Types of products sold
2. Number of visits 3. Comments and queries
54 analytics, pattern recognition, and web development. Extraction of similar behavior from historical data leads to recognition of customer clustersor segments. The clustering enhances the accuracy of SC demand forecasting as the predictionsare established for each segment comprised of similar customers.
KNN is a method of classification that has been widely used for pattern recognition.KNN algorithm identifies the similarity of a given object to the surrounding objects (called tuples) by generating a similarity index. These tuples are described by n attributes. Thus, each tuple corresponds to a point in an n-dimensional space. The KNN algorithmsearches for k tuples that are closest to a given tuple.
In artificial neural networks, a set of neurons (input/output units) are connected to oneanother in different layers in order to establish mapping of the inputs to outputs by findingthe underlying correlations between them. In doing so, each unit (neuron) will correspond to a weight, that is tuned through a training step. At the end, a weighted network with minimumnumber of neurons, that could map the inputs to outputs with a minimum fitting error (deviation), is identified.
As these algorithms are data hungry and need a huge data to predict the future demand patterns the social media data that is regularly gathered serves a feed.
4 FIGJAM
The quintessential millennials are living in an age where virtual seems real and the boundaries between real and online world are diminishing rapidly. The age that lives for instant gratification by fulfillment of demand needs the platforms like Facebook, Instagram and Google—The F,I and G and the Just Ask Me.The online customer does a lot of online research before placing an order and needs everything at his disposal asap. The reviews are checked, options explored, celebrity status verified, the influencer check and then finally the order is received by the companies.
The use of tools of these platforms like Instagram Live and reels is made to the optimum by the millennials. They eagerly wait for notifications that their star is going live and join the live video. The star is paid for by the company for endorsing the product in their video and within a span of minutes to hours the reach of that brand extends to 3-4 lakh people.
Facebook market place has become a hub for buying and selling products from all walks of life. Starting from a normal T-shirt to expensive saree to tenants and whole properties everything is being sold there. The creation of specific shopping groups and the creator being the moderator it is possible to get people of parallel interests.
Google is the synonym of find for the modern kids. Google it has become a phrase of choice when in doubt. The algorithm is robust and can find underlying connections between people, events and their habits. The location identifier can predict where you will head next and gives choices based on your past preferences.
It is as if these companies are saying to the masses Just ask me.
4.1 Applications for Small Businesses
As deliberated above the applications of this data to the new businesses are plentiful. The new businesses have a major challenge of promotion today and making their presence felt drains them of financials. The cost sustained in the traditional media marketing like Newspaper, magazine, hoarding and bill boards is immense. The upside being that this media is present in public and has many eyeballs still gets beaten by the fact that targeted marketing done after diligent effort on Big Data creates better leads and the conversion of potential viewer to a customer is much higher.
Combined with the fact that almost 77% of the urban dwellers are on at least on e of these platforms makes this a preferred choice for new businesses to promote and generate new customers.
The cost incurred in selling an ad to Instagram is Rs.80 per day or Rs.400 per week.
If an ad campaign is launched on a Friday; the weekend views can easily bypass 6-7k for a startup. An endorsement by a celebrity or an influencer can make the reach manyfold. The businesses can leverage this reach to boost their presence and also generate leads. The
55 meta data presented along with makes it easy for the companies to understand which product is being viewed and liked maximum. Even the areas where the products are being liked can be mapped and the ads can be directed in that area.
The power of social media platforms is easily available and for the business to harness. This provides startup companies and home run businesses a way to make a mark and showcase the art, craft, product and talent even from the hitherto areas.
5 CONCLUSION
The applications are immense and the scope of research on FIGJAM power is virtually open for taking. The market penetration of these apps is still in the growing phase and will gradually take onto the brick-and-mortar markets. That impact will be interesting to watch and will further shape the future the way businesses are conducted.
REFERENCES
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http://creativecommons.org/licenses/by-nc-nd/3.0/.
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