Programmatic Digital Marketing

     Programmatic Digital Marketing is an advanced and automated digital marketing strategy designed to replace human negotiations with machine learning, which relies on automated and real-time bidding processes that allow companies to reach their target market with hyper-targeted and effective ads by advertising targeted customers in specific contexts. Businesses can reach the target audience who is more likely to be interested in their products or services with programmatic advertising through real-time auctions. Detecting, analysing, and reaching the optimized audience through behaviour-based advertising leads businesses to achieve a higher return on investment and expand their customer base. In 2021, 88% of display marketing in the United States is expected to transform programmatic advertising (Rask, 2021).

How Programmatic Digital Marketing Works?

 

The process starts when someone clicks on a page that is modified for programmatic marketing. After an auction among the advertisers is being put by the marketplace for an open advertising place, the advertiser who bids more for that advertising spot gains the right to display its ads. That allows the advertiser to increase sales and conversions since customers see that ad and make purchases. Although it may seem complex, it is an easy and fast process that takes only milliseconds which means the winner of the advertisement auction can be determined even before the user’s page uploads. Besides, there are several points that need to be considered while embracing programmatic digital marketing:

 

·      Companies should have the understanding and knowledge of not only consumer data but also customer behaviour to achieve successful programmatic advertising.

·      Companies should rely on not both website analytics and survey data that reflects more natural indications while designing programmatic work.

·      Companies should use insights to identify the most effective channels and devices.

·      Companies should use existing customer data to deliver hyper-personalized messages.

·      Companies should track and test the effectiveness of advertisement to make sure where to focus on, considering business objectives and brand metrics.

 

Benefits of Programmatic Digital Marketing 

    Programmatic digital marketing allows companies to focus more on their target market and audience at the right time and in proper context. Programmatic digital marketing enables businesses to save on costs since it helps set the frequency, time, and price of ads and requires payment for only relevant impressions. In addition, it helps companies keep track of their advertisement budget while achieving their set goals since it allows them to have control over ads by providing more flexible options. For example, a telecom company in Qatar, Ooredoo achieved to reduce the acquisition cost to reach their target audience 88% by using programmatic advertising, compared to traditional channels (Fayez, 2016). Lastly, it enables companies to provide a better user experience by promoting tailored advertisements and advanced targeting. There numerous brands that achieved building successful ads by embracing programmatic campaigns based on consumer data, such as O2, The Economist, Turner Sports, Audi, ScS, and Amanda Foundation (Keane, 2018). Regardless of the industry type, sector, or size of the company, programmatic digital marketing can be embraced to increase sales, conversions or drive awareness.

Buket Bostanci

Keywords: programmatic digital marketing, programmatic advertising, target market, target audience, personalised advertisement

References & Sources

 

Al Fayez, N., 2016. What is Programmatic and Why is Everyone Talking about it? [online] Think with Google. Available at: https://www.thinkwithgoogle.com/intl/en-145/marketing-strategies/programmatic/what-programmatic-and-why-everyone-talking-about-it/ [Accessed 13 April 2021].

 

Rask, O., 2021. What is Programmatic Advertising? The Must-Have 2021 Guide. [online] The Match2One Blog. Available at: https://www.match2one.com/blog/what-is-programmatic-advertising/ [Accessed 13 April 2021].

 

Keane, L., 2018. Programmatic Ad Buying: 6 Examples of Brands Getting it Right. [online] GWI. Available at: https://blog.globalwebindex.com/marketing/programmatic-ad-buying/ [Accessed 13 April 2021].

Unleash the power of Business Intelligence for your company

The terms business insight and business intelligence are frequently utilized reciprocally. The term business intelligence means inspecting information to discover patterns in them which leads to arriving at certain facts.  At the point when utilized together, business intelligence and business analytics are two sides of a coin and possess more extensive importance and incorporates each part of collecting, inspecting, and interpreting data and insights which can be even visualization of data. (Oracle, 2021)

BI Techniques for 2021

BI tools perform data analysis and make reports, rundowns, dashboards, guides, diagrams, and graphs to give clients definite knowledge about the idea of the business.

Data Analytics

Data Analytics is an important domain in business intelligence that every small and medium business should use in their operations in 2021, this method includes the investigation of raw data to extract significant patterns and insights.

This is a mainstream BI strategy since it allows organizations to profoundly comprehend their business data and drive extreme worth with information-driven choices, it can greatly help business managers from making wild choices in making important decisions.(IDA Ireland 2021) For example, how DigiX Media is utilizing data analytics to create customized marketing budgets, strategies, improve the client experience, and for quality affirmation purposes.

Data Mining

Data mining is an important subset of data science and an integral part of business intelligence. It is a method for finding insights in very large datasets and frequently consolidates data set frameworks, insights, and AI to discover patterns.

Data Visualization

Visualization is an important part of BI where dashboards of data visualization can be created using popular softwares' like Tableau, Power BI, etc.

SAP, as the most popular BI tool for large businesses. 

Fig. Using SAP BI tool for creating Business Objectives 

It is the most popular application used at the enterprise level for the purpose of client/server systems. SAP facilitates data visualization, data analytics, creating drill-down reports reporting, and many other integrations with Office support.

SAP is created to help all levels to managements, developers, clients, and other departments including sales. The reason for the popularity of SAP is that it provides tons of functionalities.(SAP, 2021)

Tableau, the simplest Business Intelligence software for everyone

Fig. Using Tableau to find customer segments

In simple words, won't be it great to easily find out - 

• How to increase profit
• How customers are behaving
• How competitors are growing
• Is the performance good enough
• Predicting outcomes
• Find out issues and problems

Tableau posses a simple interface for anyone with data analytics knowledge to use it for business intelligence purpose finding the hidden insights from data and using  it for managerial decision making.

The availability of enough features in data is also a critical factor in deciding the dataset is good for usage with a BI software. (Tableau.com, 2021) 

-  Spoorthi Joshi S

REFERENCES

Oracle 2021 | How business intelligence can keep your organization in the know | https://www.oracle.com/ie/what-is-business-intelligence.html (Accessed on 29 March 2021)

IDA Ireland 2021|  As market leader in enterprise application software, SAP (NYSE: SAP) helps companies of all sizes and industries run better |  https://www.idaireland.com/how-we-help/case-studies/sap (Accessed on 29 March 2021)

Tableau 2021 | Powerful analytics anyone can use | https://www.tableau.com/resource/business-intelligence  (Accessed on 29 March 2021)

How the Loss of Third-Party Cookies Will Affect the Future of Digital Marketing?

The Background: What Has Happened Recently?

As the privacy concerns and controls about the protection of personal data have been raising since few years, many tech giants such as Facebook and Twitter started to take action to improve their security systems and be clearer about how they keep and use the data of the users. Moreover, the recent legislations like General Data Protection Regulation (GDPR) aims to protect and encourage customers to have more control on their personal data, and to ensure transparency on the usage of customer information by companies. As a result, these protective regulations have also affected the cookie policies and lead to a crumbling of third-party cookies. This trend began with disapproval of third-party cookies by well-known browsers Firefox and Safari and continued with Apple’s decision on the apps that they won’t be holding a device identity unless the related customer consent to that (Remekie, 2021). Lastly, third-party cookies which are also identified as tracking cookies, have been blocked by Chrome, Google’s leading browser. Besides, Google has declared that the company will not publish a substitute for third-party cookies, and in March 2021, it has announced the first-party data will be the new substitution for third-party cookies (Tracking Cookies are Dead: What Marketers Can Do About It, 2021).

After mentioning the terms “first-party” and “third-party”, let’s take a deep dive into the purpose of third-party cookies in general, and then go deep into the future impacts of their loss in terms of digital marketing.

What Does the Loss of Third-Party Cookie Mean?

Unlike the functional first-party cookies which help website owners to collect information; third-party cookies, -also known as marketing cookies- are formed by domains, not by the website. These cookies are used for marketing purposes, mostly for online advertising, by allowing advertisers to track the user every time they visit a website. For example, when a user visits a news website, a first-party cookie is created and held by the website. Then, when the website benefits from ads made via different websites, third-party cookies will be created and these will be held in the computer of a user rather than a website itself (1 et al., 2021). If we have a look at the pros and cons of third-party cookies, it is obvious that they can be beneficial for advertisers and practicable for users by ensuring them targeted ads in the light of “personalisation”. But, on the other hand, visitors have also struggled with privacy concerns as they can’t control which companies are gathering and using their personal data. Even being protected by GDPR’s cookie consent, users wouldn’t able to see for which organisation their data will be using after they have consented to related website (2021).

As cookie-based data is considered as an important input for digital marketing campaigns, basically, demise of third-party cookies means less data to be processed. Therefore, the new conditions lead to marketers and advertisers to find less costly solutions, and to be more creative when it’s come to design a digital marketing campaign. Agencies and brands may be dealing with offering non-targeted ads to their customers by having less clear consumer behaviours. Consumers will be affected positively in terms of privacy issues, but they might be exposed to more irrelevant ads (Juneau, 2021). Publishers will also be affected by the loss the third-party cookies as they rely on cookie-based data. The study conducted by Google among top global 500 publishers, shows that disabling access to third-party cookies decreased the average revenue of publishers by 52% (2021). According to Cookiepedia, The Daily Mail holds 19,136 third-party cookies on its site (Know your cookies: A guide to internet ad trackers - Digiday, 2021).

Source: https://digiday.com/media/know-cookies-guide-internet-ad-trackers/

What Happens Next? What Marketers Need to Do?

• Marketers will be relying on first-party data, high quality data or real-time data.

• Personalisation is still possible considering the value of first-party data.

• Contextual advertising/targeting will be replacing the cookies.

• People-based marketing/advertising will be targeting customer’s real-time behavioural data.

• Advertising might be more human engaged rather than automated systems (Tracking Cookies are Dead: What Marketers Can Do About It, 2021).

Keywords: Third-party cookies, First-party cookies, First-party data, Advertising, Privacy, GDPR

Ilgin Damla Omay

References and Sources

1, C., 2, C., Scanner, F., Function, T., Base, K., Subscription, M., Edition, F., Now, B., Subscription, M., Us, A., Us, C., Demo, R., Quote, R., Consent, C., Rights, D., Consent, M., Management, D., Support, Q., Tools, F., Scanner, W., Button, C., CMP, I., Developers, F., Publishers, F., Agencies, F., Calculator, R., Directory, P., Partners, R., Partners, M., TCF, I., DPC, I., 220, N., PDPA, T., Library, R., Base, K., Plugins, I., Hub, D., Us, A., Us, C., Demo, R., Quote, R., Plans, C. and Edition, F., 2021. What is a Third-Party Cookie? | Knowledge | CookiePro. [online] CookiePro. Available at: https://www.cookiepro.com/knowledge/what-is-a-third-party-cookie/ [Accessed 21 March 2021].

Digiday. 2021. Know your cookies: A guide to internet ad trackers - Digiday. [online] Available at: https://digiday.com/media/know-cookies-guide-internet-ad-trackers/ [Accessed 21 March 2021].

Invoca.com. 2021. Tracking Cookies are Dead: What Marketers Can Do About It. [online] Available at: https://www.invoca.com/blog/tracking-cookies-are-dead-what-marketers-can-do-about-it [Accessed 21 March 2021].

Juneau, T., 2021. Council Post: Digital Marketing In A Cookie-Less Internet. [online] Forbes. Available at: https://www.forbes.com/sites/forbesagencycouncil/2020/05/18/digital-marketing-in-a-cookie-less-internet/?sh=13d751121e2d [Accessed 21 March 2021].

Remekie, S., 2021. What Happens to Marketing When the Cookie Disappears?. [online] CMSWire.com. Available at: https://www.cmswire.com/digital-marketing/the-demise-of-the-cookie-and-the-rise-of-first-party-data/ [Accessed 21 March 2021].

Services.google.com. 2021. [online] Available at: https://services.google.com/fh/files/misc/disabling_third-party_cookies_publisher_revenue.pdf [Accessed 21 March 2021].

www2.deloitte.com. 2021. [online] Available at: https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/consultancy/deloitte-uk-cookie-less-marketing.pdf [Accessed 21 March 2021].

Using Cookies to assess digital marketing performance

 What is a cookie?

Before we start it is important to know what exactly the cookies are and how it helps in the field of digital marketing. So, cookies are a piece of code that lives on your web browser and stores information in the user’s web browser to identify and enhance your experience online. This technology is utilized to work with different capacities which include keeping track of stateful data such as items added into the shopping cart, keeping data from applications that have already been filled out (for autocomplete function), Account- protected servers receive the user’s account information and log-in status through authentication cookies. (Kaspersky 2021)

With an increasing understanding of privacy concerns and laws like the EU's General Data Protection Regulation (GDPR) and e-privacy, there is a greater need to educate consumers about what cookie files are, what information they should hold, and what types of cookies are available. (Clearcode 2021)

Now we will see the types of cookies. Essentially cookies are divided into first-party cookies and third-party cookies from a technological standpoint. However, all store the same data and can execute the same task. But what makes them unique is how websites build and use them.

 First party cookies

They are specifically stored by the domain (website) you are visiting. They enable website owners to collect analytics data, remember language preferences, and perform other valuable functions that aid in the delivery of a positive user experience.

Third-party cookies 

As mentioned even they perform the same function as cookies do but third-party cookies offer information that lets advertisers identify their audiences' taste and expectations beyond their interactions with the brand.  Exposing trends and other user data can be used to help influence potential marketing strategies. To view related advertisements, they store information across web domains and across interactions, hopping from browsers to social media applications and beyond. They are created and saved in a user’s web browser to monitor their online activity through various websites. (Adroll 2021)

Cookies in Digital marketing 

Now let's see how cookies are used in facilitating your digital marketing function. Considering Targeted digital marketing, web cookies are used in delivering many forms of personalized digital ads. They save user data and behavior records, allowing advertisement providers to reach a specific customer audience based on factors such as gender, age, interests, location, actions on websites, and actions on search engines or social media.

Cookies may be a tiny aspect but it plays a crucial role in promoting targeted ads on social media platforms. Without cookies, accounts could not be generated, downloaded, or maintained; without the user profile, consumer data would be unavailable; and without the data, targeted ads would be impossible. To begin thinking about social media accounts in this way – as freely surrendered caches of user data – is to obtain an understanding of how Facebook has created one of the world's most powerful targeting empires. It's even a little unsettling.(Targetinternet 2021)

 Using third-party cookies to assess marketing performance.

 Well, you have already seen third-party cookies in motion if you've spent some time on the internet. It is quite often that you have been to an online retailer and looked at a few items only to find advertisements for the same items on entirely different websites? Third-party cookies operate exactly in the same way. they observe your actions outside of the brand's ecosystem and then use it to provide personalized marketing to help you move from surfing to a paying client. In the long run, the information gathered from third-party cookies is used to create accurate consumer profiles.

Consumers are becoming more aware of how advertisers use their personal information as they do more of their business online. As a result, there is a growing trend for an online marketing future that is more privacy-friendly. Google's decision this year isn't the first time browser creators have restricted the use of third-party cookies; Safari did so in 2014, and Mozilla's Firefox in 2019.( Targetinternet 2021)

 

 Viewing the web cookies can be an interesting experience. Each one is intended to support a specific purpose while also adding a subtle layer of color to your online experience. We get the feeling that, while cookies aren't great, we can't imagine life without them.

- Spoorthi Joshi S

 References

 AdRoll. 2021 |MEGAN PRATT |Third- party cookies and digital marketing: what’s next? https://www.adroll.com/blog/marketing/third-party-cookies-and-digital-marketing-whats-next ( Accessed on 21^st march 2021)

2.      Targetinternet 2021 | The digital marketing guide to web cookies | target market| https://www.targetinternet.com/digital-marketing-guide-to-cookies (accessed on 21st march 2021)

3.      Clearcode 2021| Michal Wlosik, Michael Sweeney| First party and third- party cookies: what’s the difference? https://clearcode.cc/blog/difference-between-first-party-third-party-cookies/#cookie-types ( Accessed on 20^th march 2021)

4.      Kaspersky 2021| what are cookies? https://www.kaspersky.com/resource-center/definitions/cookies ( Accessed on 20^th march 2021)

 

Data structures in digital marketing and making it useful for your business : Segmentation

Data structure is a very common word heard in this big data world, so what is Data Structure? Famous scientists Peter Wegner and Edwin D.Reilly defined data structure better way which is more precise in their publication Encyclopedia of Computer Science as it is a collection of data values and the relationships between those data values and the functions or operations that can be applied to the data.

Talking about the data structure domain to easily understand we can create 3 categories 

The format: It is mainly the process of arranging data based on its structure or type into different categories, It can be Arrays, Stack, Queues, Linked Lists, Trees, Graphs, Hash Tables, etc.

Storage: It included storing, and the management of data. Moving a business to the cloud takes out the expense of equipment and support. Eliminating these capital consumptions and the related help compensations can convert into huge expense reserve funds. Your cloud storage provider will maintain, manage and support your solution. This frees up employees who would otherwise cover the tasks necessary for keeping your data safe and your server(s) up and running.

Efficiency: Efficiency is a pivotal necessity in light of the fact that effective information structures defeat their own purpose totally.

Segmentation can be treated as another side of the coin when taken in the case of digital marketing with data structures. The ordinary utilization of marketing segmentation is to partition data into several groups with similarities and differentiate marketing strategies for them. Each organization has a set of Ideal customers, the customers who have an affection for the service a company offers. If we envision the entire clients are that way. Productive, exceptional, the best client we could ever want. Regardless of whether we could get a couple of a greater amount of these, it could have a significant effect.

                                               Pillars-of-segmentation

Data structures are fundamental for most developers since they're the foundation of how all products work. Data is everywhere, and the capacity to coordinate the data in an effective way is definitely essential for building solutions and quality programming.

Collecting and using client information is an exceptionally significant step for any company. Most advertisers will concur that we are exactly toward the start of what is actually possible. The innovation is to utilize client information and predictive analytics considerably with a proper understanding of data structures and knowledge of segmentation.

The most grounded sign of the future of structured data comes from Google itself. where they developed their own structured data testing tools. An example is that how google's algorithm gets updated frequently to filter most suited search results for a keyword. 

- Spoorthi Joshi S

REFERENCES

[1] Smart Insights 2019 Get your data structure in shape for your next step in customer segmentation. Available at https://www.smartinsights.com/digital-marketing-strategy/customer-segmentation-targeting/get-your-data-structure-in-shape-for-your-next-step-in-customer-segmentation/ [Accessed 3rd March 2021]

[2] The Coder Pedia 2020 Type of Data Structures (Complete Overview) Available at https://www.thecoderpedia.com/blog/type-of-data-structures/ [Accessed 3rd March 2021]

[3] Digital Marketing Institute The Importance of Structured Data in SEO 2017 Available at https://digitalmarketinginstitute.com/blog/the-importance-of-structured-data-in-seo [Accessed 3rd March 2021]

What are the Benefits of Volume-Data Storage and How it is Beneficial to Digital Marketers?

Data storage is a medium to store a huge amount of Information. Any electronic document can be store in less space than any paper document. This information converts into bits and can be stored in the electric circuit. The storage volume can be removable hard disk but it doesn’t remove physically from computer or storage system. This Volume data storage is flexible and it can contract or expand. In it, files and documents can record digitally and saved in a storage system for future use. If we talk about a business point of view data is the most important asset. So in today’s digital world, the best method of volume data storage is websites, blogs, social media sites. Making a high-quality website for storing data is a good option so that it can include information about things that customers find relevant and interesting. With the help of data storage, it’s easy to get the contact information of the customers. Digital marketers have to deal with a large amount of data on different sources like social media, websites and that collected data helps them to do marketing digitally in the digital world. Not only this there are many other data management or data storage platforms where digital marketing experts can store their data and use it whenever they needed. Here if we talk about different marketing which is called content marketing, in content marketing data storage is very much important because if we don’t have any accurate data or we are not able to make proper and right content and in content marketing strategy data plays a vital role especially when we don’t have any idea about data analytics. By capturing or recording data digital marketers are better to understand what content or marketing strategies and methods are required for getting a better result. The things which come in mind for storing huge amount of data for a long time is optical media like DVD, and external USB - SSD drive for storing last 20 years as well as Network Attached Storage (NAS) with RAID: These have high performance magnetic hard disks and are your best option. Because of RAID, there is failure protection. I am not sure that original disks can last 20 years, but you can replace them (NAS allows hot-swapping of disks). In volume data storage it helps to keep a record of all past and activities of digital transactions. It also helps in data analysis so that any marketer can forecast the trends of the future market. It also provides flexibility and mobility and storage is easy and can move from one place to another, not only this it’s easy to forecast the better strategy formation. With the help of volume data storage decision-making is easy for the management which benefits the company’s business. 

In conclusion, it is not easy to manage and recognize the huge amount of data for the human brain so that with the help of data storage it is easy to keep a record of the day to day activities which increase the efficiency of the employee in many ways as a result easy to analysis the market scenario that helps business winning out in today’s competition.

Damanvir Kaushal

Keywords

#Volume Data storage

#Digital marketing

#Data storage

#Digital Transformation

#Social media

References and Sources :

• https://searchstorage.techtarget.com/definition/volume
• https://techterms.com/definition/volume
• https://docs.oracle.com/cloud-machine/latest/stcomputecs/ELUSE/GUID-6ACE7B13-442B-459C-8868-566F1CB65E3F.htm#ELUSE-GUID-6ACE7B13-442B-459C-8868-566F1CB65E3F
• https://docs.microsoft.com/en-us/windows-hardware/drivers/ifs/storage-device-stacks--storage-volumes--and-file-system-stacks
• https://kt.cern/competences/high-volume-data-management-storage

Velocity – Data Processing

What is Big Data?

Big Data is a modern subfield of data science that requires the use of several tools, methodologies and techniques to explore, analyse and process complex data sets in order to be provided insights and information systematically. 

The Five V’s of Big Data 

Big Data had broken into four dimensions by IBM data scientists. Volume, Velocity, Variety, Veracity and Value are known as the five V’s which can be referred as the characteristics or the key elements that define Big Data. These characteristics are crucial and must be considered by companies that want to run operations successfully. Volume refers to the size of big data while velocity can be defined as the pace in which the data is getting accumulated. Variety stands for the complexity of the data while Veracity can be considered to assure the accuracy of the data. Lastly, the term Value was added, representing the usefulness of accumulated data.
 
 
Velocity – Analysis of Streaming Data 
 
The speed at which data from IoT, mobile data and social media is generated, accumulated, distributed and collected can be defined as Velocity. The rate of velocity parallels with the speed in with the data is acquired and processed. Velocity-oriented databases provide users real-time analytics, information and insights which enable companies to make valuable business decisions at the right time. In addition; acquiring, analysing and processing data in real-time allows companies to solve upcoming problems before facing complex issues, making real-time decisions and catching frauds as well. Besides, Processing information quickly into data allows users to have flexibility in their queries and reports.
 
On the other hand, the systems which analyse the data should be compatible with the task which means high velocity data may require distributed processing techniques due to the speed it is being generated. Some organizations came up with several solutions for streaming data such as; Apache’s Kafka and Spark, Amazon’s Kinesis, Google’s Cloud Functions and other streaming applications that process information in almost real-time to handle the high velocity of data (Reca, 2020).
 

Every day 2.5 quintillion bytes of data is created to be managed, secured (Marr, 2018). Processing that streaming data instantaneously requires strong data handling processes. High velocity allows users to react high volume of information within a short time. Twitter or Facebook messages, social media posts, Facebook status updates, online transactions, fraud checking, credit card swipes, compliance mechanisms, GPS signals, purchase transaction records and live transportation data can be shown as high velocity data examples. For instance, Facebook needs to ingest, process and file all of the photos uploaded by the users in a short time (Gewirtz, 2018). Also, one TB of trade information can be captured by The New York Stock Exchange during each trading session. In addition, velocity is essential for packet analysis for cybersecurity since the massive flow of data should be analysed and investigated quickly in order to detect anomalies and prevent risks. Thus, data should be gathered, processed and presented near real-time to achieve successful business results (Tudor, 2020). 
 
Buket Bostanci

Keywords: big data, data velocity, velocity, data flow, data volume

References & Sources

Gewirtz, D., 2018. Volume, Velocity, and Variety: Understanding the three V’s of Big Data.  [online] ZDNet. Available at: https://www.zdnet.com/article/volume-velocity-and-variety-understanding-the-three-vs-of-big-data/[Accessed 21 February 2021].
 
Reca, M., 2020. The 5 V’s of Big Data. [online] FlyData. Available at: https://www.flydata.com/blog/5-vs-of-big-data [Accessed 21 February 2021].
 
Marr, B., 2018. How Much Data do we Create Every Day? The Mind-Blowing Stats Everyone Should Read. [online] Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/?sh=6da11b3560ba [Accessed 21 February 2021].
 
Tudor, N., 2020. Understanding the 5Vs of Big Data: Volume, Velocity, Variety, Veracity & Value. [online] BornFight. Available at: https://bornfight.com/blog/understanding-the-5-vs-of-big-data-volume-velocity-variety-veracity-value/ [Accessed 21 February 2021].

COVID19 and Big data | Big data helping businesses in 2021

Big data is the focus domain in the data science domain after covid19 and recent times. This can be simply explained by the example that recently to renew the license people used to visit the office before but now it's all done online. The amount of data collected starting from 2020 is enormous. It is same time true that big data analytics helped in tracking and preventing the spread of coronavirus. JHU released a dashboard for tracking and reporting real-time data on COVID-19 for most of the countries. (JHU, 2021)

COVID19 tracking dashboard by John Hopkins

Arogya Setu, the covid19 tracking app of India is downloaded 127.6 million till now on App Store and Play Store which makes it the world's most downloaded covid tracking app, the data collected from users including location, their test details helped in tracking and isolating the covid positive patients. Similiar applications developed are greatly supporting the segregation of population and location based on the amount of risk and also supports government and organizations to take up timely actions. (Yourstory, 2020)

Since the virus is novel, there require researchers to analyze a huge volume of information – out of scope for the human brain to comprehend on its own. The area called predictive analytics helps governments to manage patients who are more vulnerable most at risk from the virus.

Machine learning along with big data analytics aids in treatments like finding antibodies required for vaccine preparation.

Big Data in 2021 comes to action in similar scenarios as discussed where it helped in tracking spread to planning activities regarding the virus, the same time big data during this scenario came into wider discussion due to the fact that these applications collect a large amount of user data to fuel its functionalities. (TCD, 2021)

The future of business in 2021 can be improved like how Big Data supports covid19 tracking and prevention from 2019. Businesses can make smarter decisions using Big Data analytics where strategies are made using facts derived from data and not from assumptions or feelings.

Adoption of strategies: There is a wide range of tools available for data analysts where the centralized data is available to the different departments of the company not just the IT departments with controlled access s required. This enables departments to form strategies that aid in their varied operations. This avoids any miscalculation by the IT department since the data is available across all the departments to cross-check analysts and reports.

Serving the right customer: Likewise, how Facebook and Google know about us it is crucial for companies to know their customers well using the data they provided with content to better serve them and increase conversions by providing customized solutions.

Products and services: As discussed above knowing customer's likes and behavior also helps in customizing and offering unique products and services. Big Data Analytics will also assist in promoting and improving products and services that need attention leading to improved innovation. 

Boosting income: Using data it is possible it conduct competitor analysis to understand what works better for them in comparison. This helps in identifying the trends in their market, capture them at early stages, and adopting them. 

Big Data opens door to AI to automate decision making leading to increased revenue and happy customers. 

- Spoorthi Joshi S

References

YourStory 2020 | Arogya Setu remains among top 10 downloaded apps globally in May: NITI Aayog CEO Kant | https://yourstory.com/2020/06/arogya-setu-top-10-downloaded-apps-globally-niti-aayog  (accessed on 14th February 2021) 

JHU 2021 | The Johns Hopkins Coronavirus Resource Center (CRC) | https://coronavirus.jhu.edu/about 

(accessed on 14th February 2021) 

TCD 2021 | COVID-19 and the Perils and Promise of Big Data | https://www.tcd.ie/business/news-events/covid-19-big-data.php (accessed on 15th February 2021) 

What Is Big Data and How It Affects the Way of Decision Making?

In the era of digital transformation and emerging technologies, one cannot deny the importance of Big Data analytics which directly affects and enhances the decision-making process of an organisation. Here comes the question. What is Big Data and why effective usage of Big Data is crucial for companies who wants to achieve their digital marketing goals in the long term?

Components of Big Data

Big Data can be defined as large amount of data which is also fast and complex that makes the analysing process unmanageable with conventional methods. According to Laney, the components of Big Data are the three Vs which forms the definition of the term as high volume, velocity and variety of data to be processed. Volume means the various different sources that organisations can benefit for data collection such as connected IoT devices and social media platforms. Velocity describes the high-speed streaming of data including near real-time actions. Variety expresses the different formats of data which can be occurred both structured or unstructured such as email, video or financial transactions (Big Data: What it is and why it matters, 2021). Two more Vs which are entitled value and veracity have been added to the three Vs by some sources to emphasise the importance of the value and truthfulness of the data (What Is Big Data? | Oracle Ireland, 2021).

Why Organisations Analysing Big Data?

A survey was conducted in 2017 indicated that the number of companies which have adapted Big Data analytics has been dramatically increasing in the recent years. Moreover, the survey reveals the most common purpose of using Big Data as data warehouse optimisation which requires an integration of Big Data platforms such as Hadoop and Spark into an existing data infrastructure of an organisation. The main reason of using Big Data is followed by the purpose of analysing social media and streaming data coming from IoT devices which considered as data lake sources to define the unprocessed data, and exposing fraud detection (Watson, 2019). Once the organisations know the sources of Big Data, they will be able to manage and store the data by the help of Big Data platforms or cloud spaces, and then analyse it in terms of relevancy for the business purposes to have better, evident-based and data driven decisions in the marketplace that they compete (Big Data, what it is and why it matters, no date). It could be said organisations that are aware of the significance of the Big Data and have ability to process and analyse it properly, are more likely to have meaningful insights from their customers and make successful decisions while applying their digital marketing strategy.

Big Data Applications

There have been many applications of Big Data that have emerged as Natural Language Processing including Digital Assistants such as Amazon's Alexa and Apple's Siri, chatbots which are used for customer support, and Visualisation Systems including Drones and Facial Actions Coding Systems (FACS). For example, the company P&G used a coding software to analyse facial expressions of people for testing the scents of its new product which ended up with more precise and successful predictions of the software rather than what participants said (Hugh J., 2019). Another example of using Big Data shows how Amazon has been collecting detailed purchase data from its customers since then and how it lets other companies to access its ad portal to make them reach to the specific target audience (17 Big Data Examples & Applications, 2021).

Finally, using of Big Data by many companies brings governance concerns and security issues as well. To protect the privacy of personal data, regular controls of service providers need to be reviewed and the compliance with laws and regulations should be considered.

Keywords: Analytics, Big Data, Decision Making, Digital Marketing, IoT, Social Media

Ilgin Damla Omay

References and Sources

Built In. 2021. 17 Big Data Examples & Applications. [online] Available at: https://builtin.com/big-data/big-data-examples-applications [Accessed 16 February 2021].

Hugh J., W., 2019. Update Tutorial: Big Data Analytics: Concepts, Technology, and Applications. Communications of the Association for Information Systems, pp.364-379.

Oracle.com. 2021. What Is Big Data? | Oracle Ireland. [online] Available at: https://www.oracle.com/ie/big-data/what-is-big-data/ [Accessed 16 February 2021].

Sas.com. 2021. Big Data: What it is and why it matters. [online] Available at: https://www.sas.com/en_us/insights/big-data/what-is-big-data.html [Accessed 16 February 2021].