Value in Big Data for Marketing

Data is valuable if relevant information is identified and process to recognise patterns, analyse performance and to make informed decisions. Tech giants are constantly evolving by exceeding customer expectations with the help of big data. Google aptly stated that “technology continues to shape people’s lives and shopping behaviour. They expect all digital experiences to be helpful, personal, and frictionless, providing a seamless experience no matter what the channel may be” (Google, no date). That’s why marketers are swift in keep up with today’s consumers and learning new ways to effectively persuade them to take action. They have hit the jackpot with online data and now optimising their resources and “tailoring ads by zeroing in on users that have already shown interest in their products” (Schiffman and Wisenbilt, 2019, p40).  

Social media is a major source for data and the volume is getting bigger than any other data type. The influx of information coming from these platforms is being used to perfect that marketing performance. Big data from social media worldwide is estimated to reach 44 trillion gigabytes by 2020 (Socialbakers, no date) and businesses are using these insights to understand users better, and plan better strategies for better ROI and engagements. 


Amazon is the powerhouse of the recommender engine and has nailed that to perfection. The company uses clickstream and historical data to mine 152 million customers and each user gets a customized recommendation (Datafloq, 2013). The buying process of customers has been streamlined to a T by showcasing a series of suggested products instead of going into a rabbit hole of products after products.    

Applying automation tools like artificial intelligence, bots, and analytics can tremendously increase marketing strategies and make the user experience better (Mallon, 2018). For instance, data-driven company Netflix uses metrics, insights, predictions, and analytic tools to dive into large, complex data to assess new opportunities to measure success (Netflix, no date). The company uses computing systems along with algorithms, and data to feed into each other to generate fresh recommendations (Netflix, no date). 

Surprisingly, Starbucks has been leveraging big data to open branches after branches by understanding the success of each location, customer behavior, and traffic into consideration (ICAS, 2016). Furthermore, the data coming from 90 million transactions a week worldwide are used to improve direct marketing, sales, and business decisions. The rewards program and mobile app which have 13 million and 17 million active users respectively are used to extract information about their purchasing habits (Forbes, 2018).  

Today, data mining has revolutionised businesses and enterprises are fully aware of the value these data sets provide to facilitate growth for a better outcome. The availability of various tools has made data processing cheaper and more accessible and companies have the capability to make more accurate and precise business decisions (Oracle, no date).

.
.
.
References:

Google (no date) ‘Evolving To Meet Customer Expectations’. Available at: https://skillshop.exceedlms.com/uploads/resource_courses/targets/75879/original/index.html?_courseId=14224#/page/5c79270517b63d054e68171c (Accessed: 10 February 2020)

Mallon (2018) 'What To Know About How Big Data Is Affecting Social Media'. Available at: https://www.smartdatacollective.com/what-to-know-about-how-big-data-affecting-social-media/ (Accessed: 10 February 2020)

Netflix (no date) ‘How Netflix’s Recommendations System Works’. Available at: https://help.netflix.com/en/node/100639 (Accessed: 17 February 2020)

ICAS (2016) ‘10 companies that are using big data’. Available at: https://www.icas.com/thought-leadership/technology/10-companies-using-big-data (Accessed: 16 February 2020)

Forbes (2018) ‘Starbucks: Using Big Data, Analytics And Artificial Intelligence To Boost Performance’. Available at: https://www.forbes.com/sites/bernardmarr/2018/05/28/starbucks-using-big-data-analytics-and-artificial-intelligence-to-boost-performance/ (Accessed: 17 February 2020)

Datafloq (2013) ‘How Amazon Is Leveraging Big Data’. Available at: https://datafloq.com/read/amazon-leveraging-big-data/517 (Accessed: 16 February 2020)

Schiffman, L and Wisenblit, J (2019). Consumer Behaviour. 12th ed. UK: Pearson Education Limited.

Socialbaker (no date) ‘Understand, Predict, and React: How Big Data Social Media Marketing Transforms Your Campaigns’. Available at: https://www.socialbakers.com/blog/big-data-social-media-marketing (Accessed: 16 February 2020)

Netflix, no date ‘RESEARCH AREAS: Analytics Driving insights from data’. Available at: https://research.netflix.com/research-area/analytics (Accessed: 17 February 2020)

Oracle (no date) ‘The Definition of Big Data’ Available at: https://www.oracle.com/ie/big-data/guide/what-is-big-data.html#link3 (Accessed: 17 February 2020)