IntelliPaper
Abstract
The digital world is largely expanding. Today more than 5 billion people are using the Internet which is developing in a correspondence increase in the flux of data that is being generated. A lot of researchers highlighted the importance of big data and the challenges, abilities, and capabilities associated with collecting and analyzing such huge data sets to support a level of decision-making that is more precise and time-consuming than anything previously attempted. This article aims to shed light on this phenomenon from a marketing perspective. Contrary to what has often been assumed, the familiarity, usage, and benefits derived from data are not for scientists only. Marketers have always dealt with research to get data and today they are challenged more than ever through dealing with big data-driven decision-making. There is more and more of a need for marketers with knowledge of data because the insights derived from big data, the decisions made, and the actions taken make all the difference. Instead of data moving purposelessly around in the ether, marketers find value in this data that will help businesses take better actions. In this article we attempt to prove how combining big data with an integrated marketing strategy will have a substantial impact in areas related to customer engagement, customer retention, and loyalty and finally on optimizing marketing performance.
Explore Digital Article Text
I. INTRODUCTION
The world's most important resource is no longer oil, but data (The Economist, 2017). Almost six years after this statement, describing the opportunity and size of that staggering truth is difficult. Today, our everyday lives in the digital age are being facilitated by services and platforms that are powered by a new type of fuel called Data. In the framework of marketing, the benefit of actionable data insights is massive – they optimize marketing performance, guide day to-day decision-making, drive strategy, induce customer engagement and retention, and fuel innovation. Many brands like Facebook, Google, Tesla, Apple, and Uber have changed our world just because they pioneered adapting and disrupting data-driven decisions and innovation. All these data-driven insights benefits have increased the interest of marketers in mining digital data (Sponder & Khan, 2018). Markets and consumers have evolved throughout the years, and this evolution has directly impacted researchers and marketers. For every business to succeed, a strong marketing strategy needs to be implemented in today's competitive business landscape. And to do so, marketers can no longer rely only on their assumptions when making marketing decisions. With the abundance of data available to businesses, data-driven decisions are becoming more and more important (Bibby, Gordon, Schuler & Stein 2021). Nowadays, marketers need to modify their techniques and methodologies to gain a deep understanding of consumers' trends and tendencies to mirror experiences and engagements.
Data analysts are mainly responsible for communicating the data that matters by highlighting trends and insights based on the visualization, transformation, and manipulation of existing data. (Sponder & Khan, 2018). Marketers are expected to gain these skills because organizations all over the world are increasingly approaching their businesses from a customer centric perspective and collecting massive quantities of customer information in the process; utilizing this data flood is an enormous challenge (Bibby et al., 2021). Research has always been an integral part of the marketing process. The systematic design, collection, analysis, and reporting of data and findings relevant to a specific marketing situation facing the company represent the first steps in developing marketing strategies. Marketers must know their customers and gain an extensive understanding of their behavior and with the amount of data provided by the customer himself, database marketing is today more than ever playing an integral role in optimizing brands' performances. Evolving consumer behavior and the fast pace changing marketing landscape have put pressure on businesses to put marketing operations in a position to shape the interactions with customers rather than just connect with them. Today marketing operations necessitate the combination of skilled people, efficient processes, and supportive technology (Edelman & Heller, 2015). Born from the digital world we live in, the new marketing landscape has acquired a fundamental value: Big data. Has digital brought anything new to marketing? digital marketing is certainly faster and more cost-efficient but has not brought anything new to marketing operations. Research and data are not new to marketing, what is new is the size and opportunity of data that is challenging every marketer and pushing him to gain more skills in data analysis (Charlesworth, 2020).
Organizations must be aware of the importance of data analysis and provide their employees with relevant training and academic institutions must rethink their course offerings to equip future marketers with data analysis skills. Developing these skills will improve marketers' potential in putting different data together like paid advertising analytics and conversation, data website traffic, data customer care, and data sales and explore the direct and indirect connection to get a specific source of fact. Integrating different data sources into clear reports intended for insight-driven marketing decisions will unlock the organization's value and optimize its potential. Marketers skilled in combining big data with integrated marketing strategies will make a substantial impact on significant areas related to customer engagement, customer retention, loyalty, and optimizing marketing performance. Big data does not simply help you connect with the customer, but it helps you gain an in-depth understanding of who your customers are, what they want, how they want to be contacted, and when. What makes this kind of data reliable is that the customer himself is the source and he willingly made it accessible to marketers. Combining data learnings with strategic thinking also allows marketers to develop loyalty programs that are relevant to the desires of their customers by identifying what could influence them to make them want to be labeled as their loyal customers and what would affect their buying behavior and increase their consumption. With access to big data, achieving ROI is becoming more achievable through data and metrics helping to assess performance and optimize it in a way that every dollar spent is directly linked to conversions achieved. The data that matters to marketers can be classified into 3 main types: customer, operational, and financial. Customer data includes behavioral attitudinal and transactional metrics and can be retrieved from different sources such as marketing campaigns, communities, loyalty programs, points of sales, websites, customer services, and surely social media. Operational data is crucial in setting objective metrics that measure resource allocation, budgetary controls, asset management, and quality of marketing processes.
Finally, the financial data which is usually found internally within the company systems play a major role in assessing sales, revenues, profits, and other important numbers that reflect the financial health of the organization (Chernev, 2019). When those 3 types of data are combined, reports and conclusions are derived to enable the development of a marketing strategy that is efficient and profitable. Data is not only the new oil but it also can be described as the soil that supplies the world. Organizations are more and more seeking to grow from it. The internet of Things (IoT) is a great example of how data can generate more data. It is when the product becomes the source of data itself through a dynamic system of devices that use the internet to exchange data and the "thing" represent all the internet-enabled devices such as smartphones, computers smartwatches, smart TV, smart homes, etc. IoT, which integrates everyday "things" with the internet can give an edge and truly generate innovative marketing campaigns. IoT devices are senders and receivers of data, and this data is very valuable and helpful for marketers to be able to predict trends, sales, and market changes in general which leads to the formulation of effective strategies that enhance revenues. Data of IOT helps marketers decide on how to improve their product or what offerings might be useful and desired by the customers through an in-depth analysis of the consumer interaction with the product and thus it will help them have more personalized and customized offers which will convey more happy customers and satisfying business leads (Greengard, 2015). Fitbit, for example, gathers data from the device itself and provides the user wearing the device with personalized messages, activities, and relevant promotions in addition to that Fitbit gathers statistics by itself related to the user's performance and achievements and gives him the option of sharing it with his friends on social media. By that, the users' friends are informed about their friends' activities, influenced, and are surely aware of the Fitbit benefits from a trusted source even though the source of the data is the app itself. The app uses data to promote itself through a trusted source: the user (Waher, 2015) Data can also drive creativity. The data are retrieved in visuals that represent more than numbers and facts; they tell stories. Data analysis is the collection of data that is being analyzed to tell stories using charts and visualization. Contrary to what has often been assumed, the familiarity, usage, and benefits derived from data are not for scientists only. Marketers have always dealt with research to get data and today they are challenged more than ever through dealing with big data-driven decision-making. Data is derived from more sources than a website page makes connecting insights to actions more challenging and has raised the need for incorporating many data sources via database integration and application programming interfaces. It is also important for companies to be aware that the analytics strategy cannot be handled by one person or a very small team. It is important to spread access and leverage the strengths of multiple teams to create maintainable cooperative data culture to achieve scalable and valuable results. Real-time data with advanced analytics and machine learning models combined with Key performance Indexes (KPIs) that are set based on business goals can achieve greater results (Sponder & Khan, 2018). This combination mastered by the marketer will provide clearness on the direct impact of data-driven decisions on ROI.
Finally, for data to be valuable, marketers must be equipped with the knowledge and provided with training that will help them merge their strategic thinking with existing information derived from data which will lead to optimized performance. Data analysts' skills are required to be part of marketers' skills to help organizations grow and stay one step ahead of the competition. There are plenty of analytics tools available and accessible but tools without people are useless. The combination of great tools with expertise to use the tools unlock the value of data (Simon, 2015). In 2023 and beyond, businesses looking for success must adopt a data-driven marketing approach. Decision-making based on data and analytics will improve the effectiveness of the marketing strategies, help them reach their target more efficiently and the data-driven approach, and lead to more profit. Marketers are expected to quickly adapt to the new technologies and innovations that are shaping their roles and responsibilities in the industry. It is also important that academic institutions and organizations be aware of the importance of data, technologies, and innovations since they play a major role in supporting the evolution and advancement of marketers' performances by providing them with knowledge and training that will keep them up to date with the pace of the market changes. We can conclude that yes data is the new oil, but it needs a powerful engine to extract it. This engine is the organization that builds internally a strong analytics culture and competency. Only with this engine, the new oil will harness and produce wiser decisions.
Conflict of Interest
The authors declare no conflict of interest.
Ethical Approval
Not applicable
Data Availability
The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].
Funding
This work did not receive any external funding.
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