The Correlation Between Marketing, Data Mining, and Operations


I was always intrigued by data and numbers and the numerous conclusions that one could derive from a single datasheet. My strong point was always scoring over 99 percentile on ‘Data Interpretation’ for all the GMATs, CATs, and GREs taken over the years.

Having distributed business models these days; it is important to visualize the bigger picture to integrate the different fields through streamlining the marketing campaigns, communications flow, identifying the process maps, integrating automated tech solutions, understanding the data, and maintaining a cohesive inter-department communication flow.  

Now how does one reach meaningful conclusions based on some random figures? With the continuous change in customer demands contributing to the rapid advancement of MarTech tools, businesses have resorted to more data-driven campaigns. Many leaders still fail to understand the rich data they already have access to and go behind intuition to make important business decisions. This is where data analytic tools and expertise play a critical role for companies and the top management to use, leading to making smarter, informed, and strategic decisions to operate more efficiently.

These can be done using advanced software systems, including Tableau, Power BI, RapidMiner, KNIME, Qlik, Google Data Studio, and our very own Microsoft Excel to name a few.

How does data analytics boost a company’s overall performance?

  • Precise and more personalized marketing

Businesses collect essential information from customers through different channels, including google, email campaigns, and social media. This allows companies to create a client persona based on the customers’ attitudes and behavior while considering other factors, such as demographics, interests, nationality, and location information.

For example, companies can run predictive analytics to determine products that can be recommended for a specific customer or the best mediums to reach their ‘Ideal Client’. On the other hand, they can also analyze their sales data to gauge the client journey that helps to cross sell and up-sell to existing and new clients.  

In a study by Salesforce and Accenture, 91% of consumers believe that relevant offers and personalized recommendations impact their buying decisions, while 56% expect offers to be personalized based on their taste. This is a testament that consumers nowadays prefer a custom-made experience that data mining can provide to businesses.

  • Prevention of business risk & fraud

Data analytics is a critical foundation for a company’s efficient risk management and running an analysis can help identify events that might impact a company’s forthcoming financial goals and operational objectives. Once the risks are predicted, one can decide to adopt for a corrective or preventive action.

Furthermore, efficient data analysis can help a company prevent fraud and external threats coming through different data touchpoints allowing to mitigate potential risks.

  • Enhanced customer service

Data analytics just doesn’t provide in-depth insights, but it also gives companies the opportunity to be consistent when it comes to providing excellent customer service. Research conducted by Salesforce shows that 88% of customers claim that the experience that a company provide is as important as its product and services while 96% of customers say excellent customer service builds trust. Companies can attain this through analytical tools thereby making customer transactions seamless and easier through personalized customer experience.

  • Opportunity to be pioneers for trends

The world of business is competitive, but data analytics can help companies to be the first ones to start the next marketing trend by providing information as to what might turn out to be the next big thing in the market. Predicting future outcomes from past events and information using techniques such as machine learning and AI can generate future insights and forecast trends accurately.

In fact, according to a 2017 report by Zion Market Research, predictive analytics which is used to forecast trends is projected to reach approximately $10.95 billion market size and share this year, growing at a compound annual growth rate of around 21 percent between 2016 and 2022.

  • Results in better budget allocation

A company’s budget allocation influences its financial goals, which is why smart budgeting is critical to any marketing strategy. Learning to allocate budget wisely can help companies monitor their performance while capitalizing on products and services that are doing good in the market.

Data analytics can provide insights into what methods should be changed or enhanced in order to optimize the performing and non-performing campaigns to yield the best ROI. Analytical tools like Power BI enables one to dwell into the raw data and advise strategists how to allocate the budget between paid, organic, email, referral, and social campaigns.

  • Efficiency in resource management

Effective resource management leads to optimum efficiency, and leveraging information drawn from big data is a way for a company to maximize its performance. Nobody likes wasting resources, especially when it comes to business and affects the bottom-line. It is always important to introspect existing resources and check if a process automation can substitute for an employee.

Alternatively, advances in data mining and technologies can help in collecting a large amount of data that can be used to evaluate employee productivity and performance. Having enough information to identify performance trends and other factors can be a way to formulate constructive feedback that can help employees improve or stay consistent regarding their performance.

  • Streamline operational processes

The use of data analytics by company executives help in identifying ineffective internal processes that can lead to the development of new and streamlined workflows. Improving operational efficiency through data analytics boost corporate management by aiding business leaders in evaluating the effectiveness of existing workflows and refining them over time. Replacing slow manual operations with efficient processes can speed up all digital initiatives – to cut short, process automation is the future and increasing revenue per square meter is what matters.

  • Efficient leaders with data-driven decision making

According to Forbes, there are two distinct ways to use data as a leader — data-driven or data-informed. Data-driven leaders listen to data and allow the facts to prove or disprove their hypotheses. On the other hand, data-informed leaders use data selectively to justify their actions regardless of the findings. Data-driven leaders are proven to be the better ones because they use logic, reason, and facts rather than relying on subjective opinions to govern their choices. Having these types of leaders in any organization can maximize company efficiency without wasting resources.

  • Enhances process automation

Automated data analytics refers to using computer systems and procedures to execute analytical tasks with minimal or no human interventions. Companies take advantage of the automation in data primarily to increase the speed of analysis. Although automated analytic mechanisms vary in complexity, if used properly, companies can save costs and time.

It helps to reduce human error, increases accuracy in reporting, and saves budget if invested in the right tools.

Research reveals that the combination of AI and Big Data technologies can automate almost 80% of all physical work, 70% of data processing, and 64% of data collection tasks, and today, as much as 65% of global brands are willing to integrate big data technologies to stay competitive.

According to an article by Tableau, 40% of the companies leveraging data are enjoying various benefits like a better understanding of consumer behavior (52%), better strategic decisions (69%), and cost reductions (47%). Moreover, the organizations have reported an average of 10% reduction in costs and an 8% increase in revenues from analyzing data.

In Marketing, through customer profile data, marketers can make strategic business decisions and remove costs to strategies and campaigns that are not beneficial to the company. Data helps in finding out what medium best attracts their potential leads and maximize the potential of attracting new customers.

The big data analytics (BDA) market was valued at 168.8 billion U.S. dollars in 2018 and is predicted to grow to 215.7 billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go toward services. IT services are projected to make up around 85 billion U.S. dollars, and business services will account for the remainder.

Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The business intelligence and analytics software application market are forecast to reach around 16.5 billion U.S. dollars at the end of 2022.

In short, it is important to chalk the strategic vision and mission of your company regardless of the position or level you work at to evolve and grow into the person you want be. Continuous learning is non-negotiable, and it is highly recommended to improve inter-departmental communication to ensure cross-collaboration for overall productivity.


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