How Big Data Analytics & AI Combined can Boost Performance Immensely

AI and big data are twin pillars in most companies' technological strategies in an increasingly digital world.
big data analystics and artificial intelligence
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Big data, analytics, and AI all have a relationship with each other. For example, big data analytics leverages AI for enhanced data analysis. In contrast, AI needs a large amount of data to improve the decision-making process.

Consumers are presented with ads every day they access the online world. The number of options available to them can sometimes really stress them out. So, what is the primary concern of consumers? What makes them pay attention to what you are doing or how you are promoting your product or service?

Brands are closely working to solve this as they dive deep into the world of big data analytics. Well, don’t go anywhere because, in this article, we will show you how you can use big data analytics combined with AI to achieve the best performance possible. 

What is the relationship between big data analytics and AI?

Big data and AI have a direct relationship. Without data, AI can’t function and help you improve the decision-making process and leverage big data analytics for much better data analysis. You may be asking why this is important? When you combine big data with AI, you can help your users extract highly-valuable insights from data, foster data literacy across your company or organization, and take advantage of the many other benefits it offers.

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By combining big data and AI together, companies can improve their business performance in the following ways:

  • Analyzing consumer behavior 
  • Customer segmentation automation 
  • Personalizing marketing campaigns
  • Customer retention and acquisition 
  • Intelligent decision support systems powered by AI and big data

How big data analytics and AI can help you boost your business performance

Customer retention and acquisition

To stand out from competitors, every organization should have a uniqueness in its approach to marketing its product and service. Big data analytics allows companies to identify what customers are looking for.

Large amounts of data can observe consumer patterns. Afterwards, companies use them to enhance brand loyalty by collecting additional data to find out what makes customers satisfied. A perfect example is Amazon, which provides a high level of personalized shopping, one of the best on the internet. Purchasing behaviors are scanned from past purchases and similarities of what other customers buy as well. 

Improves decision making and reduces costs

Businesses can access a large amount of data and analyze data from different sources in order to gain new insights and take action. You can get started small and efficiently manage data with real-time insights.

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Furthermore, the flexibility in data processing and storage allows companies and organizations to lower costs in analyzing and storing large amounts of data. As we mentioned before, it also helps you discover customer behavior patterns with the help of AI and insights, so this means you can market your product and service much more efficiently. 

Business analytics

According to a study, 97% of businesses invest in big data and AI. Let’s not forget that big data and AI can also automate about 80% of the physical work required from human beings, 70% of the data processing, and more than 60% of the data collection tasks. From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace.

For instance, supply chain and fulfillment operations rely on data, so they rely on AI to provide real-time insights into customer feedback. By doing this, businesses can form their finance & marketing strategies with the new information they have gathered.

Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning.

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This is where business analytic specialists come in. These types of specialists can also present their product or service to investors and potential customers with the help of AI and big data analytics. Some programs offer you free templates customized to showcase your ideas, goals, funding, progress etc. As a businessperson, you can use these templates to make your Pitch deck and create a powerful presentation.

Collecting consumer information

Regardless of your industry, AI’s greatest assets are its ability to learn new things. Its ability to recognize data trends is handy and quickly adapts to any changes made. In addition, the AI’s ability to work with big data allows it to use data inputs for generating new rules for business analytics. However, there may be issues whenever the generated data isn’t good. 

High-performance data systems and MapReduce

Multiple vendors offer high-end computing systems that reduce latency when working with large datasets. However, the cost of these systems is too high for smaller organizations and can be a big issue when setting up a project.

With the evolution of technology and the introduction of Hadoop, Big Data analytics have become more accessible. These systems allow you to separate Big Data requests across multiple parallel computing systems, such as a programming model called MapReduce.

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MapReduce separates requests into smaller parts using a set of computing units and brings them back together for a final answer. However, sometimes, even these computing units can add complexities to an implementation. 

Targeted campaigns

Businesses can use big data to deliver products to their target market. Don’t waste your time setting up advertising campaigns that won’t work. Big data helps companies set up an in-depth analysis of customer trends. This analysis will usually include observing point-of-sale transactions and online purchases.

In-depth insights like these can allow companies to create successful targeted campaigns to exceed customer expectations and increase brand loyalty. 

Query Approximation systems and data summaries

Query approximation systems use statistical data sampling to predict the outcome of a query without running one. System samples will underline data and be based on the resulting answer on samples rather than on the complete set of underlying data.
The answers won’t be the same as the results you’d receive if you queried all of that data. However, most of the time, they are almost identical in making decisions.

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Additionally, we have data summaries, which are the attributes of data, and store this type of information for retrieving the data quickly. But, of course, whenever you use data summaries, there’s a limitation to pre-calculated points accumulated in summary, giving them limits to interactive reporting, where users can choose the number of permutations they want with data selection.

These existing solutions don’t succeed in offering high interactivity levels with big data due to one issue- they all need access to the underlying data. 

Identifying risks

Businesses are struggling with the same thing nowadays: having to deal with highly risky environments, but being in these environments requires you to have the proper risk management capabilities. Bg data has been very responsive in responding to risk management by providing new solutions. As a result, it can improve how effective it is and help you set up better strategies. 

Innovations

Big data and AI continuously help companies bring innovations to their existing products. Moreover, companies can identify what best fits their customers by collecting big data. Nevertheless, companies need to remain competitive in today’s market, and if they fail to do so, having so much data and the help of AI, it’ll be a major issue.

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For instance, you can use big data and AI to track customer feedback and product success and identify what competitors are doing. 

Wrapping it up

AI keeps evolving year by year so it’s no surprise if you see any major changes in the upcoming years in how data is managed. As technology evolves, so will data and what’s even more challenging is that the bigger data gets, the harder it is to be entirely controlled by a human being.

Above all, we recommend that you combine both the power of analytics and AI to learn more about your customers. The customer is the backbone of your business and if you aren’t gathering the proper feedback around them, you won’t be able to boost your business performance.

Data is what makes everything easier for us, to learn more about customer behaviors and what kind of tweaks you can make with the feedback you gather.

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Furthermore, AI is there to help you automate the data you gather, reduce time consumption, and make sure you are getting in-depth insights about your consumers.

Annie Qureshi
Annie is a passionate writer and serial entrepreneur. She embraces ecommerce opportunities that go beyond profit, giving back to non-profits with a portion of the revenue she generates. She is significantly more productive when she has a cause that reaches beyond her pocketbook.