The year is 2023, and it seems like the era of Skynet has finally begun for us, if just a few decades later than in the Terminator franchise.
Artificial Intelligence (AI) has taken the world by storm. Although the technology has existed for quite several years, the sudden emergence of publicly accessible AI services like power of ChatGPT and Stable Diffusion has put AI at the forefront of almost all business discussions. After all, AI seems to be the road ahead, and many businesses have already begun investing in AI for the future. For example, we have seen mega-corporations like Microsoft develop their very own predictive AI search engine, while the newsroom seems to be experimenting with AI as well, with CNET now using AI to generate journalistic articles like a production line in a factory.
Certainly, while AI has come far and become a major point of consideration when it comes to automation today, we can’t forget just how integrated AI already was in business prior to the current surge in popularity.
AI and Big data have been a massive part of our lives ever since the technological age kicked into high gear around the mid-2000s. We have known for several years now how corporations, mainly social media corporations, leverage data alongside AI to gain keen insights for business growth.
Until now, AI use has been a rather hush-hush subject, only being mentioned behind closed doors, and corporations are treading very carefully when it comes to revealing their AI and data usage, thanks to the number of strict regulations put on these technologies.
In this article, we discuss the various ways businesses can leverage big data and AI to gain never-before-seen insights into their business and plan for the future based on these insights. But first, we must start from the basics: what is big data and how does AI work with big data?
What is Big Data?
Let’s hear it straight from the experts at SAS what big data is exactly:
“Big data refers to data that is so large, fast, or complex that it’s difficult or impossible to process using traditional methods.”
In the information age, there is a constant influx of data into the business, of all different natures. For example, there is customer data, financial data, market data, and so on and so forth. All of this data is harvested from various sources, such as social media, customer interactions, online surveys, transactions, and so on.
And because of the sheer volume of the data and the absurd speed at which it comes through thanks to the Internet of things, traditional data analysis methods are simply inadequate to deal with it. In the old days, we had enough data coming in that a single analyst could initiate the data mining process and find patterns in the data, which could then be put to further use. But today, this is a job that no human can perform.
Artificial Intelligence and Big Data
Luckily, Artificial Intelligence (AI) completely solves this problem. By putting artificial intelligence algorithms on the job, whose advanced machine learning capabilities and ability to sift through and categorize large swathes of raw data, we can put the waterwheel of our business in this river of data and start using It to fuel our business growth.
Combining AI and Big Data has created new opportunities for businesses to gain insights into customer behavior, market trends, and other critical aspects of their operations. With the help of advanced analytics tools, businesses can analyze large datasets to identify patterns and correlations that can be used to improve business processes and enhance customer experiences.
Gaining Business Insights Through Big Data and AI
Customer Behavior Insights
It may not seem like it, but every interaction a customer has with your business, no matter how small, is valuable. As a result, your customer base is a treasure trove of data that you can use to your advantage.
By looking at your customer base’s shopping patterns, for example, you can figure out exactly what kind of product your repertoire sells and what is not. Furthermore, by looking at your customer’s biographical data such as age, gender, and spending habits, you can pinpoint your exact target audience, and tailor your products as well as your customer experience to best fit your primary customer base.
For example, if you run a clothing brand, and see that most of your customers are female, and your male customer base is significantly smaller. You can augment your business strategy to reduce the inventory you carry on male clothing. You can also hire more female sales staff, to make a friendlier environment for your primary customer base. Furthermore, if you see that the average spending range of your customer base is for example $400, then you will adjust your pricing to be more appealing to your target demographic.
By processing your collected customer data through advanced AI and machine learning-based techniques like data mining and predictive modeling, you can generate a clear picture of your customer base’s behavior and habits and develop business strategies appropriately.
Marketing Insights
Marketing Analytics is another area where businesses can leverage AI and Big Data to gain valuable insights. Businesses can identify the most effective marketing strategies, campaigns, and channels to reach their target audience by analyzing customer data.
Think about it, if your business is active and engaged with customers on various social media channels such as Facebook, Twitter, Instagram, and so on, then you can pool all of that engagement data together using processes like data integration and get a single unified picture of your customer demographics and preferences.
After that, you can divide your entire customer base into segments based on various customer segmentation criteria, such as behavior, preferences, and other criteria, enabling them to target specific groups with personalized marketing messages.
Financial Insights
Perhaps the most useful way to leverage data insights is in the domain of finance. The information collected and analyzed via data mining, data warehousing and other data science methods can be put to amazing use in the finance department.
Financial data can tell you almost everything about your business. From business health to the business’s prospects, all of these answers can be found in the business’ data banks. Of course, on its own, this data might as well be useless, but in the hands of competent bookkeeping accounting services usa and professionals , who can interpret this data and tell you exactly what the business’ current status is and what measures need to be taken for the future, AI can be quite a formidable weapon.
Furthermore, by using predictive modeling and data visualization software, businesses can draw a fully visualized map of their estimated financial future based on historical data.
AI and Big Data can help businesses to identify potential financial risks and opportunities. By analyzing large datasets, businesses can gain insights into market trends, investment opportunities, and potential areas of risk.
Business Process Insights
It can be very difficult to look at your business’ workflow and spot what is a problem and what isn’t. Especially in medium-to-large-sized businesses, where multiple departments are all working in tandem, optimizing business processes can be a massive headache due to the interconnectedness of it all. With AI and machine learning, however, it becomes very much more doable.
By observing your organization’s work patterns across the business, A seasoned business analyst can determine where things are taking longer to happen, or what processes seem redundant or mishandled. For example, suppose you’re looking at your supply chain and you see that your supply chain has faced regular setbacks in the past due to accounts payable missing out on payments. In that case, you can contact your AP staff and ask them what the issue has been for the delayed payments, and work your way up from there to find the root of the problem.
This was only possible because you had consolidated and processed your business data into meaningful information through AI.
Data Governance
While all of these insights are truly amazing and contribute greatly towards business growth, you can never forget about the extremely sensitive nature of your business’ data.
As we have mentioned at the start, it is incredibly heavily regulated. You can’t simply leverage any data however you please without the proper protocol and operation measures. Therefore, data governance must be enforced across the business.
What is data governance? Put simply, data governance is the collection of policies, rules and regulations that an enterprise enforces throughout the business for data security, access control, and proper data handling
Your data governance plan is where you decide what function gets access to what data, how that data can be modified and all interactions with that data be tracked, and how that data stays safe and in the hands of the business alone. All of these things matter, and if you slack on your data governance because you are blinded by the potential for business growth through business insights, then you are in for a world of trouble with the government and with your customer base, should anything go wrong. Expertise Accelerated publication titled “A Guide to Cyber Risk Management in Business Accounting”, while a post primarily about cyber safety in the accounting function, also goes in depth into cyber security best practices that can be applied all across the business. After all, the finance function always has the tightest data security measures in place, so why not use it as the standard for the rest of the business?
Conclusion
By leveraging AI and big data, businesses can access key business insights through data science and data analytics technology, which can help spur business growth. Whether it be the marketing department, the finance function or the sales department, data analysis can show you how to make every business process better, and by means of predictive modeling and data visualization, even graphically forecast the business’ future based on historic trends.
It is important to remember that AI is not everything, and you still need the human element to oversee all data analysis. Computers are not flawless; they also cannot self-reflect and pick out issues logically. You always need human input and opinion when putting the data insights to use. An AI can give you the raw facts of the matter, but you need human input to process and get into the decision-making phase. AI is ultimately a tool, so use it to help you and your professional staff grow alongside the business.
