The Business Benefits of Data Analytics Pose Enormous Opportunity

Most organizations understand the potential benefits of investing in Big Data analytics: These tools promise cost savings, productivity gains, and better decision-making. According to a MicroStrategy report, 90% of participating business users said that data and analytics are central to their organization’s digital transformation initiatives.

Analytics holds the key to truly “knowing” your customer and paves the way for innovative solutions, hyper-targeted advertising strategies, and personalized marketing campaigns. In this post, we’ll look at the benefits of Big Data.

Benefits of Data Analytics in Business

Big Data, AI, Internet of Things (IoT), and machine learning (ML) are converging. Organizations now have access to powerful analytic tools that can unlock a whole range of competitive advantages:

Better Decision-Making

One of the main benefits of Big Data analytics is that it improves the decision-making process significantly. Rather than relying on intuition alone, companies are increasingly looking toward data before making a decision.

When Big Data joins forces with AI, ML, and data mining, companies are better equipped to make accurate predictions. For example, machines might help brands predict what a customer might buy—customers that buy X beer and Y bread are likely to buy Z product.

Essentially, you’re automating what was once a years-long accumulation of knowledge and using technology to arrive at conclusions faster and without all of the trial and error. Another critical use-case is using AI-analytics tools for classification, such as identifying a cat vs. identifying a suspect with an outstanding warrant.

More Accessible Analytics

More and more, AI is helping get data analytics in the hands of more employees by democratizing the process of generating reports and making sense of the findings. With self-service, intelligent tools, organizations can gain complete visibility into their operations across all departments.

Automation

A report by EY estimates that automated data processing can support around 65% of HR tasks, including payroll processing, candidate screening, and data cleansing. According to McKinsey, businesses can automate 69% of time spent on data processing, which stands to increase business effectiveness while reducing costs. Data processing tasks include everything from processing loan applications and customer support queries to manually processing invoices and forms. The firm also estimates that at least 18% of all business activities can be automated.

An Atlassian survey on The Future of Teamwork revealed that nearly 87% of workers think that AI will change their job while 76% believe that at least some or half their job could be performed by a robot, algorithm, or AI-enabled device. What’s important to understand here is automation isn’t necessarily a bad thing—we still need humans for the foreseeable future. The Atlassian report says these changes are a real opportunity for workers to use technology to help them solve problems and eliminate mundane tasks.

Predictive Modeling

Predictive modeling allows organizations to understand the root causes behind problems and predict future outcomes. For example, doctors use analytic simulations to identify the best care plans for infants in the NICU, manage public health issues like kidney disease, and track COVID-19 outbreaks. Financial services use predictive analytics tools to identify fraud risks and determine credit-worthiness. Additionally, you see these tools used to support policies around climate change and conservation, nuclear power, oil drilling, and more.

Fully Understanding the Potential of Data-Driven Marketing

Organizations can become truly customer-centric by using Big Data analytics for a competitive advantage. What’s important to understand about data-driven marketing is that while marketers have long focused on using data for ad targeting and content creation, most organizations have yet to achieve true marketing intelligence.

Often, you have teams that capture a lot of data and are skilled at interpreting the behind each metric. However, even the best analysts work off of best practices and gut feelings.
Innovations in AI and machine learning are changing the game by filling in knowledge gaps and streamlining the process of analyzing data and serving up the most effective possible action plan.

Personalization

Delivering a personalized experience is considered the standard that most marketing teams strive for. As such, one of the primary advantages of Big Data analytics is that marketers can now provide tailored interactions at scale.

According to a Salesforce report, 84% of customers say being treated like a person is very important to them. Their findings also revealed that consumers are more than twice as likely to view personalized offers compared to those perceived as being generic.

Big Data powers recommendation engines and price optimization, and it provides a holistic view of the customer, allowing companies to cater to the individual user. For example, United Airlines uses data to provide personalized service by giving flight attendants an app containing customer information. This allows them to assist guests with a tight connection or special needs better, as well as engage users based on profile information.

Retention and Loyalty

A study by Markets and Markets found that social media advertising, email campaigns, and behavioral analyses are the key enablers for increasing sales and consumer loyalty. Social listening, website analytics, behavioral data, and market research all come together to help brands understand what audiences truly want from them.

Forecasting

Big Data analytics, combined with statistical algorithms and historical data gives marketers the ability to predict consumer behaviors and outcomes more accurately. They can then apply key insights to future strategies.

Optimized Messaging and Solutions

Companies can use data analytics to identify what customers want and what messages they respond to, and then apply those insights to marketing, development, and sales strategies.

Accurate Measure of Campaign ROI

Attribution has long been a major challenge for marketers. Advanced analytics tools help measure the impact of all campaigns, communications, and tactics that contributed to converting a customer. These insights give organizations a framework for future strategies: What channels, actions, and content were most (or least) effective? The insight also help companies make better budgeting decisions.

Innovation Benefits of Big Data Analytics

One of the biggest advantages of Big Data is that companies can use AI-enabled analytics tools to create new products and improve existing ones. According to a survey from MIT Sloan Management Review, 54% of businesses use their AI investments to accelerate time-to-market on new products and services.

As mentioned in the previous section on data-driven marketing, Big Data analytics provides companies with a major advantage by revealing exactly what customers want. Analytics is great for finding hidden patterns and correlations that humans can’t easily observe by reviewing large data sets, allowing companies to answer fundamental questions:

• Who are our end-consumers, and what do they want?
• How can we make our products/services better?
• What gaps or opportunities exist in the market?

By bringing together different data sets that look at buying behavior, consumer sentiment, and demographic information, businesses can identify new customer needs and pain points, and then build solutions that speak directly to those findings.

Big Data analytic tools can also be used to experiment with different variables to identify the best possible solution quickly. AI and machine learning can provide the ability to test for hundreds of potential scenarios at once to identify the best possible use-case.

Additionally, that technology can be trained to discover unknown variables that humans would have never identified on their own. For example, IBM’s Watson was able to sift through digital records to identify six new cancer suppressors within two months. That amount of work would have taken researchers years.

Wrapping Up

The opportunities with Big Data are far too powerful to ignore. Smart, data-driven organizations are increasingly taking advantage of new tools to help them understand customers, automate processes, and streamline complex operations. They’re leveraging real-time insights to enable rapid decision-making about new opportunities and emerging threats. Right now, there’s an opportunity to get ahead of the curve and lay the foundation for long-term success.

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