Top Trends in Business Analytics Are Changing Business as Usual

Top Trends in Business Analytics Are Changing Business as Usual

Artificial intelligence (AI) and machine learning are taking data analytics to the next level. Companies are increasingly using automation for better insights about their customers. These AI-driven big data analytics solutions enable companies to use their understanding of what's happening right now to shape future outcomes. It really is an amazing time to be alive!

Data analytics promises to impact every aspect of business operations, from improving customer experiences to increasing productivity.

Here are five trends highlighting how business analytics are changing the status quo:

1. The Reinvention of Customer Retention

While subscription revenue models were once used primarily for print publications and software, they are now used for selling everything from groceries to entertainment services (Heck, even transportation is getting in on the game). One of the keys to success when it comes to subscriptions is reducing churn — or customer turnover.

Fortunately, data analytics is taking customer retention to a new level. Beyond simply projecting income streams or renewal rates, data analytics can provide insights into which customers are most at risk.

What's more, with the rise of predictive analytic capabilities, companies also can identify those prospects that are most likely to respond to their marketing efforts—and those that are a lost cause. This is where knowledge becomes power. Decision-makers can allocate resources toward those surer bets, re-engaging them by offering more relevant products or services. Targeting means more cost-effective marketing and less time and money wasted on customers and prospects that don't resonate with a particular brand.

In short, focus your time and money on those customers who will get you an ROI.

2. Knowing Buyers Better than They Know Themselves

Brand marketers have to really understand their market. Thanks to data analytics, e-commerce retailers have been able to gather an enormous amount of information about customer behavior, enabling brands to develop an in-depth understanding of product preferences and shopping patterns.

Machine learning technology enables companies to develop business strategies based on what has worked before. Automation also facilitates real-time action, such as offering a discount to a potential customer who has left an item in his or her shopping cart. Data analytics can also help a brick and mortar retailer better plan inventory needs based on criteria such as weather, community and cost basis. Details usually limited to the local store managers can now be planned and anticipated at the highest levels, no matter how remote.

3. Improving Customer Experiences and Reducing Risk

The financial service industry is an example of how big data is being used to improve customer experiences and overall business efficiency. Some solutions include helping consumers manage and improve their finances. For instance, a host of fintech apps use AI and analytics to provide automated services, from investment advice to saving extra cash.

Banks, meanwhile, are leveraging predictive analytics to help identify and stop fraudulent activity. McKinsey reports that in some of the most cutting edge applications, financial service firms rely on predictive models that consider patterns of previous fraud as well as new indicators of criminal activity to prevent fraud before it happens.

4. New tools for improving productivity and product quality.

While early adopters of big data solutions in manufacturing focused on predictive maintenance, companies that are staying ahead of the curve are using data-driven strategies for process improvements, waste reduction, and quality assurance. For example, automotive manufacturers are collecting data on newly launched car models by monitoring for technical issues, and then using that information for engineering improvements. Improved business analytics means that manufacturers can identify and fix problems earlier, or even before they happen — helping them avoid or minimize the impact of bigger problems, such as recalls.

5. Better Customer Experiences Across the Board

Better, smarter usage of data is becoming a fundamental business capability. Big data technology is already having a significant impact on customer experiences. In fact, 77 percent of high-ranking customer service teams rank their use of predictive analytics as above average or excellent. This ranges from using data to predict basic customer needs to gathering product feedback and course correcting in real-time. The result is ushering-in a new era of data-driven customer service that is far more personal and relevant than ever before.

While Business Analytics may still be a young field in the business world, it has already shaken many of the core principles that we attribute to "successful business". Like other industry disrupting technologies before it (automobile, computer, the internet), the adoption of artificial intelligence to perform business analytics at scale will lead a major shift in the thinking of all industries, big and small.

Keyence has more than 40 years of success using data-guided business practices. Download our digital brochure to learn more about how you can turn your data into action!

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