The 5 Best Use Cases for Advanced Analytics in Business

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The use of advanced analytics has grown rapidly over the past few years as the technology continues to improve, become cheaper, and easier to use. And demand will increase exponentially over the next five years, according to a report by Frost & Sullivan.

Deviki Gupta, senior industry analyst at Frost & Sullivan, said in the report that advanced analytics is expected to see dramatic growth in the future as customers become more familiar with analytics as a whole and as technology use cases will increase.

What is Advanced Analytics?

Advanced analytics is a category of analytical tools that use sophisticated techniques and tools to analyze data beyond that of traditional business intelligence platforms.

Advanced analytics uses machine learning, pattern matching, semantic analysis, network and cluster analysis, sentiment analysis, and neural networks for tasks such as making predictions, identifying patterns, generating recommendations, and uncovering deep insights in data. Predictive and prescriptive analytics make up a large portion of the advanced analytics market.

Here are some of the best use cases for advanced analytics for business.

Learn about some of the differences between advanced analytics and BI tools.

1. Customer service

Advanced analytics are being used in a variety of ways to improve customer service, and businesses are feeling the benefits.

According to an insurance industry survey released earlier this year by Willis Towers Watson, the world’s third-largest insurance brokerage and advisory firm, approximately 77% of insurance companies want to use advanced analytics on customer data and 54% are already analyzing this data.

And what is the main reason to apply advanced analytics? To expedite customer service.

And the positive results are already there. According to the survey, 68% of respondents are already seeing a positive impact on overall performance from their use of advanced analytics, and 86% are seeing a positive impact on overall performance.

And the insurance industry is not alone.

According to a recent Forrester Research survey of analytics professionals, 47% of respondents used analytics to gain new customers, 31% used it to improve customer retention, 28% used to increase customer lifetime value and 23% used it to improve customer experience.

The percentage of companies using advanced analytics for customer acquisition increased 14% over last year, said Forrester analyst Brandon Purcell.

“But many companies actually start with customer retention like [an advanced analytics] use cases because companies typically have better data on their own customers, he added.

Analysts look at historical data from customers who have left, feed it into a supervised machine learning model, and then use the model to calculate risk scores for existing customers.

“You can optimize your retention efforts,” he said. “Telecom carriers are really good at this. Verizon has less than 1% churn because of this. Their churn models are very robust. So are banks.”

Subscription-free businesses such as retail businesses are also looking to use advanced analytics to improve retention by looking at historical data about customers who haven’t shopped there for a certain period of time.

2. Predictive maintenance

According to a report published last December by IoT Analytics, predictive maintenance is the largest use case of industrial advanced analytics which would have represented more than 24% of the total market in 2019. According to Deloitte Analytics Institute, predictive maintenance based on advanced analytics can increase productivity, reduce downtime and lower overall maintenance costs.

Royal Dutch Shell, for example, develops and maintains thousands of models to support predictive maintenance applications on thousands of pumps and valves on offshore oil rigs, said Doug Henschen, vice president and principal analyst. at Constellation Research.

“It’s a high-value use case because a failure on an oil rig could mean millions of lost dollars or, worse, environmental damage,” he said.

3. Recommendations

Another high-value use case for advanced analytics is recommending products or services to customers. Amazon is the 900-pound gorilla here, but plenty of other companies offer recommendations to improve sales.

There are also startups specializing in narrow applications of this technology.

The Climate Corporation, for example, is a digital agriculture company that helps farmers figure out what to plant, where and when to plant it, Henschen said. The company’s seed advisory service collects historical data such as past crop yields and soil samples and combines it with other data sources, including weather data, then runs it through thousands of different models, he said.

“It provides recommendations on what seeds to plant and when, how deep to plant the seeds and how far apart the rows should be,” Henschen said.

He said farmers using this information were able to increase their yields by more than nine bushels per acre.

4. System Optimization

Companies are using advanced analytics to optimize everything from supply chains to drug discovery to data center operations.

According to Dan Simion, Vice President of AI and Analytics at Capgemini, one of the main use cases for advanced analytics in business is to use pattern recognition to analyze usage trends. IT resources, such as servers and networks, and forecast application usage and bandwidth requirements.

“The goal here is not to have unhappy customers because their apps don’t work,” he said. “One of our customers used AI-based models to predict the number of licenses needed for different applications.”

This use case was especially useful when the COVID-19 pandemic hit, he said.

“When they moved to working from home, it led to an increase in requests for video collaboration,” Simion said. “With the AI-infused models, they were able to make sure they had the bandwidth and the licenses to use the tools.”

The healthcare industry has been hit the hardest by COVID-19, and many organizations are using advanced analytics to meet new challenges.

“We see them using advanced analytics to analyze patient and hospital data, and visualize COVID-19 data from inside the organization, as well as research from outside sources,” said Vijay Raman, vice president. -President of Product Management at Ibi, an analytics provider. which is currently being acquired by Tibco.

Ibi recently worked with St. Luke’s University Health Network in Pennsylvania to help them develop more than 100 self-service apps that use advanced analytics. Raman said the scans are being used globally to track the impact of the virus and locally to support high-risk patients.

5. Product development

Advanced analytics is also used to help create new products and services. Purcell said this is the most exciting emerging use case for advanced analytics.

“Use the results of customer analysis to create a new phone or whatever customers might need,” he said.

The analysis can also be part of the actual product or service, he added.

“In the world of IoT and connected devices, for example, how do we create products that can better track customers and improve engagement through the products themselves?” he said.

The future of advanced analytics

As advanced analytics continues to become easier and less expensive, we can expect to see many more use cases as the technology becomes more economically feasible.

“Fifteen years ago, predictive analytics and data mining methods combined with advanced analytics typically appeared in high-value use cases,” Henschen said.

These high-value use cases include lending; fraud and risk analysis; processing insurance claims; and high-volume, high-value marketing use cases, such as direct mail targeting and customer churn risk analysis for mobile and cable companies.

“Model development methods at the time were slow and manual, and the infrastructure costs required were high,” Henschen said. “As a result, it has not been easy to widely disseminate the benefits of these techniques.”

Today, data science platforms and cloud computing have reduced the cost and effort needed to create and use models, he said. Advanced analytics is now being applied much more widely across industry verticals and for many new use cases within those industries.

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