Why should firms shift to Advanced Analytics ?

There were times when the whole world was stunned by the word “Analytics” and today all we hear about is “Advanced Analytics”. Why do we keep hearing this word frequently? Did you know that according to PRNewswire, the estimated value of the global advanced analytics market which was $29.5 billion in 2021 is anticipated to reach $184.4 billion with an increase at a CAGR of 20.2% from 2022 to 2031? Isn’t it something then to be implemented in your firm?  Here’s a short intro to Advanced Analytics.

As per Gartner, Advanced analytics is the autonomous or semi-autonomous analysis of data or content to gain a deeper understanding, predict the future, or produce suggestions. A few examples of advanced analytical techniques are data/text mining, machine learning, visualization, sentiment analysis, simulation, complex event processing, and neural networks.

Companies that do not use advanced analytics miss out on big customer-service improvements. The good news is that simple data and analytics solutions are becoming commonplace. While it is an excellent first step, most firms are not fully utilizing the technology and vast amount of data they generate, which means they are not into advanced analytics in ways that truly put the customer first.

Unlike previous data and analytics solutions, which assisted businesses in understanding what was now happening within them, advanced analytics assist them in generating actionable insights about what will happen next, via both internal and customer-facing applications. As a result, costs are decreased, income is boosted, and, most importantly, customer satisfaction is higher.

Discussed in the blog are a few major advantages that can be reached by businesses and firms on switching to advanced analytics.

Benefits of Advanced Analytics
Enhanced decision making

Advanced analytics helps in delivering information in an organized, straightforward manner, allowing for fast data interpretation and response. With Advanced Analytics, Firms can handle large amounts of data thus making data oriented tasks get dealt easily.

Consider a manufacturing company deciding which electric-vehicle battery technology to invest in. This is not a small decision—the capital expenses alone would require investing billions of dollars, tying the manufacturer to a certain technology for many years. However the company’s executives would benefit from understanding trends in current and when a specific technology is likely to have a clear advantage. 

Sentiment analysis which employs trained algorithms to categorize news and social-media information based on the event or topic at hand, the companies involved, and the positive or negative sentiment associated with each. Companies creating plans can also use such analysis and other advanced analytics methods to gain timely insights into customer sentiment or reputational risk thus making wiser decisions for their firm’s upliftment.

GeakMinds helped a Fortune 500 Company manage huge amounts of log files from different sources and analyze issues in the logs. It was solved using the Advanced Analytics approach of Anomaly Detection on Microsoft Azure Platform along with Realtime data ingestion using Spark, and Kafka.

With the issues identified, they took improved decision making in near real time hence their customer satisfaction rates got increased.

Better targeting of audience

Understanding clients well will help a firm establish a successful brand by providing them with better products or services. There are numerous methods for understanding client behavior trends which include market research, online and offline surveys, past sales data, and so on. These generate a large amount of client data for businesses that traditional analytics cannot evaluate. This is where advanced analytics comes into play.

For example, an European CPG company has used Advanced Analytics on customer data to discover which SKUs were selling well in particular retail formats and which SKUs to swap in and out to better satisfy customer preferences. It is presently experiencing 10% sales growth in a low-growth category. And the potential impact isn’t only in sales: according to a recent McKinsey and MIT study, organizations that use big data and analytics into their operations beat their peers by 5% in productivity and 6% in profitability.

Greater ROI

The integration of data and advanced analytics presents numerous opportunities for companies. Companies can gain a more complete insight into consumer wants and views and more precisely define consumer categories in portfolio planning and product development, boosting their capacity to target the highest-value possibilities. They may calculate the return on investment (ROI) for marketing spending spent on both classic and emerging marketing channels (such as social media), allowing them to reallocate marketing spend to the most productive channels.

Take an example discussed in Mckinsey. One organization had to hire and retrain multiple translators to serve as a bridge between the business and IT at the start of its AI transformation because they had little fluency in AI. As the company’s proficiency in deploying AI grew over time, they were no longer in need of translators. Instead of training a large number of translators, the company now required a larger pool of specialists to capitalize on the organization’s data assets, develop its AI procedures, and implement more advanced initiatives. By concentrating critical mass where and when it was most needed, the organization was able to extract greater value from its investments, increasing AI-related ROI by 50% over three years.

Discover new opportunities for progress

Advanced analytics can also improve strategic planning by identifying growth prospects that would otherwise be difficult to identify, such as appealing industry areas and acquisition targets, new product or service concepts, or even new applications for existing items. 

A leading London stockbroker devised a Predictive Analytics application that examined the historical and present stock valuations. It improves the investor’s understanding and directs them to the best investment choice. Traders and portfolio managers may now make more accurate suggestions and investments with the help of this technology. Early spotting of excellent possibilities contributes to long-term lucrative returns. This was created by the data science team using advanced machine learning and cutting-edge massive cloud data technology. In the financial market, this is proving to be a major changer.

Thus the most effective of the Advanced Analytics techniques helps to interpret and uncover links that can help a firm find newer ways to achieve success.

Reduced Human effort

Firms which tend to spend larger amounts of money and time on works that can be automated or simplified through usage of technologies got a solution, thanks to Advanced Analytics.

GeakMinds helped a Fortune 500 Telecom company to manage text analysis. Previously, the firm had to manually sort through thousands of contracts, which took a long time. On the Azure cloud, OCR and NLP algorithms were used to tackle the problem. It allows clients to quickly find certain sections in contracts and verify invoices. Thus by deploying Advanced Analytics, human efforts and error percent got largely reduced.


The global advanced analytics market is predicted to increase from $248.0 billion in 2019 to $281.0 billion by 2024. It is thus evident that the growth of advanced analytics will reach an unprecedented level. So firms shouldn’t delay in deploying Advanced Analytics but use them as early as possible to attain business sustainability and growth.