Has Big Data Adoption Slowed Down in the Pandemic Era?


big data
Spread the love

When the COVID-19 started showing its impact on the business entities, many global leaders speculated that the juggernaut of big data explosion would finally stop. To an extent, these leaders were proved right. According to a recent report, there has been a remarkable shrink in the investments pertaining to big data technologies even as investments have retracted to less than 2% in 2021 to what it was in 2019 and 2020. While some industries showed a significant appetite to adopt Big Data capabilities for their operations, there were many others that were left far behind in the race.  A lot has changed in the two years of the COVID pandemic and lockdowns that have directly impacted the investments and technological advancements that were supposedly going to take the businesses that depend on these capabilities to the next level. Market disruptions, security loopholes, cyber warfare, and economic slowdowns –were some of the important factors that affected the growth of Big Data and analytics in the last 2 years. But, nothing comes close to what the lack of top-quality retainable talented professionals did to the market. There are thousands of jobs available in big data companies that are lying vacant. Of which, 90% of the vacancies will never get filled because the candidates with Big Data Certification would never meet the right hiring managers and trainers who could influence their career paths.

While organizations have a clear strategy on what kind of Big Data they want to leverage to drive their Marketing and Sales pipelines, there is not enough human intelligence involved on the product and business analysis side that could influence the decision-makers to look into the real value of “data”, which is key to driving customer experience and customer service goals.           

See also  Five points to consider in hiring an assignment helper in Malaysia

Why does customer experience management require big data analysis?

Big Data Analytics is also referred to as BDA in the technology industry. BDA offers a very productive and competitive opportunity to differentiate products, services, and solutions. From a managerial perspective, the application of big data has emerged as the top trend that has allowed all kinds of businesses to integrate their Marketing, Sales, Finance, and Customer Services with traditional Information Technology and Applications development or DevOps.

Marketers rely on different types of Big Data belonging to the family of structured and semi-structured data. These data sources are carefully segmented based on their volume, variety, and veracity. BDA teams help to erect a culture of strong analytics and business intelligence that can be directly integrated into ongoing efforts for meeting challenges and opportunities in the digital economy.

Let’s understand the roles of BDA in customer experience management.

  • Big Data gets personal insights without crossing the “boundaries.”

There are different ways a brand tries to connect and engage with the customers, and likewise, customers also opt for different channels to contact an organization. For example, the email form of communication is considered to be the most authentic and secure compared to others. Marketers look at email inquiries with a lot more attention than social media comments or comments left on a contact page. In order to forge productive communication with the customers, brands invest in powerful business analysis tools that ingest big data from different sources such as website forms, contact forms, social media, call centers, emails, SMS, and other third-party data aggregators. In all these, to deliver a seamless customer experience to users, top-grade organizations use structured/semi-structured data analysis tools for integrated marketing communications.

  • Bringing Machine Learning to BDA
See also  What is force? Its types

Advanced big data analysis and monitoring activities allow these organizations with a strong big data foundation to chase down goals in automation and machine learning with unstructured data modeling and analysis.

This aspect of using Machine Learning for big data analysis is the biggest positive outcome that has emerged in the last 5 years. It is a trillion-dollar economy and the size is only going to grow further irrespective of how the global economy shapes up. So, big data marketplaces would continue to draw blood from this area of adoption centers.

  • BDA misses coherence in larger customer databases

According to Tech brighter 90% of the customer experience management efforts are automated – which means human tasks have been assigned to software-based automation processes. Simply put, from document processing activities to email marketing designing, everything can be automated. But, there are certain aspects of customer experience that require in-depth human engagement from the organization’s side. For instance, call service at the time of post-sales conversation. When companies try to use BDA to offset the human relations to machine learning applications based on assumptions that certain types of “inquiries” and questions can be very well managed by a set of workflows handled by machine learning, failure is inevitable. And, this is not the failure of the machine learning or BDA systems – but of the human decision-makers who thought this automation would work without effectively analyzing large customer databases. In customer experience management, coherence of BDA outcomes is very important and some organizations like Google, Amazon, and Alibaba show how big data intelligence can be productively used to turn the fortunes of not only the organization but also the partners and customers. This is called a coherent partnership ecosystem, and the emergence of Partnership Marketing is an outcome of this effort.

See also  Top 8 Benefit of Using Writing Journal in Student Life

Yes, despite so much space in the market, big data analysis and monitoring slowed down.

Currently, we are in a “technology plateau” that is based on the Dunning-Kruger Effect.

For big data, we have passed the phase of cautious adoption and now reached the plateau phase where investors and technology analysts more or less understand that BDA has outgrown its niche-targeted markets (adoption centers). That’s why you will find there is a lot happening in the emerging fields of IoT, blockchain, crypto, drones, computer vision, and deep learning compared to what’s happening in conventional business analysis and intelligence software domains. Certified big data professionals help identify newer adoption markets for BDA vendors.


Spread the love