A new approach to data collection can be the key to a successful marketing strategy.
The world has seen the rise of Big Data. Collectively, we are generating a tremendous amount of information; and as our most complex systems become smarter and more powerful, they depend on this vast assemblage of statistics to continue learning and become better at finding meaningful insights. Vinay K Mayer, Director – Marketing Research & Consulting @ Asia Research Partners LLP, provides a deep dive into new ways to collect data.
The world is increasingly becoming a digital place where Data Collection is essential for growth in different sectors. Most enterprises depend on the continuous flow of data to make informed decisions, as it drives more development and innovation. However, there exist several barriers that prevent organizations from the smooth collection of relevant data. Enterprises need to collect relevant information without fail without having their operations affected. It’s important to consider big data management techniques that allow organizations to get audited consistently and securely without breaking privacy laws.
Filling the gap between Data Usage & Collection
Big data is shaping up to be the next big thing in the technology industry. The power of big data is being leveraged across a variety of industries, from healthcare to retail to e-commerce, aviation to business intelligence. With the world going digital, it is estimated that the BDA market will reach a value of $68.09 billion by 2025.
How AI-powered data collection changes the game?
Machine learning is a subset of artificial intelligence (AI) where computer systems autonomously improve at performing specific tasks by analyzing large amounts of data with complex algorithms in it. This means the computer is capable of improving its performance over time, without needing to be directed by an outside party. The report predicts that 70% of organizations will shift their focus from big to small and wide data by 2025. It’s not something that can happen overnight but rather one that will take years to achieve. Not only does this development open up numerous opportunities for companies, but it also requires a new way of approaching monetary investments in research and development for the industry to produce enough data scientists to cope with demand.
Different Methodologies
The outbreak of the COVID-19 virus led to a major fall in the worldwide economy. As a result, marketers started using various strategies and tactics like monitoring consumer behavior as they searched for the best way to respond to an increasingly volatile economic climate. The future will belong to digital natives who will rely on research methods like ethnographic studies, focus group interviews with customers and message boards that they can study cold hard data—both internal analytics and search query histories and e-commerce data insights are the most promising ways to get that hard data. In addition, more and more companies are now relying heavily on tracking social media networks like Twitter or Facebook to glean information about their customers through usage patterns which can show whether or not people have liked a product’s page for example. However, we have to contend with problems like data credibility.
In a nutshell, data collection is a significant problem. It’s not a trend or buzzword; it’s a vital concern. In the past, complexity was the enemy of quality. Generally, the more complex a system is, the more difficult it is to maintain. The flip side is that in the future, this same complexity will be required for success through big data applications. We will be able to collect more information in many more ways than ever before, but, we can use this information to identify trustworthy insights into systems across all areas of business and industry, from customer preferences to sales patterns and product life cycles just to name a few.
Author: Vinay K Mayer, Director – Marketing Research & Consulting @ Asia Research Partners LLP
