Predictive analysis of consumer behaviour with the aid of emerging technologies

Businesses run on what their customers want.

Every business may have a social presence, but in today’s world where digital media influences consumers, it is more important for businesses to have a social conscience. You don’t need to ask questions to generate consumer insights. You just need to harness the insights from the huge pool of data your customers leave you with. 

According to a recent report by Forrester, “By 2021, Insights Driven businesses will be generating $1.8 Trillion annually.”

For businesses to be ‘Insight-driven’, market research is the trump card that is revolutionising the art of generating consumer insights. With digitisation, consumers have made their personal information vulnerable over cloud and social media platforms, which has provided the market research industry with a huge pool of data about their consumer base.

With the advent of technologies such as machine learning, augmented reality (AR), and Internet of things (IoT), market research awaits a promising and streamlined future. The fascinating topic of discussion here is how.

  • Augmented Reality (AR)

Through AR, businesses can virtually review the feasibility of their business strategies in a real-time user environment. This enables them to identify their most feasible solution and analyse how each solution is different from the others.

What is AR?

AR is a huge revolution across industries especially Retail and Healthcare as it focuses on providing customised options as per user’s needs.  It is a powerful technology that enables infusion of visual content or graphics in a real-time user environment within a software application.

Why is AR everyone’s go-to?

Because it provides real-time user interaction!

Imagine the level of satisfaction a customer experiences when they would be provided with the concept of virtual fitting rooms! A recent concept that JC Penney came up with resulted in a significant boost in both their sales and the Customer Experience Index (CXI).

This technology is helping market research agencies identify their improvement areas without even physically analysing them.

The technology focuses on eradicating language barriers associated with market research in diverse geographies, enabling much more qualitative consumer insights.

  • Internet of Things (IoT)

With businesses focusing more on online sales than physical brick-and-mortar store sales, market research relies heavily on consumer behaviour analytics.

Through IoT, market research can now measure and predict consumer behaviour by tracking and recording patterns through which consumers interact with devices.

What is IoT?

IoT is an extension of the internet in everyday devices, which allows interchange of data via interconnected devices over a network. The technology is made by a blend of various technologies such as machine learning, real-time analytics, and commodity sensors.

Why IoT?

IoT has enabled businesses save a lot of time on secondary research as it keeps a track of consumer data on its own. With the technology eliminating human bias, qualitative research expects a refined level of quality in qualitative insights.

 IoT applications optimise inventory tracking and management remotely without any physical human presence, which leads to better resource management and increased productivity for businesses.

Amazon recently came up with a new application Amazon Go that is based on IoT. When consumers pick a product in retail stores, the sensors on the clothes update the application with the items in the cart, and the price is deducted from the Amazon wallet during the checkout. This led to a huge increase in customer satisfaction and enhanced its customer lifecycle values.

  • Machine Learning

The face of market research has now changed by this technology as it can predict consumer behaviour and customer lifecycles by identifying hidden insights without even being programmed to do so. This is the technology that aims to make organisations customer-centric.

What is Machine Learning?

 It is a subset of Artificial Intelligence. Machine learning uses a mathematical algorithm to identify important insights from a huge database.

Why Machine Learning?

Through data mining and data segmentation techniques, machine learning is helping market research companies with predictive maintenance, customer retention, and satisfaction.

Recently, Nielsen came up with a report where they invested in Machine learning to predict future TV ratings. Machine learning is providing businesses with time-saving options at minimal investments, and even SMEs (Small and Medium Enterprises) are looking to adopt this technology.

It is very important for businesses to understand their consumers, draw patterns about the consumer lifecycle and implement changes that satisfy their customers.

Generating consumer insights has always been a mandatory ask for the market research industry. With these technologies eliminating human bias, saving time and continuously improving business strategies, the future of market research looks promising more than ever.

Sources:

[1]https://www.forrester.com/report/InsightsDriven+Businesses+Set+The+Pace+For+Global+Growth/-/E-RES130848


[2] https://www.strategy-business.com/article/00073?gko=3559e


[3]https://www.forrester.com/report/InsightsDriven+Businesses+Set+The+Pace+For+Global+Growth/-/E-RES130848


Pulkit Pillai
Pulkit Pillai
About the Author

Pulkit has rich experience in conducting quantitative and qualitative analysis within the market research field.
He is passionate about market research across various verticals and couples this passion with writing to discuss expert insights.

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