Advanced Predictive Analytics: AI is predicting Consumer Behaviour

artificial intelligence predicting consumer behaviour

In today’s world, where IoT is in trend and companies are making use of it for their profit, how IoT and AI drive the future of customer experience and reveal valuable customer insight on a real-time basis to predict consumer behaviour.

With the evolution of Big Data and Deep Learning in AI, the prediction has become as easy as ABC for marketers, on what customers want even before they need it. Deep learning has the potential of predicting consumer behaviour, it is a machine learning process which uses neural networks to learn skills and solve complex problems faster than human, and it is remodeling the future of marketing.

What is Big Data? 

Big data is a word that describes the large volume of data, both structured and unstructured, which is complex to be processed and analyzed efficiently and effectively using traditional methods. Characteristics of big data are volume, variety, velocity, and variability, and analysis happens for the insights that lead to more reliable decisions and strategic business moves. 

Prediction outcome is the combination of both human and technology, as AI evolving capabilities needs both types of intelligence to figure out future actions that impact positively on the business. 

Prediction Level:

Success in today’s business world is on the shoulders of customer experience, and AI predicts consumer behaviour using historical customer experience data and patterns. Let’s cover the different levels of prediction:

Understand Emotions:

Collection of consumers feedback and a reliable solution for unstructured feedback mining is the first level. In the first step, the machine identifies customers’ emotion behind any comment or experience from the in-depth insight of past feedbacks. After the segmentation, the next step is to identify the patterns and trend spot.

Identify Pattern:

Aggregating the data and recognizing the pattern or trend spotting in structured or unstructured data to predict customer behaviour is the next level. This process uses the data of your organization and identifies the pattern or trend in them that impact specific business outgrowths.

Advanced Predictive Modelling:

The final level is the ultimate goal for any business, using a predictive model based out of previous customer experience data to enhance the customer journey and business growth. With the advanced predictive modelling and future predictive actions, you can determine the points of trade in a customer journey for better results.

The neural network model (Dynamic Pricing) defeats the conventional stepwise analytics and produces more substantial business value by making better decisions in regards to the pricing of the product. The element of a neural network which opens the path to noise ratio of information is one critical factor, why AI can deliver advanced performance model.

Much research already has happened in this area for adjacent efforts to employ AI in a non-big data environment. Explanation of neural network or deep learning is not easy as pie, even though it won’t go any soon from the market.

Social media is turning into an essential tool for observing customer needs, satisfaction, dissatisfaction, and overall response. Based on the data accumulated from AI analytics, businesses can effortlessly improve a product or service, or introduce a new and more reliable one collectively.

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