Is analytics based on Big Data and artificial intelligence already capable of predicting what we will think about tomorrow, that we need something, that we should perhaps buy something we think we need?
Can an AI-equipped internet robot using the results of research carried out by Big Data advanced socio-economic analytics systems and employed in the call centre department of a company or institution already forecast, in real time, the consumption and purchase needs of a specific internet user on the basis of a conversation with a potential customer and, on this basis, offer internet users the purchase of an offer of products or services that they themselves would probably think they need in a moment?
On the basis of analytics of a bank customer's purchases of products and services, analytics of online payments and settlements and bank card payments, will banks refine their models of their customers' purchase preferences for the use of specific banking products and financial services? for example, will the purchase of a certain type of product or service result in an offer of, for example, a specific insurance or bank loan to a specific customer of the bank?
Will this be an important part of the automation of the processes carried out within the computerised systems concerning customer relations etc. in the context of the development of banking in the years to come?
For years, in databases, data warehouses and Big Data platforms, Internet technology companies have been collecting information on citizens, Internet users, customers using their online information services.
Continuous technological progress increases the possibilities of both obtaining, collecting and processing data on citizens in their role as potential customers, consumers of Internet offers and other media, Internet information services, offers of various types of products and services, advertising campaigns that also influence the general social awareness of citizens and the choices people make concerning various aspects of their lives. The new Industry 4.0 technologies currently being developed, including Big Data Analytics, cloud computing, Internet of Things, Blockchain, cyber security, digital twins, augmented reality, virtual reality and also machine learning, deep learning, neural networks and artificial intelligence will determine the rapid technological progress and development of applications of these technologies in the field of online marketing in the years to come as well. The robots being developed, which collect information on specific content from various websites and webpages, are able to pinpoint information written by internet users on their social media profiles. In this way, it is possible to obtain a large amount of information describing a specific Internet user and, on this basis, it is possible to build up a highly accurate characterisation of a specific Internet user and to create multi-faceted characteristics of customer segments for specific product and service offers. In this way, digital avatars of individual Internet users are built in the Big Data databases of Internet technology companies and/or large e-commerce platforms operating on the Internet, social media portals. The descriptive characteristics of such avatars are so detailed and contain so much information about Internet users that most of the people concerned do not even know how much information specific Internet-based technology companies, e-commerce platforms, social media portals, etc. have about them.
Geolocalisation added to 5G high-speed broadband and information technology and Industry 4.0 has, on the one hand, made it possible to develop analytics for identifying Internet users' shopping preferences, topics of interest, etc., depending on where, specifically geographically, they are at any given time with the smartphone on which they are using certain online information services. On the other hand, the combination of the aforementioned technologies in the various applications developed in the applications installed on the smartphone has made it possible, on the one hand, to increase the scale of data collection on Internet users, and, on the other hand, also to increase the efficiency of the processing of this data and its use in the marketing activities of companies and institutions and the implementation of these operations increasingly in real time in the cloud computing, the presentation of the results of the data processing operations carried out on Internet of Things devices, etc.
It is becoming increasingly common for us to experience situations in which, while walking with a smartphone past some physical shop, bank, company or institution offering certain services, we receive an SMS, banner or message on the Internet portal we have just used on our smartphone informing us of a new promotional offer of products or services of that particular shop, company, institution we have passed by.
In view of the above, I would like to address the following question to the esteemed community of scientists and researchers:
Is analytics based on Big Data and artificial intelligence, conducted in the field of market research, market analysis, the creation of characteristics of target customer segments, already able to forecast what we will think about tomorrow, that we need something, that we might need to buy something that we consider necessary?
Is analytics based on Big Data and artificial intelligence already capable of predicting what we will think about tomorrow?
The text above is my own, written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems such as ChatGPT.
Copyright by Dariusz Prokopowicz
What do you think about this topic?
What is your opinion on this subject?
Please answer,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz
I couldn't resist and asked the AI (ChatGPT) itself (translated with another AI - Deepl):
What does humanity think about the future?
Here's „her" answer:
As an artificial intelligence, I have no way of knowing the opinions and beliefs of everyone in the world. However, it is common knowledge that humanity has different ideas about the future.
Some people are optimistic and believe that humanity will be able to solve many of its problems and create a better future. They believe in advances in areas such as technology, science, medicine, and education that will help improve people's standard of living and create a more sustainable world.
Others are more pessimistic and fear that humanity is headed for a bleak future. They see problems such as climate change, economic instability, political conflict, social inequality, and technology dependence as serious challenges that must be addressed to ensure a positive future.
There are also many different visions of the future. Some believe in a future characterized by technological advances and advances in space exploration, while others focus on a future characterized by environmental sustainability, social justice, and peace.
Overall, there are many different opinions and perceptions of the future, and the actual future will likely be influenced by a variety of factors, including political decisions, economic conditions, technological development, and individual choices.
The short answer is no. I don't believe AI models are yet completely capable of it. When your social media platforms use recommendation systems and make suggestions for content you aren't really interested in, you can tell it is not accurate. However, once more of our systems and transactions are automated, it will be able to predict with more accuracy. Although people are not always predictable, you can predict general behaviors or events by looking at your Google Calendar or Snapchat memories.
Michael Domsalla asked chatGPT so I thought I would ask it too.
The Question:
Can AI models trained at Walmart marketing department predict its future customer behaviors?
The answer:
Yes, AI models trained in Walmart's marketing department could potentially predict future customer behaviors. Walmart has access to vast amounts of data about its customers, including purchase history, browsing behavior, and demographics, which can be used to train machine learning models. These models can analyze patterns in the data and make predictions about future customer behavior, such as what products they are likely to buy and when they are likely to make a purchase.
There are several ways in which Walmart could use AI to predict customer behavior. For example, it could use machine learning algorithms to identify patterns in customer purchasing behavior and use these patterns to make personalized product recommendations. It could also use predictive analytics to forecast demand for different products and optimize its inventory and supply chain accordingly.
It's worth noting, however, that no predictive model is perfect, and there is always some level of uncertainty and risk involved in making predictions about human behavior. Additionally, there are ethical considerations to take into account when using customer data for marketing purposes, and it's important to ensure that any AI models used by Walmart are transparent, fair, and protect customer privacy.
Predicting individual thoughts and opinions is a complex task due to the inherent complexity and subjectivity of human cognition. Thoughts and opinions are influenced by a myriad of factors such as personal experiences, values, beliefs, cultural background, and individual idiosyncrasies. These factors create a highly nuanced and dynamic landscape that is challenging to capture accurately through data analysis alone.
While analytics based on Big Data and AI can provide valuable insights into general trends and patterns, predicting individual thoughts requires a deep understanding of the context and personal factors that shape an individual's thinking. AI algorithms typically analyze historical data to identify correlations and patterns, which can be useful in predicting collective behavior or trends at a broader level. For example, analyzing social media data can help identify sentiments about a particular topic within a given population.
However, predicting individual thoughts requires accounting for unique and specific circumstances that can significantly impact an individual's perspectives. These circumstances may not be adequately captured in the available data sources or may change rapidly over time. Furthermore, individual thoughts and opinions are not solely influenced by external factors but are also shaped by internal cognitive processes that can be highly subjective and difficult to quantify.
Another challenge lies in the interpretability of AI algorithms. While AI can make predictions based on complex models, explaining how those predictions were generated can be challenging. This lack of interpretability makes it difficult to gain a deep understanding of the underlying factors influencing individual thoughts and opinions, limiting the reliability and trustworthiness of such predictions.
It is important to note that the field of AI is rapidly advancing, and new techniques and approaches are continually emerging. Researchers are working on developing more sophisticated models that can better capture and understand human cognition. However, the ability to predict individual thoughts with complete accuracy still remains a significant challenge.
In summary, while analytics based on Big Data and AI can provide valuable insights and predictions at a collective level, accurately predicting individual thoughts and opinions is a complex task due to the multifaceted nature of human cognition and the limitations of available data sources. While advancements are being made, predicting individual thoughts with certainty remains beyond the current capabilities of AI.
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