Cognitive computing is the girl-next-door for marketers.
The rise in big data, artificial intelligence, and programmatic advertising makes cognitive computing a necessary knowledge base.
According to Tech Target’s What ls database, cognitive computing is defined as:
The simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works.
Simply put, cognitive computing is a process based on machine learning technology and artificial intelligence that performs human-like tasks in an intelligent and effective manner.
Impact of Cognitive Computing on Marketing
Cognitive computing and cognitive systems are paving the way for a new era of computing. First generation computer models represented the first era of computers developed during the 1900s. These computers could tabulate sums within seconds. The second era came during the 1950s with programmable systems. Some people say that cognitive computing as we know it today represents the third era of computing which involves disruptive technologies aimed at efficiency.
Cognitive computing systems are ready to disrupt industries including marketing. As a marketer, it becomes essential to keep up with the latest trends and to make actively apply them to your marketing strategy. If you’re on the edge of this technology, below is an in-depth summary to understanding cognitive computing:
The term “Cognitive Computing” is derived from the words cognitive science, meaning the study of the human brain and how it functions, as well from the words computer science, which is the study of computer programing. The possibilities for cognitive computing are limitless, and the idea is that it is just beginning.
How Cognitive Computing Works
Cognitive computing combines several functions to produce the best results. These functions are:
- Natural language queries and processing
- Machine learning algorithms
- Real-time computing
- Preset Artificial Intelligence data
Cognitive computing thrives on data and machine learning. It uses data to analyze patterns and trends. Hence, the more data the machine can derive, the more efficient the interpretations and analysis.
Prerequisite Features for a Cognitive System
To ensure successful implementation and high results from your cognitive computing system, it is important that the system contains the following features:
1. Adaptability: The idea is to ensure long-term sustainability of computing software. Therefore, the system must be able to accept dynamic data of different varieties and interpret variables as they are presented.
2. Interactive: The system must be able to easily interact with users so they can define their needs accurately. It must also interact well with processors, devices, and cloud services.
3. Stately: The system must be able to gauge the quality of data and the various methodologies to be used for interpretation of such data. This is important as it helps deliver reliable and updated results.
4. Self-learning: The system must be able to understand, identify, and extract elements such as meaning, syntax, time, location, appropriate domain, regulations, user profiles, process, task, and goal from the data available.
“As machines take over, people will lose their jobs.”
A very common myth that many believe is that as more tasks are taken up by machines, people will eventually lose their jobs. However, cognitive learning is not a replacement, but a “more efficient” assistant to people.
Let’s take for instance customer X. If his financial agent can gather all his data, from his travel and commute history to his credit score, a cognitive computing system can create a transparent 360-degree view of customer X and analyze different patterns and trends and generate reports. Based on the reports, the agent can tailor and provide his services accordingly. Effectively, the system facilitates better results as opposed to taking away someone’s job.
Several new and established companies are heavily investing in machine learning and artificial intelligence to develop better products, services, and subsequently, gain a greater market share and boost profits.
As of now, the cognitive computing market is dominated by large players like IBM, Microsoft, and Google. IBM, being the creator of this technology, has invested about $26 billion in the development of this project named Watson. As computers becoming increasingly programmed to think like humans, they will help to expand our knowledge and increase efficiency and productivity and amazingly new ways.