Cognitive Computing and the Age of Virtual Reason

August 23, 2017


Get inside the mind of your consumer with cognitive computing.
Artificial Intelligence was once considered a futuristic concept, but with the advent of cognitive computing, that future is now. As a self-learning system, cognitive computing can make sense of large swaths of consumer data to help businesses make more informed decisions and improve their capabilities.

The Current State of Retail

Our retail market has undergone unprecedented change. Globalization and advances in technology have transformed consumer behaviour, created new channels and product categories, and opened doors to international markets. The speed with which things are changing coupled with the sheer amount of available data can result in missed opportunities and slow-moving businesses.


Evolving Consumers
Consumers are progressively moving online, especially through their smartphone devices, when making purchasing decisions. In fact, a digital device will influence 50% of consumer purchases at retail ¹. Consumers are also demanding increased interactivity so that they can control when, where, and how they connect with a brand and its products. Consumers have come to expect a highly personalized shopping experience, forcing brands to look for new ways to customize their communications to the individual shopper.


Evolving Technology
Constant technological innovations and upgrades can make it difficult for businesses to stay current. With greater reliance and access to technology, marketing strategies must leverage the correct online platforms to engage their customers. Growth in technology can also mean higher possibilities of fraud and security threats, pressuring brands to find security measures or risk losing consumer loyalty.


Evolving Markets
Increased competition, rent inflation, and globalization are all factors that put pressure on margins. Businesses are forced to prioritize all incoming data to maintain competitive advantage and adapt to the changing marketplace.

How to Stay Ahead of the Shift in Retail?

Business data is estimated to double every 1.2 years, and is set to become increasingly complex ². Agility and efficiency are critical to addressing the changing retail landscape, but human beings simply do not have the ability to go through every piece of information to develop the most optimal solutions. Traditional analytics have their limitations as well. These analytics can provide a broad snapshot of the past and present situation but are unable to turn this information into future insight.

Cognitive computing takes the best of both traditional data analysis and human thinking, to create a computerized model that can mine enormous amounts of data and mimic the human thought process. Cognitive computing can also build on its own knowledge, make intelligent connections from ambiguous information and patterns, and communicate in natural language that doesn’t require specialized technological knowledge to understand.

Consumer Implications
Cognitive computing can find patterns in a consumer’s personal online behaviour and combine it with information pertaining to general market conditions. Not only does this facilitate a hyper-targeted approach, this data also helps to develop actionable insights and growth opportunities, and identify existing customer concerns.

Technological Implications
As cognitive computing is constantly building its knowledge, it can find the best systems, devices, and platforms to deliver personalized communications to the individual user. With the assistance of cognitive computing, campaign and promotional dollars can be used most effectively. It can also uncover security threats to the businesses, thereby increasing consumer confidence.

Market Implications
Through analyzing market conditions and economic patterns, manufacturers will have a better idea of where and how to compete. Cognitive computing delivers real-time observations to allow for quick and strategic decision-making.

To effectively implement cognitive computing into your business model, define what success looks like, prepare for success by dedicating enough human capital to feed the system with all necessary information, and maintain cognitive computing’s success through ensuring both business processes and people support the system.

What strategic goals can cognitive computing address in your company? Tweet us @stjoseph with your thoughts.



1. Deloitte
2. ATKearney

Now, tell us how we can help