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.
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.
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.
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.
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. 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.
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. 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. […]