We define marketing strategies to achieve business objectives. We analyze the behavior of our audience, find how it interacts with our brand, define the strategy and launching a series of actions to achieve the objectives. In this process we must make many decisions based on data. Decision-making in current marketing We are aware that we will never have all the information we need to get our decisions right. The number of variables that affect the outcome is so great that it would be impossible to achieve. That is why we try to stimulate the best decisions possible based on the data we have. To do so we have multiple sources of data, so many that we have troubles to assimilate all information and become it into knowledge for the company. In the context of online marketing we typically handle data file such as: surveys, databases, campaigns, web, social networks, etc, but this is only a small part of the data that we are capable to take into account to stimulate the best possible decision. Use big data to optimize marketing strategies The more unstructured the data source is, more difficult the analysis is. We are talking about big data, of its three V’s: data that are created at a great Velocity, are unstructured (Variety) and are generated in large quantities(Volume). When we talk about inserting big data in decision making, the most sensible recommendation is for the company to take control of the data it currently manages( Basic data ) to continue to optimize the online channel( Small data) and to consider the Step or not to the big data. In this context of the analysis of the big data, its used only for make business decisions (in terms of marketing, patently its applications are numerous) is when cognitive technology takes on importance. Big data and cognitive computation Including unstructured data in decision-making is very complicated. If we add that 80% of the information collected has not been encoded in language( so our systems can read it) and is in formats that our systems are not able to interpret, it is “invisible” info for our company. What is cognitive artificial intelligence or cognitive computing? Seeking for sources of information to illustrate this article, the definition that I liked the most was Cognitiva (IBM partner): Definition of cognitive computing “Cognitive computing is described as a new type of technology system that understands the world like humans do: through the senses, learning and experience. Cognitive systems continually learn through each interaction and with each new part of information and thus gain value and knowledge over time.” What are the phases of the functioning of cognitive technology? Understand Watson has the ability to read the equivalent of 1 million volumes per second. The more information he process, the more powerful his response will be. This technology reads the data and construes it use the natural language, in addition to understanding them, is able to detect intention, feeling, etc. To understand us, it would be the evolution to the nth power of the listening software in social networks. To reason Once you have processed the information, you group the data according to their relevance, then utilize a series of algorithms to stimulate hypotheses so you can compare them with the actual data you know to determine which is most likely. When you come up with this most likely hypothesis, it also gives you the contentions on which it is based in order to be allowed to evaluate the answer. To learn Based on the decisions made and their results, Watson discovers. And with each interaction it becomes smarter. This is how humans become experts in one area. We understand, reason and learn. Applications of Cognitive Technology to Internet Marketing As you have seen in the video the applications are immense. From medicine, to overseeing an oil rig,… is something incredible. But what if we could use this data in marketing decision-making? What would happen if we could combine our present sources of information with this technology and all that “invisible” info? Optimize paid media campaigns, by analyzing structured and unstructured data to detect these components that most influence the acquisition decision and using them to launch targeted ad. This is applicable to all manner of campaigns: showing, Adwords, social ads, etc. Know and understand our audience: being able to interpret all kinds of data, we can take what is spoken in social networks and blogs about our product and brand, calls received in the bellow centre, …( any source of information that contains feelings of our audience) and investigates it. For: Define your audience profile. Know the reasons to choose one product over another. Find out what they are looking for (to launch a product that fits their needs). Knowing the impact of an external factor( period, for example) on buying behaviour, Improve the conversion of our website: Identify the most common client travels and interactions (micro conversions) that most influence your purchasing decision. Develop automated systems that allow natural interaction with our audience. This is directly related to the posts I have written about chatbots and also with the ability of brands to influence our audience in surroundings where brands have limited access. Develop a smart product advisor. You insure the possibilities are almost endless.