Marketing strategies and Data Scientist: a union that promises

Data analysis is not an exclusive strategy for large companies, SMEs can also use big data to their advantage.

But how? The answer lies in the figure of the data scientist , the professional who is in charge of finding solutions based on data analysis and who, therefore, is essential in the marketing department of a data-driven company .

The use of data in business

The technological advances of the last decades have allowed brands to be closer than ever to consumers and to know many more details: the location of customers, their state of mind, their family and work situation … And all this in real time. Today, brands can know everything related to customer behavior and the aspects that will define their decision-making at the time of purchase .

Thus, an organization can have very valuable information about its customers, but not take advantage of it or, rather, not know how to make that data speak. The data, by itself, does not provide answers, it must be analyzed with the appropriate techniques by qualified professionals to be able to translate it into effective marketing campaigns. The data will tell us when the marketing strategies are working .

Data analysis: the undisputed protagonist in marketing strategies

Breaking silos: let the information flow

Many vertically organized companies are, perhaps unknowingly, hindering the intelligent use of data. The fact that each department has data and cannot share it with the marketing strategy department, for example, makes analysis difficult and therefore the possibility of conversion.

Let’s take an example. Suppose a company’s marketing strategies begin with a simple email newsletter. Knowing who you are being sent to and being able to segment is key for this action to be successful. However, the sales team does not share the lists of customers and / or potential customers or the state in which they are and, therefore, the marketing department must start from scratch to attract, retain, retain … It can also happen Although the company has machine learning models that value this potential for leakage, they do not end up communicating well all the high-value information that they actually generate. If only one of the two marketing or sales areas had access to those results, or knowledge would be stuck in a sub-area of ??”business intelligence” or “customer analytics”.much more intelligent use of data and even information already processed, which would save resources and benefit conversions .

Constant updating of data

A database is a very powerful weapon. However, if it is not up to date it is of no use. We need data in real time to be able to act as soon as possible, and even predict the action. For example, it is useless to launch an insurance leak campaign to clients who have already asked to unsubscribe, we will have to analyze if they are already asking for quotes from a competitor, if they are satisfied or not, if they have had parts and incidents to, with time enough – two months for example – to be able to offer you an alternative that will make you loyal and prevent you from escaping.

Perhaps we can base our marketing strategies on giving prominence to last year’s best seller . But what if fashion has changed? If the information is up-to-date, it is possible to react in time and invest resources optimally .

Investment in technology

As we said at the beginning of the article, the possibility of using data for the benefit of companies would not be a reality if the technological advance that we have experienced had not existed. And it is that, in reality, data and technology go hand in hand, since data cannot be collected without technology.

To expect departments to analyze data manually is to take steps in the opposite direction to success. Investing in programs and applications to automate and monitor information is key .

The ‘data scientist’ and its importance in the organization

Given this obvious potential for the use of data, it is essential to have qualified personnel to analyze and untangle the tangle of information. In this context, the figure of the data scientist emerges : the link between information, the consumer and the brand.

The connection between data science and marketing results is indisputable. The direct impact we see on business results fully justifies the investment in both resources and budgets . Thus, knowing how to analyze and translate information should be a priority for the marketing department. For this reason, the companies of the present and of the future must have the most sophisticated analysis tools and the presence of the data scientist .