All digital marketing efforts must be focused on user experience and one of the most effective ways is to rely on historically collected data to achieve this.
Obviously, when a marketing action is started from scratch we do not have this data, but if you have a very well defined and proven process to use as a starting point, the learning period about an activity can be considerably reduced.
Currently, there are many automatic functions in digital tools that use the history of data generated as a result of initial efforts as an engine, such is the case of the Data-Driven attribution model of Google AdWords, which needs a large amount of information (10,000 clicks and 1,000 conversions in a month) to be enabled. The data serves as a reference for the system to identify which of the factors to attribute how much value of a conversion. Later I will write a post that goes into more detail on the types of attribution models and the value they can bring as performance indicators for certain campaigns.
One of the most important practices to take into account during the management of marketing activities is the constant optimization of the digital strategy, taking as a reference the results obtained in a period of at least one month. For example, if in a first stage our SEM budget is distributed 50% for the search network and the other 50% for the display network and we can notice that some key indicator such as conversions is more in the Search campaign, we can allocate a higher proportion of the budget for this campaign.
Big Data platforms are other modern tools that help with decisions based on historical actions with which we can navigate through a large amount of data for subsequent segmentation and analysis, which helps to make the best decisions in a business.
At Avatar we take data-based optimization very into account, because only then can we obtain the best results to achieve the best digital strategy for our clients.
Database marketing is a form of direct marketing using databases of customers or potential customers to generate personalized communications in order to promote a product or service for marketing purposes. The method of communication can be any addressable medium, as in direct marketing. The distinction between direct and database marketing stems primarily from the attention paid to the analysis of data. Database marketing emphasizes the use of statistical techniques to develop models of customer behavior, which are then used to select customers for communications. As a consequence, database marketers also tend to be heavy users of data warehouses, because having a greater amount of data about customers increases the likelihood that a more accurate model can be built. There are two main types of marketing databases, 1) Consumer databases, and 2) business databases. Consumer databases are primarily geared towards companies that sell to consumers, often abbreviated as [business-to-consumer] (B2C) or BtoC. Business marketing databases are often much more advanced in the information that they can provide. This is mainly because business databases aren't restricted by the same privacy laws as consumer databases.