Predictive analytics
What is Predictive Analytics?
Predictive Data Analysis or Predictive Analytics is the task that a company performs in order to foresee an outcome and act based on this data, being able to favor its occurrence (if it is positive) or avoid it (if it is negative). Basically, we could say that what is sought is to predict the future.
A correct predictive analytics strategy is developed at three levels:
Types of Campaigns
- Descriptive level: a general observation of all the data that is possessed.
- Diagnostic level: the cause of the events analyzed is established and, if a more in-depth analysis is desired, patterns can be looked for.
- Predictive level: predictions are made of what could happen based on the analysis of the data collected.
- Prescriptive level: establish what will be done to stimulate the event or avoid it.
- It is important to note that this type of analysis is carried out by strictly following a series of steps. It is also essential to know very well what the objective or objectives are and the strategy that is intended to be carried out to achieve them. In order to see the expected results, you will have to follow this method step by step:
1-Knowledge of the business: here we talk about the strategy to follow according to the sector in which you operate.
2-Knowledge of the data: we must know what we are looking for, determine what data will help us achieve it and discard everything that does not lead us anywhere.
3-Creating a model: here it will be convenient to create a synoptic diagram or table indicating the objectives we pursue and the means by which we will carry them out.
4-Putting into practice: with all the work done, we will put our strategy to work.
What is Predictive Analytics used for?
All this allows a company to develop a profitable business model. For example, it is possible to detect the imminent depletion of a certain stock and launch a campaign to promote another product that we do have in greater quantity. Predictive analysis has several functions and we will need to know exactly what problem we want to solve in order to know exactly what questions we want to ask the data.
With good predictive analytics we can: reduce costs, reduce time and collect valuable information.
Examples of Predictive Data Analysis
A clear example of predictive analytics is the on-demand audit service offered by Daimatics.agency. In this process, the agency is responsible for collecting all the historical data from your website and defining an SEO budget that is in line with the needs of your project. Among this data, predictive techniques are used to know what to expect over time and how to act based on this knowledge.
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