We can define machine learning as a discipline related to artificial intelligence. It tries to carry out learning for classification and behaviour prediction tasks through similar behaviours or patterns.
These actions are carried out through machine learning algorithms (yes, the famous algorithm. You have undoubtedly heard it several times).
The Fusion of Artificial Intelligence and Marketing
About all that has been said, as digital marketing professionals, we continually hear from the voices of the leading advertising platforms that we should let their algorithms learn to manage our campaigns. In this way, you find the necessary circumstances to optimize the ads in the best possible way.
This, although proven to work, tends to frustrate us since we like to be in control. At the same time, we also want to have as much information as possible and be able to manage our data based on our own learning and knowledge.
Machine Learning in Digital Marketing: Is It Possible for Everyone?
This is why studying machine learning for implementation in our work can be interesting. In such a way, we are the ones who use an algorithm that allows us to classify or make a future prediction about our investment in advertising and possible results.
Here is all I can say: Can anyone learn notions to implement machine learning actions in their digital marketing tasks related to advertising? Yes, definitely. Be careful; this is not mandatory.
Each person has a professional profile and speciality. However, it is always interesting to be able to rely on all the tools that can help maximize the value of our work.
The important thing is that you understand the procedure of action. You can rely on specialized departments with technical profiles that carry out programming tasks that may escape you.
Many people fear artificial intelligence because they see it as a substitute for their work. However, an AI will never be a human since a human knows what questions to ask at any given time. From there, you can rely on this tool to facilitate or speed up a process. This could never (or at least cannot) happen the other way around.
Practical Benefits of Machine Learning in Digital Marketing
What exactly can this help me with? Too many things.
- Segmentation: Imagine that you download your database of customers, web visits, sessions, purchases, etc… By applying a classification algorithm, you can create precise lists that distinguish customers by different types (price range, specific products ).
- Customer rating: By the above, we can divide the best and worst customers according to their behaviour. From here, many actions can be carried out, from showing different advertisements, discarding actions, or even improving them.
- Purchase or profit forecast: Using regression algorithms and historical data, we can even make an approach. And forecast how much we could sell in the following year.
- Recommendation systems: When a user with specific characteristics lands on the web, we can show them a particular product through the associations created from their behaviour.
We could discuss many things, from classifying algorithms between supervised and unsupervised. The distinction between, for example, the known or the decision trees, or perhaps about the necessary programs and the programming language required to apply them. However, today, we are lucky to have multiple training courses with hours of learning adapted to many levels.
