MOOCS Comunicação em Mídias Digitais - 05 - Machine Learning atualizado

Hello again, let’s now talk about Machine Learning. What is that? As the name suggests, it’s the ability that robots, machines, and AI have of learning on their own.

It’s not really on their own, they learn from our usage. We talk a lot about algorithms, that is, the more we use a particular app or shop with our credit card, and the more other users have purchased similar products to ours, and have similar attitudes, machines have the ability of comparing these behaviors, and of learning and predicting. There are many expressions related to Machine Learning, such as Predictive Analysis.

Many companies can perform data analysis and predict likely scenarios based on consumers’ similar behaviors on platforms like Amazon and supermarkets or apps and streaming services. Think with me that different clients that watched the same films on Netflix were also interested in others. The machine learns on its own making these types of comparisons.

So, nowadays, many strategic marketing actions are dictated by the data. Let’s look at some examples of what’s happening and what could happen. Just reminding you that this module is based on concepts.

It’s for us to begin thinking about concepts and important scenarios to later move on to applications and what we can do with our own brands. Let’s talk about cookies. Cookies are the crumbs, the tracks we leave on the networks, and that machines use to solve different problems.

On Amazon, for example, every time I shop on platforms like Amazon, the following message appears: “keep shopping. ” It knows that for some reason I left some products in the shopping cart without buying them at that time. It tells me: “Continue from where you left off.

” These are some expressions we see on these platforms. “Inspired by your shopping interests. ” The machine learns that as I bought some products, I might like other similar ones.

This greatly expands companies’ sales capacity; they use data intelligence to boost their sales. “Frequent rebuys. ” They know that if I buy a particular product once a month, I may have forgotten to buy it this month, and they will indicate me to make that purchase again.

It’s a type of “frequent rebuy”, made by me or other users as well. There is also “Buy again. ” It thinks that if I have liked a perishable product, I may want to buy it again.

Imagine you have bought iPhones from generations X, Y, and Z, and a new one has been launched, and the machine knows that every two years people tend to change their phone, it will also give you this suggestion. That is, the machine learns on its own, and clients also buy. In the case of Netflix.

Netflix tells me: “Continue watching as Claudio. ” It reminds me. Sometimes we watch a series and stop in the middle.

It indicates, it knows where we stopped, out of ten episodes, in ten different series. It shows you your list, it shows you what you can watch again, and it shows “main choices for you. ” The main choices for me aren’t based solely on my use of the algorithm.

It compares with all the other Netflix viewers that watch similar things, and they know that these choices were made for me because other consumers that like the same types of audiovisual products that I watch, will like them too. It will say, “Because you watched Walking Dead. ” It understands that if you like this kind of genre, there are other products here that you might like.

There is information about “My Account” and other “Notifications. ” The last example I’ll give here is that machine learning is also present in physical purchases as well. Relating to the point of sale.

Let’s say that in the future, or even now in some countries, your washing machine could inform you, through the internet of things, that the soap dispenser is low. It tells your cell phone app that it’s time to buy more. It informs you about recurrent purchases.

It can organize your itinerary through the store, knowing your frequent route inside a store or supermarket, based on your shopping list so you can optimize your time. Imagine you have 50 items on your shopping list, and it can organize a map of the store for you to follow. There’s automatic payment.

Just by placing the product in the shopping cart you can go home. It understands and makes the payment directly from your bank account. Cross-indication; if you’re buying tomato sauce, you may want to buy some pasta.

There’s also point of sales programmatic advertising. Programmatic Advertising is when you walk by an electronic kiosk inside a supermarket and it knows, for example, that you were searching online for a particular brand of diapers or beer the week before, and the automated point of sales (PDV) speaks to you. It identifies you as you walk by.

So that’s it. Machine learning is nothing more than how people’s usage of networks is being used to feed the data that will organize the strategic optimization of companies. See you, next class.