It is no coincidence that advertisements for products or services of interest to you appear every time you browse the internet. What happens is that digital algorithms know you well.
Has it happened to you that you are browsing the internet, and an advertising for something you want or need appears everywhere? Whether you are on a website with space for advertising, and even on social media.
Some people are even shocked to see an ad appear on Facebook about something they just searched for. Many of them think that Google spies on them, but no. The only thing that this search engine (and any other) does, is learn from you through an activity called Machine Learning.
What is Machine Learning?
Machine Learning is a scientific discipline in the field of Artificial Intelligence that creates systems that learn automatically. In other words, these systems were created to identify complex patterns in millions of data. The machine that really learns is an algorithm that reviews the data, and thanks to this it is able to predict future behavior.
All of this allows these systems to improve autonomously over time, without human intervention. Within a company, AI applied to Machine Learning can be applied in different areas. For example:
- Detect fraud in transactions.
- Predict failures in technological equipment.
- Anticipating which employees will be more profitable next year.
- Select potential customers based on behaviors on social networks, interactions on the web.
- Know when is the best time to post on social networks or send a newsletter.
- Detect intrusions in a data communications network.
- Decide what is the best time to call a customer.
- Make decisions for a better digital strategy.
Machine Learning in digital marketing
As we mentioned above, this strategy applied to digital marketing learns from the user through their search engine activity.
This means that Google’s algorithms learn from your behaviors and historical searches to determine which ad is most effective at any given time, based on the channel you are on and how you have responded in previous campaigns.
In this way, the algorithm manages to optimize the media mix, to know which combinations of creatives and channels are working better and to obtain a higher ROI for the company that is advertising.
Additionally, with the combination of search information and the historical performance of the ads, AdWords applies an algorithm that helps you maximize the impact of your advertising investment.
On the other hand, Machine Learning can also be used in audience segmentation in order to extract groups of potential customers with similar behaviors and preferences.
Simply put, Google’s algorithm pays more attention to you than some people. That is why he knows very well what to offer and when to do it. Thanks to the power of Artificial Intelligence and Data Marketing, Machine Learning is being a crucial support in today’s digital marketing.
Advantages of a digital marketing strategy based on Machine Learning
1. Optimize the growth of the company through the efficiency of the campaign
Part of it is that the data that this artificial intelligence gives you can help you see the trend of your business and make predictions. Thanks to this, you can make assertive decisions focused on long-term growth, not short-term benefits.
For example: HomeAway (a world leader in vacation rental properties, based in Austin, Tx) by testing this approach, managed to increase its return on investment in 2017, by 115% year over year.
2. Acquire better customers
Also known as qualified leads. They are those people who come to your business thanks to the attraction of your ad. What this technology does is that it identifies the segments of potential customers with the highest (CLV), “Customer Lifetime Value”. In other words, you invest in those you know will buy more often and not in those who will do so rarely.
3. Earn more with current customers
A great example of this is Amazon. By analyzing your customers’ buying patterns, you offer recommended products on your page and digital advertising. This simple action increases your purchase ticket through the cross-selling of products. For example, it suggests that we may be interested in buying the fashionable video game, in the same session in which we are buying a new console.
4. Improve and personalize the creativity of the messages
The same Google and social media tools allow you to better understand the tastes and search intentions of your consumers. Knowing how to interpret them will allow you to generate creative designs with more attractive products sought after by the client.
In this sense, Machine Learning helps to create personalized ads, based on words and search behaviors, to show the correct customer the correct message and at the best time.
5. Invest in better mobile experiences
9 out of 10 users prefer to connect through their mobile (Asociación de Internet.mx, 2018). To increase purchases on their mobile site, various brands adopt technologies to speed up and improve loading time and user experience.
This strategy implies a considerable investment in the design of the web page so that the functionalities, videos, images, are agile and with easy access. However, that investment is recovered in a short time.
Other advantages of Machine Learning in digital marketing
The new machine learning models are designed and perfected to understand everything we write on the different digital platforms and to know if they reflect a positive, neutral or negative opinion. This helps companies to.
- Analyze customer opinions about a product or service.
- Assess the mood of a customer who goes to a helpdesk (for example, through a chatbot) and tailor the response accordingly.
- Identify the most frequent complaints from users about a product or service based on their comments on social networks.
- Quickly detect and prevent possible online reputation problems for a brand.
Predict and prevent dropouts
Because it is much easier to retain a customer than it is to get a new customer, digital marketing strategies must include solutions to improve customer churn rates.
To do this, machine learning analyzes customer data to create algorithms that can predict their behavior and identify users who are at high risk of turning to competitors in the near future.
Improve user security and privacy
For this, artificial intelligence and Machine Learning propose a possible solution through biometric identification, which is one of the safest mechanisms for capturing and sharing data.
The result is that more data can be exchanged more securely, making it easier to have more insights and make better decisions. And in turn, biometric identification allows consumer data to remain more secure and protected.
If you want to apply these Machine Learning strategies to grow your business, contact us! We help you grow.