Seven ways Machine Learning can help you improve your marketing
It is no secret that marketing bases its success on the efficient use of data. Knowing who to reach, when and how, is key to achieving the desired conversions. In this context, the more detailed the audience analysis, the more advantage you will have over the competition; that is why in the digital age Machine Learning (ML) appears as a crucial actor to take marketing to the next level.
One of the great advantages of this technology is that it directly influences the performance of marketing campaigns through areas such as audience segmentation, branding, content generation and customer communication.
But it is not a question of incorporating a Machine Learning solution simply because the market demands it; ultimately an irresponsible use of this technology can cause more problems than profits in a company. Without a team of data scientists who are permanently adjusting and improving the parameters of each ML algorithm, the results will rarely be positive.
Know here some of the applications that you can implement in your company through artificial intelligence and Machine Learning:
1- Pricing models
Using ML-based regression techniques, marketers can optimize the pricing strategy of a service or product, as well as predictive models of sales and expenses in a campaign.
2- Customer segmentation and discovery
Machine Learning allows you to delve deeper into customer segmentation processes. This is achieved by generating dynamic groups of users with whom the company can interact more meaningfully and efficiently. By analyzing millions of possible interests -through the way users use their social networks or the way they navigate the Internet- insights that facilitate interaction with potential customers can be obtained.
3- Automatic translation neuronal networks
One difficulty that often arises for companies wishing to enter a new country or market, where different language codes are used, is the translation of terms that facilitate the penetration of marketing campaigns in those places. Today, with the improvement of neural networks, translation through robots has achieved a fidelity that is close to human, which allows drastically reducing marketing costs in this area. Finally, instead of having a team of human translators, it is now only necessary to have a professional to validate the translation arising from artificial intelligence.
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4- Classification of texts and generation of insights
The existence of Machine Learning systems that use language processing models (NLP) makes it possible for both speech and text to be analysed, processed and subsequently classified into insights that help achieve the objectives of a marketing campaign.
5- Recurrent neural networks in creative campaigns
“Recurrent neural networks (RNN)” is the name used to refer to ML models that help the creative branding team generate names for products, campaigns and companies with a high degree of success.
6- Chatbots with dialogue systems that improve the user experience
Although the appearance of chatbots in various portals is not a novelty, the use given to these AI tools does not usually take advantage of the potential offered by Machine Learning models, which allow language to be processed intelligently, whether through adaptation to complex questions or referral to human specialists when necessary. The optimal use of chatbots improves customer engagement throughout the customer journey.
7- Computerized visual recognition applied to branding
The marketing area can greatly benefit from the use of computerized visual recognition systems based on artificial intelligence, which generate insights from images that are not labeled or previously classified. An example of this type of system is GumGum, a company based on computerized visual recognition that allows us to identify with great accuracy when and in what context logos -and other relevant visual material for marketing managers- have been used .