Reality of Machine Learning Marketing | Uses of Machine Learning

Hello Candidates, today we have come up with interesting article called Machine Learning Marketing.

In this article we will explain the “Reality of Machine Learning in Marketing”. Many of the candidates are saying that ML is going to take over all human marketers in the marketing world.

In this scenario let us see what is the actual reality existing between human marketers and Machine Learning. In order to understand the whole concept, follow the complete blog without any skip.

What is Machine Learning?

In general, Machine Learning is an Artificial Intelligence’s Application which has ability to learn automatically and improve from experience without any programming. It mainly concentrates on development of computer programs that can access data and use it learn for themselves.

The learning process starts from observations or data, such as examples, direct experience, in order to make better decisions in future based on the examples we provide.

Check Out Applications & Latest Updates of ML 2019

The Intersection of Machines and Humans

At present all are thinking that Machines are going to replace human jobs in marketing field. But that’s not fact. Yes I agree that machines can produce final delivery to the audience as humans do. But we need to remember that human brain is more complex.

On other hand machines can also identify the unique purchase patterns and make better bidding decisions accordingly where once upon a time done by humans. But Machines cannot capture the emotions and associated intelligence optimally. So most of the creative ideas around content still come from humans.

The only thing we can say is Marketing is truly an art and science where humans and machines should work out together.

Key Areas to Boost Machine Learning Marketing

Generally every field there will be some key areas to boost that particular business. So, let us what are the Key Areas to boost Machine Learning in Marketing.

1. Landing Page Optimization

In general, Landing Page is very important for every website. Whenever you post ads and users click on the ads they will be redirected to landing page. On other hand this is an opportunity for human creators to inspire your users with creative page design and concept.

But here machines can do better job in creating personalized pages. One simple approach is to create different experiences for new vs. repeat customers. However tools such as Adobe Target, and techniques that are readily available to provide a jump start to marketers looking for solutions in this space.

2. Targeting Right Audience

Usually, the ability to finding the right audience is the key to get promised ROI for marketing dollars. One such approach is to first leverage first-party data to build micro segments and associated purchase likelihood score based on machine learning models.

Subsequently, marketers can use available look-alike models offered by almost all activation platforms; Priority will be different for each customer. Some demand-side platforms (DSPs) even allow onboarding proprietary models.

At last marketers can connect the performance data to associated systems for ongoing learning at scale. However this self-learning process is one of the core tenets of machine learning and crucial to improving the accuracy of machine learning models.

3. Media Bidding and Optimization

To ensure optimal campaign results both CPA and LTV need to be measured and optimized in real time. Generally both LTV and CPA will vary by the audience, time and platform. So the decision about how much to bid will become complex. That’s why we require machines to self learn and automate the process.

However, the general trend, especially with the rising requirements for user privacy, is for platforms to share less data with marketers, limiting the impact of in-house bidding models. So the Marketing Mix management would likely to adopt the machine learning.

4. Dynamic Creative

In actual Dynamic Creative is the ability to develop and test different combinations of creative’s and copies in real time. Human marketers can build library of images, messages, promos while machines with ML can run tons of personalized ads.

In addition to that, dynamic creative optimization and creative management platforms are merging into a unified platform which seems to offer end-to-end solutions. Certainly many platforms like Facebook, Google Ads has already offers solutions to run dynamic ads. In short marketers will also adopt machine driven dynamic copy generations as well.

Hope these 4 Points are helpful to you in understanding about Key Areas to Boost Machine Learning Marketing. Subsequently click on the below link for more and clear cut information .

Check Out complete info about Machine Learning in Marketing

Uses of Machine Learning for Marketing

Firstly, There are many benefits of ML in Marketing. In fact many experts have said that Machine Learning is going to reshape the Marketing.

So, following are the best Uses of Machine Learning for Marketing that are observed after many experiments. So go through them carefully.

  • Improved Lead Score
  • Personalized Chatbots
  • Improved Audience Insights
  • Automation Vision for Product recognition
  • Improves Website Experiments
  • Profitable Dynamic Pricing Models
  • Prioritizing and Targeting each customer
  • Relevant Recommendation Systems

Above all are the top benefits of ML. Meanwhile click on the below link to know more uses of Machine Learning for Marketing.

Click Here to check More Uses of ML in Marketing

Final Thoughts

Therefore we want to conclude that ML will bring more updated versions for marketing. However human marketers will not be replaced by machines. Moreover both human marketers and Machines will work together to show more wonders. So, this is the actual reality of Machine Learning Marketing.

Hope this article is helpful to you. However, comment your doubts regarding Machine Learning for Marketing. Moreover follow our website for more interesting articles regarding Tech, Robotics, AR & VR, ML, Digital Marketing.

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