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Machine learning is a branch of Artificial Intelligence that makes it possible for systems to learn without being programmed. Applying this technology to real world Marketing is often misunderstood and is within your reach.

Making Machine Learning useful for Digital Marketing

As technology advances at an unprecedented rate, making use of the potential of Artificial Intelligence in business is not a far-fetched pipe dream anymore. In this day and age, it is clear that technology and business go hand-in-hand. Doing one without the other would be a mistake businesses have to avoid if they intend to remain competitive.

One element that is making better customer engagement possible is data insight. Because of this, the reliance on data is continuously increasing. Gartner research predicts that in the next two years, over 75% of companies will have invested big on data.

The driving force behind this is the need for businesses to anticipate customer behaviour in marketing. This is where machine learning comes in handy. Here, we'll briefly look at what machine learning is; then proceed to highlight the role it plays in digital marketing;

What is Machine Learning?

Machine learning is a branch of artificial intelligence that makes it possible for systems to automatically learn from experiences without being programmed. This process starts with observing data so as to look for possible patterns. This allows the system to make better choices in the future.

Machine learning algorithms are split into various categories. They include;

  • Supervised
    These algorithms can apply what they have learnt in the past to new data, to predict future events. It starts with analysing a known data set often used for training. The algorithm then produces an inferred function meant to predict the output values. These machine learning algorithms are also able to compare its output with the intended output, detecting any errors, and modifying the model appropriately.
  • Unsupervised
    Here, the algorithm studies how a system can infer functions in order to describe potential hidden structures within data that is unlabelled. The algorithm does not attempt to predict outputs, it explores the data, drawing inferences (conclusion) from data sets.
  • Reinforcement
    These algorithms evaluate different options in an environment and are able to learn based upon the outcome. By providing a signal to the algorithm that associates good behaviours with a positive indicator and bad behaviours with a negative one, we can train the algorithm favour the behaviour we want and therefore learning over time.

Machine Learning applied in Digital Marketing

The scope of applications for machine learning by digital marketers may not be entirely clear, but it has already had a huge impact on digital marketing outcomes for those who have applied it. As there is an advantage to be taken from the detailed and accurate analytics machine learning algorithms are capable of providing. Marketing teams are now able to gain in-depth insights that enable them to optimise marketing strategies.

Machine learning is being implemented to help digital marketers expand their knowledge and understanding of their target demographic. They then proceed to develop better strategies that optimise customer engagement and interaction.

The implementation of machine learning in marketing is continuously finding new grounds. Currently, marketers can make use of machine learning algorithms in the following areas;

1. Content marketing

Over the years, companies have been trying to create content meant to engage the target audience. Along with compelling storytelling and its ability to trigger a response, one other element that determines how effective the content will be is its relevance.

Through tracking trends and coming up with content suggestions, machine learning tools enable you to streamline your content based on your intended audience.

2. Predictive Customer Behaviour

Machine learning algorithms can help marketers to predict customer behaviour. When it comes to buying decisions, most of them are not based on clearly defined logic. Intuition, culture, emotions, and trust play a big role. People tend to behave the same way, buy the same items, and follow the same intuitions.

There are algorithms specifically built to learn a customer's pattern and help come up with automation to boost conversion rates.

3. Enhance Customer Experience

This is one of the few fields machine learning is able to almost completely automate. Algorithms are able to recognise customer requests and route them to the right place. Forbes states that 57% of executives believe improving customer experience will be the most important growth benefit of machine learning.

Features such as chatbots are already being used to fully or partially automate customer service processes. They automate routine tasks, answer questions that are frequently asked, and also create a personalised customer care experience.

4. Advertising

The customer data analysis and predictions made by machine learning algorithms make it possible for digital marketers to come up with target promotions that have a better chance of yielding better returns on investment. Reinforcement algorithms also help with the marketing channels in which advertisements are best placed for conversion. Along with helping you to optimise the timings of the advertisements.

5. Customer retention

Through its ability to streamline the predictions of risk, machine learning can help you minimise customer churn. Harvard Business Review found that new customers normally cost 5 to 25 times as much as retaining current customers. Providing you with attributes like customer gender, age, and income will enable you to predict the kind of customer that will be likely to churn.

6. Price Optimisation

By taking into account factors like customer segment, price elasticity, product's position, and sales period, a machine learning algorithm can help you with optimising product pricing. This makes it possible to competitively price your products in a way that doesn't price you out of the market while simultaneously not affecting business profits.

7. Forecast Prediction

Making use of machine learning algorithms allow you to forecast a variety of metrics. This makes it possible for you forecast product demand in order to optimise your inventory effectively. With machine learning, you no longer have to worry about supply shortages and lost sales or oversupply. Accurate predictions can drastically improve earnings by giving you the ability to proactive and not reactive.

8. Anomaly Detection

Time to action can mean a lot when a critical system goes down, but having the resources available to monitor all of your business critical metrics or systems is not easy. Machine Learning algorithms are able to handle large volumes of data and build highly accurate models that reduce false positives.

Overview

The ability machine learning algorithms have to monitor vast amounts of analytic data, and drawing business level insights from them, is a tool that every digital marketer should capitalise on. At Jepto, we aim to facilitate digital marketers in making Machine Learning applicable in real world scenarios to allow them to be more effective and efficient.

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