We have been listening to this buzzword ‘Machine Learning’ for a while now. It is a super powerful tool available in the present data age. But how it is valuable and how it creates a significant impact in digital marketing is something we are here to learn. Read it until the end to understand how helpful Machine Learning is and will be in the future.
What is Machine Learning?
Machine Learning, in simple terms, is an application of Artificial Intelligence that helps systems learn automatically. Machine learning extracts the past data and accordingly schedules future tasks. In the past few years, there has been much data generated. Thus, machine learning can learn the data of previous tasks and predict the future.
Research conducted by Market and Markets suggests that the machine learning market is expected to grow from $1 billion in 2016 to $9 billion by 2022. Another report by GlobalNewsWire indicated that the global machine learning market was $8 billion in 2019, and it is expected to reach $117 billion by the end of 2027.
Knowing what machine learning is and how it will grow in the coming years, we must understand how machine learning is valuable for digital marketers.
Value of Machine Learning in Digital Marketing & future of businesses
One of the significant roles of digital marketers is collecting the data, learning it, and optimizing further campaigns. The ability to do this effectively and efficiently differs from marketer to marketer. It means that a business must invest in the right tools, the right infrastructure, and the right technology to improve the data insights and predict the future.
There are several ways of leveraging machine learning in digital marketing to make the most of the data extracted.
- Improvised User Segmentation
Digital Marketers can learn about their customers over a while. But the number of metrics a marketer can analyze is not more than what a machine can learn. Nearly there are hundreds of metrics that are present to be known to predict the outcome. Machines can easily learn all the metrics quickly in a matter of seconds and provide the output. Marketers can use these insights in marketing efforts.
You can provide a more customized user experience to your customers.
When your user is present on your website or application, machine learning can easily use the search data, pair it with the user’s behavioral data, and suggest more products and services.
This will improve the user experience of the users visiting your website or using your application.
Optimizing the creative aspect of digital marketing
Using A/B testing, one can learn the optimal location, color, size, and CTA providing necessary leads. But by using machine learning, you can test multiple variables at a time and provide insights on which was the most effective one.
Multiple variables include text, location on the page, number of words in the CTA, etc.
Understanding customer’s behavior
Following are the activities that can be performed quickly, coupling machine learning with customer behavior.
Machine Learning helps in determining fraud.
Machine learning helps effectively and efficiently combat fraud by learning user’s previous behavioral trends. If the user deviates from the trend, machine learning marks it as a fraud and notifies the actual user regarding it. It additionally blocks all the further actions of the fraud users.
Predictive analytics using machine learning
There is a sea of data available to marketers. All the data is not necessarily be utilized.
With machine learning, a strong prediction is made using past user data. Hypothetically, a machine knows that the user will navigate to the purchase token page if he/she has completed a particular level in the game.
This predictive analytics helps marketers to understand the behavior and make necessary changes in the ad campaign.
The more the data, the machine has better assumptions. Once there is sufficient data and particular confidence is reached, the assumptions can then be considered as predictions.
Too little data or too much time for machines to make predictions will lead marketers to miss the opportunity to optimize. Hence, tight integration with data-rich dashboards is crucial for the machines to make better decisions, make better predictions, and help marketers react quickly.
Dynamic Pricing for better conversion
Various travel apps have been using machine learning in determining the best price to be offered to their customers. Based on the price listed on multiple websites, and the user journey, travel apps ensure that the price quoted to the customers is the best in the market.
Additionally, using machine learning, they can determine which customers are almost close to purchasing. Travel apps can offer additional discounts to such users who are close to converting but need other incentives. Thus, travel apps can provide such price cuts to customers who would not otherwise convert.
Machine Learning is the future
You know machine learning is not going anywhere, at least for the next one or two decades. We can say that machine learning is getting stronger.
Marketers are always concerned that the work with machine learning is repetitive, time-intensive, and mundane. Also, they feel that these algorithms will replace some of the roles existing in the present organizations.
You know, we see the flip side of it. It frees the resource time which we can use in the tasks that require human intervention. The best example is the creative aspect of digital marketing. A machine can predict user behavior but cannot suggest the creative aspect.
Digital marketers can use the predictions to update their creative aspect of the campaign and make the most of machine learning.
Machine Learning in Digital Marketing helps digital marketing agencies/digital marketers to make smart decisions using historical data.
The more data we have, the smarter and more precise the predictions will become. The more we embrace the capabilities of machine learning, the wiser we marketers will become.