How to Apply Machine Learning to Your Digital Marketing Strategy



As a digital marketing expert, have you ever made a spreadsheet comprising the individual purchase history of all customers searching for a particular product in your category, the time of day they’re most expected to purchase, the kind of device they’re using when they purchased last, their location when they made that purchase, statistically calculated ad creative quality and numerous other proprietary Google data points; then utilized this information to manually modify each bid – in real time – for every single auction?

If you have several hours and a very powerful laptop, you may be able to study all this data manually. Or you could utilize Google Adwords Smart Bidding, an application of machine learning which makes it thinkable for Google to set the right bid at auction-time immediately using all these data points and more.

Along with the growth of Big Data, Machine Learning is perhaps the most groundbreaking technology to change the background of digital marketing. Machine Learning leverages really large datasets that marketers are now able to capture, learns from this data and generates actionable data insights that can be leveraged by marketers to generate completely new levels of understanding of your clients, personalization and optimization opportunities to enhance the efficiency of marketing campaigns.

Leveraging Machine Learning in Digital Marketing Strategy

Every customer interaction leaves behind a digital footprint that can be used to develop a deeper understanding of the client’s intent, behaviors, motivations, and predict future interactions. ML allows organizations to leverage large datasets to develop customer insights, integrate external data sources like competitive insights and weather data, examine shopping histories, infer and classify behaviors and develop actionable insights and customer explicit personalization.

●        ML can be utilized in content marketing campaigns to develop more applicable content, precise to the individual based on past data. This improves engagement and ability drive a reply from the customer.
●        ML is utilized in search and display campaigns to help identify the metrics that signify the highest propensity to forecast the desired behavior and classify the likenesses between your customers with the optimum LTV. ML is also used to recognize the order and kind of media interaction paths most likely to end in a conversion event, notify your programmatic media platform then enhances bidding to allow this sequence to your possible customers.
●        ML can be used in email to scrutinize consumer behavior to determine the optimal time to send an email to a specific individual, what creative to include, what offer will generate the best response, which landing page should be presented on the site and if it’s necessary to present a coupon code to the end-user to increase the likelihood to convert.
●        ML enables digital experience personalization based on the assemblage of customer-specific information as well as a wide collection of activities of other users.
●     This ability to utilize real-time streaming data to power in-the-moment personalization and predictive competences enabled by ML allows the incessant response loop between customer intent, interaction and action that drive efficiencies in digital media and improved return on investment for advertisers.

Machine Learning offers us all with the opportunity to develop more friendly and valuable relationship with our customers and more engaging experience with brands. Machine Learning course from a premier institution can help you build a successful career in the field of ML. Top institutions have right resources and faculty to facilitate students’ learning. 

Location: Bengaluru, Karnataka, India

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