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Machine learning and search engine marketing โ€“ How can big data empower marketers?

machine learning and search marketingOver the past few years, advertising has changed in more than one ways. Previously the era was when automation, machine learning and software-based marekting tech were not a thing. Currently, weโ€™ve crossed those days of outdoor channels, radio, print and few channels on TV. Television has also been divided into several cable channels which are all at your fingertips on the remote control. In spite of all this, digital ad revenue has progressed far enough to surpass television.

Digital world has been dominating since a long time now and paid search marketing is gradually getting more focused on data than ever before. In case you check your computer folders, you will definitely get thousands of spreadsheets which are full of conversion rates, cost-per-click bids and figures which reveal your returns-on-ad.

Big Data โ€“ What to do with it?

As we see paid search depends heavily on big data, which is that type which makes the Excel spreadsheets crash for including too many rows and hence it can be safely predicted that the future of digital is possibly linked with machine learning. But why is it intertwined in this way? This is because automation, machine learning and software will gradually replace all online professionals and not only so, their creative ideas will also be replaced.

Weโ€™re not so far from this foreseeable future. The future of digital is going to be a healthy team-up of smart marketers and of course smart automation which is based on machine learning. According to a market survey, 98% of the biggest digital marketers agreed on this.

Machine Learning and its importance

Machine learning is nothing but a smart automation which can combine millions of spreadsheets and pull off important insights from that heap of data. Processing data in order to retrieve insights is somethings which machine learning can assist you with but what about using those insights and doing smart and creative things with them? Machine learning is vital for digital advertisers, starters as they face data issues.

Machine Learning is already in action โ€“ Few examples

As we see that machine learning is growing in popularity, we should know that machine learning is already in action and letโ€™s take a look at few examples.

  • Voice Assistants and Chatbots

There is a sudden expansion in the conversational interfaces from few major publishers like Amazon, Google, Apple, Microsoft and Facebook in the form of voice assistants and Chatbots like Google Assistant, Alexa, Cortana and Siri, to name a few. Chatbots have got unique cases, contexts which are consumer-based like health-related queries and the important sports scores.

  • Preventing and foreseeing customer churn

This is a deeper customer-funnel strategy which involves using machine learning top predict common features about customer attrition. Urban Airship and Microsoft Azure have built models of predictive analytics to know the purchasing strategies and time frames at which customers can churn often. When these businesses are projecting such vital points, the businesses are able to address actively to the common complaints.

  • Semantic Distance Modeling and NLP

One more way in which machine learning is used in the field of digital advertising is to foresee bidding models for keywords which are low-data like long-tail keywords with high buying intent. In such cases, advertising solutions based on machine learning can appoint new groups of keyword on similar keyword groups and help advertisers in ramping keyword groups.

Therefore, as per what we see, machine learning can never be a threat to online marketers. Rather it is a powerful friend which makes living easier for the digital marketers. It is just vital to deliver the perfect message at the perfect time.

Aadarsh

Aadarsh is a talented content writer who specializes in creating informative articles on business and technology topics. He is a regular contributor to the popular website, Nogentech.org, where his articles are widely read and highly appreciated by readers from all around the world.

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