Machine Learning a Big Data Can Empower Marketers?

Gone are the days when automation, machine learning and software based marketing techniques were not a thing. Presently we have left behind those days of outdoor channels on TV, Radio, Print and some channels. Television is also divided into several cable channels that are at your fingertips on the remote control. Despite all this, digital advertising revenue has far exceeded that of television.

The digital world has long been dominant and paid search marketing is slowly becoming more data-centric than ever. If you check your computer folders, you’ll certainly find thousands of spreadsheets filled with statistics revealing conversion rates, cost-per-click bids, and your advertising-profits.

Big Data — what to do with it?

As we see paid search relies heavily on big data, which is like crashing an excel spreadsheet to include too many rows and hence cannot be predicted safely. The future of digital is probably tied to machine learning. But why is it connected this way? This is because automation, machine learning and software will gradually replace all online professionals and not only that, their creative ideas will also be replaced.

We are not too far from this near 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.

Machine learning and its importance

Machine learning is nothing but a smart automation that can combine millions of spreadsheets and draw important insights from that pile of data. Processing data to obtain information is something machine learning can help you with, but what about using that information and doing smart and creative things with it? Machine learning is important for digital advertisers, as they face the problem of data.

Machine learning is already in action — some examples

As we see machine learning growing in popularity, we should know that machine learning is already in action and let’s take a look at some examples.

Voice assistants and chatbots

Conversational interfaces have suddenly expanded from major publishers such as Amazon, Google, Apple, Microsoft and Facebook to voice assistants and chatbots such as Google Assistant, Alexa, Cortana and Siri, to name a few. Chatbots have unique cases, contexts that are consumer-based such as health questions and important sports scores.

Preventing and foreshadowing customer churn

It is a deep customer-funnel strategy that involves using machine learning to predict general characteristics about customer departures. Urban Airship and Microsoft Azure create predictive analytics models to drive purchase strategies and deadlines that customers can brainstorm frequently. When these businesses are offering such critical points, businesses are able to proactively address common complaints.

Semantic Distance Modeling and NLP

Another way machine learning is used in digital advertising is to predict bidding models for keywords with low data, such as long-tail keywords with high buying intent. In such cases, advertising solutions based on machine learning can deploy new groups of keywords on similar keyword groups and help advertisers develop keyword groups.

So, as we see, machine learning can never be a threat to online marketers. Rather it is a powerful friend that makes life easier for digital marketers. It is very important to deliver the right message at the right time.