Machine Learning & Advertising

Machine Learning

Let’s talk about Machine Learning. A word, almost every “progressive advertiser” is talking about these days. It is somewhat like a threat to conventional advertising professionals as a lot of them think that ML will replace them and will produce concepts instead. While the digital thinks it will reduce most of the procedural issues that may lead to complications.
However, if you look at the past, there are a lot of applications that are already involved directly or indirectly within the Marketing & Advertising world altogether. Before we debate regarding the issue of ML replacing Humans, let’s take a deep breath, step back and look at the facts and see how Machine learning is gaining its pace in the advertising world and the possibilities in the future.


I remember my early days of the Internet where I had Lycos and Yahoo to search, options were limited and results were also very vague. later, came google and the searching became more optimized and we started getting better results. But that was not the end, the bigger challenge was to further optimize these searches by making your search engine even smarter.
Google has explained this on “How Search Works” where it elaborates its 5 steps process of assessing information and make it ready for online search results. The processes of Analysing, Matching, Ranking, Considering & Returning your search results play a key role through machine learning to ensure that even your vaguest queries are responded with best search results.
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Marketing forecasting is one of the “Big Words” and we can talk on and on about it by keeping its magnitude in mind. However, in this discussion, we will focus more on its ability to forecast through data provided by an entity.
Organizations like SisenseTableau, and Looker are focusing on business intelligence and market predictions. Keeping the magnitude of market data in mind AI helps these applications to understand, sort and deliver results quickly through their sophisticated algorithms. This can talk about CTR, views, time spent on the website, number of pages seen, etc. to more complex aspects of consumer journey and purchasing products from their online stores.
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A new big word that is very closely related to Machine Learning and organizations these days are very keen to know what people think about them over the web and social media. Hashtags, links or even mentions over the internet are transformed into structured data for organizations to understand the public opinions related to brands, services politics or even social issues, also, it’s one of the most effective ways to review public opinion about any topic either at bigger geographical regions or at the focused locations simultaneously.
These opinions not just help in terms of opinions but are also useful in PR, product reviews and feedback as well as customer service. A prime example of this application is the issue of Samsung Galaxy Note 7 when it started catching fire and people started talking about it over the internet. A huge global PR issue was raised and Samsung took swift actions to overcome this issue.


Now let’s come back to the first point of Machine Learning replacing Humans. Machine Learning, as much as it can analyze complex data and provides results, it still lacks the complexity of human emotions and it is not as simple as adding data and stir to get the results.
It requires human involvement to rationalize and structure the data for further human understanding which can be used for product development, communication, and many other initiatives. So, enjoy the tools and avoid insecurity.

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