AI is rapidly gaining a foothold in multiple businesses, small and big alike with a main focus on exploiting the increased efficiency in the area of analytics and intelligent learning that come with it

When the topic of Artificial Intelligence (AI) is broached, it’s very likely for terms a la machine learning, big data and computational intelligence to pop up and science fiction movies like Ex Machina and AI, quick to spring to mind. But, the former aside, an important aspect to look out for, are the growing possibilities that Applied AI can now offer with pertinence to marketing.

EVERYONE CAN ADOPT AI IN SOME FORM: What was once considered something strictly reliant on a company’s size and cash-flow, AI is rapidly gaining a foothold in multiple businesses, small and big alike with a main focus on exploiting the increased efficiency in the area of analytics and intelligent learning that come with it.

Now, marketing can do away with the saying “Hindsight is always 20/20.” Not only can developing AI applications scour through past happenings and draw conclusions and evidences from the data – thereby shortening the distance between data and decision – but, also help shape future occurrences based on it and offer companies cost and time-effective tactics toward tackling future numbers. This brings us to the core advantage of an ideal AI system in today’s market – increased automation and reduced redundancy.

It further sheds light on the need for marketers to adopt a conscious shift from campaigning to real-time interaction with users. Customer acquisition is an omnipresent requisite in the B2B and B2C hub and with the betterment of data collection and the retesting of it, we can enhance connectivity and response time to and knowledge of the customer. We’re helping nurture a dialogue and immersive experience that the user can start at any instant and us, engage them in thoroughly. With the scope to sift through a wide expanse of factors, one can easily grow their list of contacts.

ADAPTIVE APPROACH: Traditional campaigns, however, are heavily reliant on predetermined paths – ascertaining and creating rules that dictate responses based on a customer’s actions. Not only is this an approach that lacks flexibility in further understanding the customer, it’s also one that is resource hungry. With an abundance of data in every facet of a user’s behavior today, perusing through it with each individual in mind would be time-consuming and involute. Whereas, automation guided by machine learning would abandon this path-dependent approach and embrace a more adaptive solution. We’re thus returning to AI’s cardinal ability to learn from past details and base its next step from it. By not losing sight of the end goal, we’re kindling a far more personalised and in-depth customer journey, while simultaneously stressing that the marketer is just as important as the customer.

Last year’s private acquisition of Marketo by Vista Equity Partners was seen as an effort by the company to concentrate on developing new technologies, particularly their largest investment to date: Project Orion, their next gen platform architecture. Orion will revolve around delivering big data scalability and transactional volume in addition to services such as account based marketing, predictive content and analysis.

Salesforce, on the contrary, is not looking to abandon campaigning entirely just yet. As VP of Product, Leslie Fine believes in both a rules-based approach as well as a machine informed customer journey for the optimal marketing experience.

One of the major AI facilitated tools expected to change the market would be the recommendation feature. By learning from a user’s behavior patterns and history, we’re able to put forth a product/content suited to their interests. In its wake, it brings with it the essential conversion of an individual to a customer while also boosting traffic and user engagement and retention to the brand. In addition to individual-tailored content, its generation is just as fundamental and with the help of Natural Language Processing, we can now skim data and information down to the nitty gritty that targeted groups are looking for.

Amazon’s recommendation, for example, is at work from the time a user views a certain product all the way downstream to checkout. Their algorithms are centralised around a process called item-to-item collaborative filtering. And in May of 2016, they revealed that their product recommendation system, DSSTNE (pronounced destiny), will be given to the industry as Open Source Software. Now any company, researcher, or curious tinkerer can use it for their own AI applications.

With Amazon making waves in ecommerce, Netflix has been dominating the digital consumption arena with its algorithms working to present as much of its content library to its users as possible while also retaining hyper-specific categorization so as to line up with the their tastes. Recent developments such as the removal of their star-based rating system for the far simpler thumbs up or thumbs down system has already seen a 200% increase in overall ratings from members. "We made ratings less important because the implicit signal of your behavior is more important," Netflix VP of Product Todd Yellin stated during a press briefing.

Artificial Intelligence brings the great power to exploit creativity. By reducing the human workload, we’d be able to surpass our conventional lines of wisdom and assumptions for a superior and more individualised experience. And marketing is one such sector that can seek to benefit highly from this burgeoning technology.



(The author is Founder & CEO, Kenscio Digital Marketing)

Disclaimer: The views expressed here are solely those of the author and do not in any way represent the views of exchange4media.com.

