Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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3 Reasons Why It's Crucial for Brands to Introduce Machine Learning Into Their Marketing

Aug 8, 2017 | 936 Views

Every so often, a story ripples through the media along the lines of "Scientists say a 'smart pill' is just over the horizon to make us immediately more intelligent." While there is no telling when we will actually see such a pill, there's a metaphorical "smart pill" available to marketers now, and it comes in the form of artificial intelligence, or AI.

AI is rapidly transforming the enterprise-and that includes the marketing department. According to a recent Gartner survey, 85 percent of customer interactions will be managed without a human by 2020.

Essentially, AI leverages machine learning to maximize the effectiveness of marketing efforts by predicting the best next customer interaction based on what it has learned through previous interactions. The more data AI has to work with, the better job it does identifying patterns of customer behavior and engaging them in more meaningful and authentic ways.

In today's digitally connected world, customers are demanding brand experiences that resonate with them on the channels they prefer. And if they don't feel as though a brand is being authentic, they'll disengage. AI is the partner to the marketing team, helping it deliver the right message at the right time.

Moving past the anxiety about AI's impact, Here are three reasons why CMOs should tell their teams to cheer-not fear-the power of AI:

Enables more precision
Marketers are awash in data. New technologies and channels are creating billions of customer interactions, yet marketing teams alone are not equipped to consume or mine all this data to target and engage each customer at the speed and scale required today. With the help of AI, marketers have the ability to optimize campaigns, including selecting the appropriate content, at the right cadence, across all channels, and to select segmentations. And AI can uncover opportunities that are inaccessible without its "brainpower."

Marketers' fear of AI is due to a lack of understanding. The reality is AI will complement marketing rather than replace it. What's more, AI will amplify their marketing efforts at a time when we are all forced to do more in less and less time.

Delivers better data insights
As data explodes even further in volume, velocity and complexity, AI can illuminate potential new customer journeys and new audience segments that were not obvious before.

Here's an example: I'm a pharmaceutical company and I target doctors with a specific medical specialization. AI can help by uncovering insights in my data that indicate that I should be targeting a micro-segment of doctors based on current prescriptions written, geography, etc. This kind of
data-driven foresight is an invaluable advantage that companies cannot afford to ignore.

Uncovers new opportunities for the customer
Think Amazon, where AI powers the recommendations that are seen when we log in to our account such as the movies we should watch or the groceries we should buy. Increasingly, Amazon will be selling you things you didn't even know you needed because it has learned what you like and are most inclined to buy.

But to drive true transformation, you need to do more than simply illustrate how AI can help. CMOs need to empower their teams to give AI a try. Here are three steps a CMO can take to encourage her team to bake AI into the marketing mix:

Test, then perfect. Marketers love testing messages. Encourage a test of personalized messages, pitting messages created in a traditional fashion against those devised by an AI solution. Sit back and see which did the best. Quite likely you'll want more and more of your messages to be based on AI going forward.

Try it on one campaign. Select a campaign from initial touch points to the nurture process and let AI handle personalization of message/content, cadence, channels and segmentation. Assess the results, based both on campaign success and effort saved.

See the unseen. Help your marketers see what they may not be aware of by selecting an underserved segment in your database. Turn AI loose on it and get a better level of targeting.

Given its usefulness in so many areas, and on multiple levels, AI is destined to be a dominant force in marketing, sooner rather than later. It's time for the marketing organization to embrace AI to drive revenue, which can help your team produce more leads that convert faster, power ongoing customer engagement and drive higher lifetime customer value.

CMOs, it's now in your hands. Go champion efforts across your team to embrace AI's disruptive power. It's a smart pill you can't afford not to take.

Source: adweek
Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Follow on

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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