The Impact of AI: Ravi Dodda of MoEngage

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Ravi Dodda, Founder and CEO, MoEngage
Ravi Dodda, Founder and CEO, MoEngage

What are the main ways AI/machine learning will impact marketers and their work in the next year or two?

First: marketers are already taking advantage of AI in one point solution, user acquisition. However, they're really leveraging technology built by programmatic ad vendors. I see a big advantage for marketers to leverage AI to engage customers and prospective customers they've already introduced to their brand. All marketers want to engage, but they tend to focus on adding new customers each month rather than leveraging their existing customers and known prospects. AI can serve as an optimization engine to drive higher response and engagement levels.

Second: marketers will learn which tasks should be handled by team members, and which they can hand off to be automated. In this rapidly expanding market, it's easy to fall into a predictable pattern of collecting, analyzing, and interpreting data. Marketers will realize that some processes and decisions can be automated using AI, which will free them up to focus on more strategic decision making and planning.

Third: vendor overload. Marketers should prepare and educate themselves on how AI can best serve their organization, because they'll be subjected to an ever-increasing barrage of vendor options promising to solve their pains using AI. They'll need to sort through the noise and focus on how automated decision making can make an impact, so that they're ready to talk to vendors who can impact those specific areas of their business.

In summary, what will be the long-term impact of AI/machine learning on marketing?

AI will be an absolute necessity in managing the complexity that exists in today's marketing world. As digital channels like email, mobile, social, web, and others continue to evolve, they introduce many more variables that marketers must consider.

In a Harvard Business Review article titled “What is Strategy?”, renowned strategist Michael Porter talks about operational effectiveness. The idea is that, in order to build a foundation for success, you must perform similar activities better than your competitors. If your competitors and rivals are paying less to acquire new customers and drive recurring business from existing customers, and they're using AI to do so, you have no choice but to make sure your basic marketing operations are running efficiently as possible. Everyone will be adopting AI, and companies will be forced to do so or fall by the wayside.

How is AI/machine learning incorporated in the work you're doing?

We provide marketers a solution for messaging end users across multiple devices and channels using web-based push notifications, app push, email, and other methods. Most solutions approach digital marketing with a rules-based approach, but we took this concept a step further and evolved it using machine-learning-based action. We feel marketers need AI to do the heavy lifting around what message should be communicated, on which channel, and at what time.

In your experience, is AI/machine learning already affecting what brands do, or are awareness and adoption still very limited?

In my experience, AI is still limited in adoption. Marketers are definitely aware of AI, but only a select few are really moving forward to strategically adopt it to augment their teams. Most marketers are using point solutions to let computers optimize a purchase path sequence of events that leads to a purchase or engagement of some kind. Some are using tools to detect the intent to disengage, and then automatically messaging users accordingly.

In the world of customer acquisition, AI is being heavily used to maximize the ROI of money spent on acquisition, but that's different because marketers are actually relying on vendors to provide the tech and are simply realizing the benefits as a result.

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