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Three advances in AI and ML: From Awareness to Action and Decision

Artificial intelligence (AI) technology is evolving rapidly and becoming mainstream in a myriad of business scenarios. AI has enabled many exciting capabilities, including highly accurate target marketing, predictive models and planning tools, and intelligent bots for customer service.

But those of us already deeply involved in AI are already looking forward to what’s next on the horizon. Here are three prominent next-mile moves that will advance AI: 

Natural language generation (NLG) for self-learning, intelligent systems

Today, there is no dearth of platforms to express one’s opinionHerein lies the challenge for enterprises. Putting a wrapper around potentially billions of sentiments is impossible, especially when they come from so many disparate sources. This is where natural language understanding (NLU) and natural language processing (NLP) shine—enabling you to automate these sentiment crawlers to perform text analytics on unstructured data.

Adding a layer of NLG changes the game altogether. Consider a leading technology giant’s marketing team faced with challenges—they run aggressive marketing campaigns to attract and retain customers, with a customer database of 5M. They are releasing a new product and want their customers to know and act on it. To do so, the team wants a campaign that is ultra-targeted to reach the right audience at the right time and with the right product offer.

Most enterprises at this scale have templatized their push marketing messages. However, the efficacy of this approach is questionable—value to customer is subjective, conversion rates can be low and loyalty is inconsistent. Personalized messaging is key to addressing all three of these challenges. 

This is where the client leveraged ML & AI in combination with NLG. 

NLG allowed structured data to be translated into prescriptive content, keeping the buyer personas in mind.  The client saw a five percent increase in click-through rates after deploying NLG-based email campaigns, along with a four percent increase in purchases. Considering the volume of customers targeted for this one campaign, the impact is measured in the millions of dollars—and the algorithm, now that it’s built, can be used for multiple future campaigns. 

NLG represents the last mile in terms of converting insights into meaningful content, which in turn drives action. Triangulating NLU, NLP and NLG renders greater personalization, instant redressal, higher accuracy and improved customer lifetime value. This is the future of marketing.  

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