Reimagining Rev-Ops with Gen AI: Precision Marketing 

This is the third part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In the second article, we explored how GenAI use cases are being developed and deployed in the first of the four core Rev Ops pillars - business strategy and planning. In this article, we move on to the second Rev Ops pillar- Marketing.

\ A little bit about myself - I am a Sr. Director of Rev Ops at Cisco. Here is my LinkedIn profile - prior to Cisco, I was a Manager at McKinsey, with a background in Industrial Robotics and Electrical Engineering.

\ Marketing is one of the principal functional areas that is primed to leverage the full potential of generative technology : multi-modality (text, audio,and video), scale, rapid iteration, automation, and creativity- all can be leveraged to unlock a step-change in how Marketing is executed. And Enterprises big and small are already leveraging these capabilities in their day-to-day.

\ Key advantages of Gen AI in marketing:

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• Enhanced customer understanding at scale: GenAI based capabilities help generate  deeper insights into customer preferences and persona, from a variety of structured and unstructured data including video interactions, customer feedback, product / service usage, and telemetrics to generate a truly 360 degree view of customers and leads, improving conversion rates and quality of engagement. Systems are already capable of taking this a bit further, generating product recommendations, as shown by Stitch Fix.

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• Hyper Personalization at scale: Previously, marketing efforts had to be prioritized to the biggest customer opportunities, and the best that B2B sales came to personalized marketing was Account Based Marketing. Gen AI offers the ability to deliver unprecedented levels of personalization of campaigns and strategies at scale. Marketers can now go beyond audience segments and be truly personalized even in lower tiers like SMB which previously were starved of quality marketing resourcing.

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• Content creation and automation : Gen AI is multi-modal, and can be extremely creative, reducing time and resources required to create individualized marketing campaigns, collateral, landing pages, and email campaigns. What previously took weeks, can now be accomplished in hours with a fraction of the manpower needed. Companies that are leveraging AI to generate extremely personalized email campaigns have already started seeing differentiated results.

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• Marketing Analytics and Strategy: Gen AI has unprecedented ability to combine vast and disparate data sets to generate reliable and nuanced insights faster. It enhances the accuracy of key tools of marketers such as attribution mix modeling, media mix optimization, and Search Engine Optimization, while lowering marginal cost dramatically. It also facilitates rapid experimentation and A/B testing, and optimization of campaigns across multiple dimensions. One no longer needs an army of analysts to support a growth campaign- just the right combination of skills and tools.

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• Automation and efficiency: McKinsey estimates that gen AI could increase marketing productivity by 5-15%, worth about $463 billion annually. The productivity enhancement is expected to happen across three dimensions: human augmentation (providing leverage to human teams, helping them scale), automated agents working alongside humans to accomplish complex tasks, and eventually, through the creation of automated teams that own significant portions of workflows. What sounded like distant future is almost here today - and the race is on to be the first and best at leveraging the potential of this technology to the fullest extent.

\ As the Gen AI landscape and capabilities evolve, adoption is expanding and new workflows and applications of Gen AI in Marketing are being uncovered rapidly. The rich entrepreneurial activity in this space is testament to the value at stake. But as the industry collectively navigates this space, it will be important to do so with adequate guardrails around privacy, and content rights - two of the most important concerns with the evolution of Gen AI. And these concerns are extremely valid and noteworthy in this space. It will be interesting to watch how industry, advocate groups and governments come together to shape this space in the coming days.

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