Programmatic
After decades of investment and innovation, programmatic has helped solve engineering challenges and provide solutions for targeting, transparency and attribution. What it hasn’t done—that generative AI has the power to fix—is deliver on its initial promise to tell personalized stories at scale.
There is a novelty aspect with generative AI, and some of the effects are new: Aside from the visible styling elements, hundreds of invisible elements are being generated, deciding which variation to show to the user, who only sees the winning design. For example, Cadbury’s ad campaign in India cloned and synthesized Shah Rukh Khan’s face and voice to include local shop names and towns, delivering personalized versions of the ad based on user location.
The application of gen AI, invisible to the consumer, can be implemented in the programmatic ecosystem in several ways, the simplest of which is engineering creative for the runtime using the size of the slot (given screen size and shape), background color, environment and other contextual signals available on the OpenRTB pipe. This is a very repeatable exercise and can be done at scale in 1-3 seconds, but the question is whether variants have the same impact as the original. —Abhay Singhal, co-founder, InMobi Group; CEO, InMobi Marketing Cloud
Chatbots
AI chatbots in customer support are only as good as the number of inquiries they can automatically resolve. It’s as simple as that. The North Star measurement should be automated resolutions (AR), which we define as a conversation between a customer and a company that is relevant, accurate, safe and does not involve a human.
Oftentimes, customer support leaders vetting different AI solutions can get lost in a list of features and capabilities, but these details mean nothing if they aren’t helping you automate more resolutions. Our advice is for them to ask, “How does this product help me increase AR?” —Mike Murchison, CEO and co-founder, Ada
Podcasts
AI-powered text-to-speech systems have been used to convert written content into natural-sounding audio for some time. It’s being used to create voice clones for podcast hosts and “guest” features; AI-based algorithms can enhance audio quality by reducing noise, eliminating background disturbances and improving overall sound production; platforms can leverage gen AI to deliver recommendations to listeners based on preferences, listening history and behavior. We now leverage tools to produce accompanying transcriptions for every episode, promoting the accessibility of our clients’ podcasts and minimizing human error while boosting SEO performance.
When it comes to value, the three main areas are time-saving, personalization and enhanced creativity. During editing and post-production, gen AI ad insertion saves podcasters time and effort, and personalized recommendations enhance these advertising efforts as well as the listening experience. And gen AI has enabled podcasters to experiment with unique voices, soundscapes and storytelling approaches not previously feasible. —Fatima Zaidi, founder and CEO, Quill