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Generative AI: Moving beyond the hype

Brian Browning
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Practical advice on how to get started

Technology revolutions always seem to start with a magical spark that dazzles and draws global attention. The announcement of Generative AI technologies like Bard and ChatGPT shook the world with the profound new ability to create seemingly intelligent interactions through a simple, familiar conversational interface.

Suddenly, it was easy to get answers to complex problems and to even extend that to more human-like attributes, like humor or slang. Panic set in as the future of jobs were questioned: would it replace artists? Authors? Engineers and Marketers?

This illustrates that the magic behind the miracle is actually built on years of natural language processing. Recognizing patterns, connecting data points and applying powerful algorithms to expose meaningful insights, governed by the data that it is trained on. In fact, tools like ChatGPT and Bard, are the latest application of artificial intelligence, specifically focused around content creation, also known as Generative AI, or GenAI.

We’re just beginning to uncover how best to apply this latest evolution in technology in the chaos and complexity of the real world. As more companies think about how to approach this innovation, Kin + Carta is experimenting with various use cases, working with customers to directly leverage the hype of Generative AI and hedge against its perils.

This experience was recently highlighted at our Kin + Carta FWD: Retail event, held in Seattle, WA. Kin + Carta brought together customers, partners and GenAI subject matter experts to discuss how to navigate this complex and evolving landscape. Using an agile mindset and de-risked approach, we have found that leveraging Generative AI in very specific, low-risk use cases for retail and Ecommerce can pay tremendous initial dividends and build momentum to even larger opportunities.
Generative AI represents a powerful way in which product descriptions and related content can be both rewritten for different tones, audiences, use cases, adaptations, all at scale
Brian Browning, VP, Experience & Product Service Line
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Practical use cases of Generative AI

Based on our own experience, here are several specific use cases for GenAI that balance reward versus risk to deliver notable results:

  1. Personalized experiences
  2. Leveraging A/B/N and multivariate testing
  3. Product data
  4. Optimize for SEO
  5. Adapting existing content and repurposing it to a specific audience

Personalized experiences

Personalized experiences are well known to boost engagement, conversion and to add differentiated value to a customer experience. The greatest business value for personalization happens at scale, but the challenge is centered around the sheer volume of additional content required. 

Generative AI is a powerful way to take the baseline content you’ve already created and to scale it to the needs of personalized audience segments. GenAI can also evolve these tailored experiences over time because GenAI is not static, but instead learns from high-performing content and applies it at scale over long periods of time.

Leveraging A/B/N and multivariate testing

Similarly, leveraging A/B/N and multivariate testing, and live explore/exploit scenarios, allows retailers to better discover messaging, content and experiences that drive conversion. Again, the primary value for experimentation occurs at scale and suffers from the same challenges requiring exponential increases in content generation. Generative AI can automatically generate variations of baseline content, scale the testing automatically and deliver on the promise of experimentation at scale. 

Product Data

Commerce experiences rely heavily on product data to better promote and demonstrate the value of a product or service. Many organizations recognize the potential value of this content but struggle to maximize the effectiveness of this content. Generative AI represents a powerful way in which product descriptions and related content can be both rewritten for different tones, audiences, use cases, adaptations, all at scale. 

 

Combined with personalization and experimentation, optimized product data represent another powerful avenue where Generative AI can solve fundamental problems of content generation. To illustrate this point:

 

  • Victoria’s Secret followed this approach using a platform called Writer. The results were powerful - they enhanced more than 6,000 SKUs long product descriptions, resulting in a 23% improvement in CTR to shopping cart.
  • AdoreMe also enjoyed improved CTR using writer.ai and allowed their content writer to reallocate 20 hours per month to other tasks. 

Optimizing for SEO

Optimizing for SEO is a well established way for external search engines to index a company’s products and services to build customer awareness. SEO optimization is time-consuming to maintain properly. Summarizing page content into SEO optimized tags and auto-generating descriptions and keywords are all tasks that Generative AI automates to free up content authors and editors alike. 

We expect that using GenAI for this use case will become the norm in the future and companies that recognize this opportunity will have a limited advantage as Google adapts its indexing approach in the future.

Adapting existing content

Finally, adapting existing content and repurposing it to a specific audience or even to an individual is a leading use case that demonstrates the power of Generative AI. Some organizations are taking highly technical content and having GenAI produce less technical versions of the content that are better suited toward non-technical business buyers. Others are exploring ways to redirect content to different audiences, like adapting content for Millennial consumers. 

Diving in: Start with smaller wins, measure gains, and build momentum

This list represents just an example of the powerful results Generative AI can provide. Businesses are seeing compelling results by investing in this technology, but we’re really only scratching the surface.

While risk exists with this (and all) technologies, we’ve found that it makes sense to start with smaller wins, measure gains, and build momentum toward larger, more full-scale evolved ways of working. And the future is incredibly compelling when it comes to Generative AI; we’re already exploring how it can revolutionize customer service, inform chatbots to deliver human-like experiences and much, much more.

Let us help you brainstorm and identify use cases with GenAI that can help move the needle. We encourage you to reach out and start a conversation with one of our Generative AI experts.

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