In an ever-changing marketing landscape, one technology is emerging as a potential pivot: Generation G AI. Seen as a way to help businesses go further, faster and more efficiently, does it also hold the key to a new way of creating campaigns?
I recently discussed this topic and more with Rio Longacre, Managing Director of Slalom, and Jon Williams, Global Head of Agency Business Development at AWS.
Gen AI: Understanding the Mania
In our conversation, Longacre describes a paradigm shift in the AI landscape of the generation. Beyond experimentation, companies are now charting strategic paths, identifying areas where they can truly make a transformative difference.
“There’s been a sea change in the last few months, which is very positive. Instead of just trying different things, the idea is now to adopt a generative AI strategy. Companies are looking to identify areas where generative AI could make a big difference and make a difference. They want to invest in those areas, whether it’s e-commerce, operations or creative. They want to find ideas that might work and test them. If they work, great. They’ll look to commercialize them. If they don’t, that’s okay, then they can change course and try something else.”
The Future of AI as a Marketer
Williams explains where Gen AI excels as a marketing assistant, so to speak. “Amazon Q is a new type of AI-powered generative assistant that can be used specifically for a job tailored to your business to have conversations, solve problems, or generate content. It uses data and expertise found in your company’s information repositories, such as code bases and enterprise systems.
“You can use Q, for example, to:
- Learn a brand style guide, then
- Use this information to turn a press release into a blog post that meets these standards, then
- Analyze how a brand appeared on social media, then
- Create new messages around these releases that will make sense to subscribers, then
- Analyze the results of these publications, and finally
- Summarize them to review as a team
“It’s almost like a vicious cycle of incremental productivity that happens by leveraging some of the generative AI capabilities that are being used through a bot but are connected to the systems and data that your company has. We’re in the very early stages of that process, which is pretty exciting.”
According to Longacre, there are three ways marketers are using Gen AI to gain efficiencies and save money:
- E-commerce business: This company wrote descriptions for 10,000 product SKUs using Gen AI in just a few weeks, saving them months of time and about $1 million.
- Paid media campaigns: When it comes to paid media tools, such as those built for Amazon Marketing Cloud, there is a background image generator specifically designed to create lifestyle images. Results show a remarkable 20-25% increase in conversion rates for products featured with lifestyle images versus those with a plain white background. Deploying these features quickly, testing their effectiveness, getting results, and then optimizing based on those insights is a game changer.
- Banks and finance: The bank’s creative briefs are now generated by artificial intelligence, reducing the time spent on exchanges with agencies by around a week.
Even with segmented strategies, brands often face resource challenges. Accelerating the creation of creative briefs, creative images, and product descriptions enables faster personalization of on-site experiences. This progression toward personalization doesn’t require them to adopt a “hands-free” mode where the generation AI truly runs the show. Instead, it’s truly a true one-on-one chatbot interaction or conversational AI.
Keeping Humans Informed with AI
Longacre points out that every use case he shared involves a human in the loop. Given that we’re in the early days of AI, this isn’t surprising, as most brands start with “human in the loop” use cases. This is where AI generates results that a human then approves and can eventually refine. “Human in the loop” use cases enable productivity gains while minimizing the risks of hallucinations or unexpected results.
“Maybe the copy is written by Gen AI, but a human reviews it,” Longacre says. “The image may be generated, but it’s not released into the wild.”
“We’re starting to see a little bit of that, but generally there’s human oversight. Even with chatbots. I mean, chatbots have been around forever. Most of them are machine learning-based. You have to know, ‘OK, when do you have escalation? Where do you go from the chatbot to a real person for certain use cases?’ Identifying that is always extremely critical.”
Prepare your brand for success with Gen AI
When developing a generative AI strategy, Williams highlights five key elements that play a critical role in ensuring success. These include:
- Technology stack: Your tech stack is critical. You need to be able to explore patterns, test use cases, and choose the right ones.
- A solid and mature first-party database: Generative AI relies on data to function properly, which means you need to have strong data storage and ingestion management capabilities to ensure that proprietary data is accurate and as close to real-time as possible to ensure the accuracy of model outputs.
- Human surveillance: You still need human intervention in the loop to make sure that what you thought was going to happen happens and that there are no anomalies.
- AI-specific analysis skills: Leveraging AI requires the ability to accurately interpret and apply the results of AI models. You need to ensure your teams have the expertise to understand how the tools work and how best to leverage the data.
- Process redesign: Consider existing processes or workflows that need to be reorganized to take advantage of general AI.
Start small with AI for big results
My advice to brands and organizations deploying AI: start small. I would start with a small use case that is highly measurable and doesn’t require major changes. Clients we work with have had great success optimizing the subject line or body of emails or paid ads. Since you can have a human in the loop, this is a great opportunity to experiment with creating different segmentation strategies and messaging.
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