Content Marketing

Will AI be your next marketing assistant?

Will AI be your next marketing assistant?

Joyce is the head of generative AI at Amperity, leading product development and strategy. Previously, Joyce led product development for many of Amperity’s ML and ML Ops investments, including launching Amperity’s predictive models and infrastructure used by many of the world’s top brands. Joyce joined the company in 2019 following Amperity’s acquisition of Custora where she was a founding member of the product team. She earned a B.A. in Biological Mathematics from the University of Pennsylvania and is an inventor on several pending ML patents.

In the ever-evolving marketing landscape, one technology emerges as the potential linchpin – Gen AI. Revered for helping businesses move further, faster and more efficiently, does it also hold the key to a new way of creative campaigns?

I recently discussed this topic and more with Rio Longacre, MD at Slalom, and Jon Williams, global head of agency business development at AWS.

Gen AI: Making sense of the mania

During our conversation, Longacre describes a paradigm shift in the Gen AI landscape. Moving beyond experimentation, companies are now forging strategic pathways, identifying areas where it can genuinely make a transformative difference.

“Within the last few months, there’s been a big shift, which is very positive. Instead of ‘let’s just try different things’, it’s now, ‘let’s have a Gen AI strategy’. They are looking to identify areas where Generative AI could make a big difference and move the needle. They want to invest in those, whether it’s eCommerce, operations or creative; they want to come up with ideas that could work and test them. If they work, great. They’ll look to start to commercialise them. If they don’t, that’s OK too, then they can pivot and try something else.”

The future of AI as a fellow marketer

Williams shares where Gen AI is shining as a marketing assistant, of sorts. “Amazon Q is a new type of generative AI-powered assistant that can be used specifically for work to be tailored to your business to have conversations, solve problems or generate content. It uses the data and expertise found in your company’s information repositories, such as codebases and enterprise systems.

“You could use Q, for example, to:

  • Learn a brand style guide, then
  • Use that information to turn a press release into a blog post that adheres to those standards, then
  • Analyse how a brand has shown up on social media, then
  • Create new posts around those releases that will make sense to followers, then
  • Analyse the results of those posts, and finally
  • Summarise them for review for teams 

“It’s almost like this self-fulfilling circle of incremental productivity that’s happening as a result of leveraging some of the generative AI capabilities that come to use as a result of a bot but are plugged into the systems and data that your enterprise organisation owns. We’re only in the very early stages of that, which is pretty exciting.”

3 Ways marketers are leveraging Gen AI for greater efficiencies and cost-savings, according to Longacre:

  1. eCommerce company: This company has written descriptions for 10,000 product SKUs using Gen AI in a couple of weeks, saving them months of time and about a million dollars.
  2. Paid media campaigns: As it relates to paid media tools, such as those designed for Amazon Marketing Cloud, there’s a background image generator specifically tailored for crafting lifestyle images. Findings indicate a remarkable 20 to 25% increase in conversion rates for products showcased with lifestyle images compared to those with a plain white background. Swiftly deploying these features, testing their efficacy, obtaining results and subsequently, optimising based on these insights is a gamechanger.
  3. Banks and finance: The bank’s creative briefs are now being generated by artificial intelligence, reducing the time spent on back-and-forth communication with agencies by approximately one week.

Even with segmented strategies, brands often face resource challenges. Accelerating the creation of creative briefs, creative imagery and product descriptions allows for a faster customisation of on-site experiences. This progression toward personalisation doesn’t require them to go in a ‘hands-off’ mode where Gen AI is really running the show. Instead, it’s truly like a genuine one-to-one chatbot interaction or conversational AI.

Keeping the human in the loop with AI

Longacre points out that every use case he shared has a human in the loop. Since we’re in the early days of AI, that’s not surprising as most brands are starting with ‘human in the loop’ use cases. This is where AI generates outputs that a person then approves and potentially refines. ‘Human in the loop’ use cases enable productivity gains while minimising risks arising from hallucinations or unexpected outputs.

“Maybe the copy is being written by Gen AI, but a human reviews it,” Longacre says. “The image might be generated, but it’s not being pushed out 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 were machine learning based. You need that knowing of, ‘OK, when do you have the escalation? Where do you pass from the chatbot to a live person for certain use cases?’ Identifying that is still super critical.”

Setting your brand up for success with Gen AI

In the journey of crafting a Generative AI strategy, Williams points out five key elements that play a pivotal role in ensuring success. They are:

  1. Tech stack: Your tech stack is vital. You should have the ability to explore models, test use cases and choose the right ones.
  1. A solid, mature first-party data foundation: Generative AI relies on the data to function properly, which means you must have robust data ingestion storage and management capabilities to make sure that the first-party data is accurate and as close to real time as possible to provide accuracy in the model outputs.
  1. Human oversight: You still need that human in the loop intervention to make sure that what you thought was going to happen is happening and there are no anomalies.
  1. AI-specific analysis skills: Leveraging AI requires the ability to interpret and accurately apply AI model outputs. You must ensure that your teams have the expertise to understand how the tools work and how best to put the data to work. 
  1. Process redesign: Consider existing processes or workflows that need to be resigned to take advantage of General AI.

Start small with AI for big results

My advice to brands and organisations when rolling out AI: start small. I would start with a small use case that’s highly measurable and one that doesn’t require major change. One place where clients we work with have seen a lot of success is just with subject line optimisation or optimising the body of emails or paid media ads. Since you can have a human in the loop here, it’s a great opportunity to experiment with creating different segmentation strategies and different messages.

Interested in hearing leading global brands discuss subjects like this in person? Find out more about Digital Marketing World Forum (#DMWF) Europe, London, North America, and Singapore.

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