Beyond The Buzz: 7 Ways Brands Can Use ChatGPT And OpenAI For Boosting Sales On Amazon

AI tools like chatGPT, openAI and DALL-E have dominated the newsfeed of marketers the past few months. But how much is simply buzz, versus a business opportunity that’s actionable right now?

I personally believe that this is just the start of a big shift in how we implement digital marketing strategies across many channels. Many more use cases will come out of the woodwork with further experimentation and technology overlays. In a few months or even weeks I hope to look back on this list and consider it narrow and elementary.

But for now, here are seven specific ways that brands can leverage these tools right now to improve the quality and efficiency of their Amazon
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marketing efforts.

1. Generating keywords.

The retail media buying team at my agency Acadia have started using chatGPT for this purpose. A prompt might be ”Populate 10 non-branded keywords for an amazon ppc campaign, related to the product “YOUR PRODUCT NAME”. But don’t stop there. Ask the AI to get more specific, more detailed, or even widen the parameters. “Make them shorter,” or “Use more technical words,” can net more results and more relevant results.

This can make the keyword research stage much more efficient, and ensure it does not get relegated to a one-time project. Revisiting keywords periodically is important as consumer trends and the competitive landscape changes over time.

2. Creating headlines for ads.

Ad types like Sponsored Brand ads on Amazon rely on benefit-driven headlines. Amazon has some requirements for this ad type including the copy being less than 50 characters. Provide these parameters to the AI, and you can get a great starting point to test new messages inside retail media.

3. Generating images.

AI imagine tools like DALL-E can be used to generate custom images for product pages, brand storefronts, Amazon Posts, and more.

Russ Dieringer, a retail industry analyst at research firm Stratably, says that DALL-E can be the starting point for an image. “It can create something you might not have thought of – and then the team can download that image and make whatever edits they want from there.” One limitation right now is that the AI is most effective at representing items and concepts that are already widely represented on the internet. This means DALL-E is currently most suitable for general lifestyle content, rather than pulling in images of your particular product.

There is also an editing capability, where you can replace portions of the image, but it’s fairly limited. I am personally excited to see AI do more robust image editing in the future. “Merge these 3 images to create a single hero image that is 3,000 px by 1,500 px” or “Show a single unit of [X product] next to a case pack,” or “Make a variation of this image for Amazon Posts” would all be amazing shortcuts for brands who are struggling to keep up with the huge quantity of content required to keep their product and brand content fresh.

4. Generating product copy.

Use AI as an entry point for product content that leads with trends or market differentiators. Here are three approaches.

1. Ask AI for trends in the product category, then cue up the AI to expand on the most relevant points. Another query being used by my team is “What are some growing trends inside the YOUR PRODUCT CATEGORY market.” Mention these trends on your product content and advertising messages too.
2. Address your competitors’ weaknesses. Chad Rubin, founder and CEO of Profasee, uses a process to export competitor’s Amazon reviews, have the AI summarize the negative reviews, and then ask the AI to take negative reviews and create benefit statements for each negative. These can be used on your own product listing, to address the concerns of customers who are shopping around in your category. “Your potential customer who is reading those negatives of your competitor will be compelled to take “add to cart” action,” Rubin says. The reverse approach could be used as well, taking positive reviews to develop copy that addresses product attributes that your customers love.
3. Use the various copywriting frameworks that AI has knowledge of, to organize the key marketing messages. Ask the AI to generate content that uses the ‘Attention-Interest-Desire-Action’ framework, the ‘Before-After-Bridge’, or the ‘Problem-Agitate-Solve’ framework, for longer-form copy in the product description, to really tell the story of your brand.

What’s the downside?

The risk with relying too much on AI driven content is that everything starts to look and feel the same. If all cat food brands start using the same query to generate headlines for ads, for example, they may all start using the same copy for those ads. We may end up with a lot of product and brand content that sounds the same, repeating the same trends and customer use cases.

But that’s where the point of AI ends and the requirement for brands to measure and test effectiveness of their efforts begins. These prompts should be viewed as either a starting point, not a shortcut. There still needs to be someone with a hand on the wheel, reading the dashboard and adjusting course.

To stand out from the crowd, brands will need to consider AI as a tool in their toolkit rather than the author of their positioning on Amazon.