This Emancipator track goes well with today’s post:
It was hardly 9 months ago that ChatGPT stormed on to the scene and surprised everyone with its capabilities. At the time, it was the fastest product to reach 100 million users (within 2 months) until Zuck’s “Threads” took that crown last month.
When I started writing Future Telescope 6 months ago, the first large scale application of generative text AI was seen outside of ChatGPT - the Bing GPT integration. It went on to have its moment in the spotlight, but failed to get Microsoft any traction in search engine market share. Not to forget the Sydney personality problems that were all over the headlines, haha!
With generative AI becoming more mainstream since then, it was only a matter of time before it was added to the OKRs of Product Managers across the world to add features related to AI to their products. So now, 6 months in, we are seeing some of the earliest examples of successful integration of these features in mainstream products.
Today, let’s look at some examples of this integration in the world of shopping, especially ecommerce.
1) Amazon’s AI highlights for Customer Reviews:
Amazon's using AI to summarize reviews right on product pages, highlighting common themes and sentiments. Customers can now tap to surface reviews about specific features like "ease of use". The AI only uses trusted reviews from verified purchases, and that should ensure authentic community opinions at a glance. A thoughtful and super useful implementation of generative AI technology.
Speaking of Amazon, last week, Decoder’s Nilay Patel spoke with the CEO of Amazon Web Services - Adam Selipsky. In this episode, they discuss Amazon’s role in the world of cloud computing and AI in a lot of detail. Check it out!
2. Shopify’s Magic
Shopify rolled out “Shopify Magic” - a tool that allows sellers to generate attention grabbing sales copy for their online stores.
All a merchant has to do is add keywords, and the AI tool generates descriptions from the same. The tool creates enticing descriptions with a consistent tone, saving merchants a lot of time. And with the mobile app, descriptions can be made on-the-go. For large catalogs, AI enables quickly crafting descriptions for all products. This has to be a huge time-saver if you’re a seller, allowing you to focus on business instead of writing.
Now imagine this - you’re trying to buy a product online, and think that it’s the right product for you, but you are left to decide whether you should purchase it or not just on the basis of poorly written descriptions. It’s not even the merchant’s fault because they were too busy working on the operations of running an ecommerce business to focus on writing good copy. This will now be an instance of the past, thanks to Shopify’s Magic tool. Woohoo!
3. Google’s Product Studio
Google's new AI-powered Product Studio helps businesses easily create unique product images for free. Merchants can add custom scenes or backgrounds and increase resolution of small images without reshooting.
This removes the chance for any scenarios of blurry or poorly lit product images that confuse you as a shopper. If you’ve used this product studio as a seller, do let me know your experience!
Conclusion
With AI tools becoming more mainstream, there is a wave of customer experience improvements underway. I can imagine these tools being put to use in different use cases like homebuilding (an AI tool that lets you design a home within the regulations of your area), horticulture (an AI tool that creates a nurture plan for the plants in your backyard), or for hobbyists (design a toy that you can assemble using household items).
The biggest USP of generative AI compared to previous types of computer systems is that it is creative. These algorithms work with unstructured data on large datasets and somehow find a way to make predictions on what the next word will be or what an image will look like. These systems are brand new and we are just figuring out how to use them to create a beautiful world.
If you’ve read this far, I have a treat for you. Here’s a 30 minute visual explanation of how a Neural Network learns - a delightful treat if you’re curious about how these AI systems actually come to life. Check it out!
I’ve been writing about this world for more than 6 months now, and am still amazed at the possibilities. Thanks for being on this ride with me, dear reader!
That’s it for the twenty-eighth draft, see you next week!
Nice explanation