Amazon Will Get You Selling Faster With AI Robotics

Plus: Exclusive Interview With Danny McMillan

Author

Jo Lambadjieva
October 24, 2023

Hey there! I am thrilled to share with you a very special interview this week with Danny McMillan. We spoke about Amazon’s Project Nile and what it means for sellers. Enjoy!

Why are you reading this?

In this newsletter, I summarize the top AI ecommerce and Amazon developments so you can stay up-to-date in just a few minutes. I do the reading so you don't have to. Consider this your weekly AI ecommerce update to save you time while keeping you informed on what matters most.

TL;DR

  1. Amazon Boosts Warehouse Operations with AI and Robotics

  2. YouTube Introduces AI-Powered "Spotlight Moments" for Advertisers

  3. ChatGPT Fine-tuning

  4. Exclusive Interview: Danny McMillan On Amazon’s Project Nile

Amazon Boosts Warehouse Operations with AI and Robotics

Amazon is set to re-haul its warehouse processes by integrating advanced AI and robotic systems. This move aims to expedite deliveries and manage inventory more efficiently. The new robotic system, named "Sequoia", is designed for speed and ensures safe collaboration with human workers. Through Sequoia, items can be put up for sale faster on Amazon's site, and it will lead to more accurate delivery predictions. Furthermore, it speeds up the order fulfillment process by up to 25% and enhances inventory recognition speed by 75%.

This innovation is part of Amazon's ongoing effort to amplify its delivery speeds in response to rising competition. The revamped system involves transporting products in tote containers to a new sortation machine, which uses robotic arms and computer vision.

What does this mean for ecommerce sellers?

Probably for Amazon sellers this is just good news (unless Amazon starts hiking fees again) as it will enable products to be available for sale faster, fulfilled faster (think happy customers) and hopefully less damages.

YouTube Introduces AI-Powered "Spotlight Moments" for Advertisers 

YouTube is tapping into Google's AI technology to offer a new ad feature called "Spotlight Moments." This new feature uses AI to automatically detect trending YouTube videos associated with particular cultural events—think Halloween, the Oscars, or a sports match. Advertisers can then display ads on videos discussing those specific topics on a dedicated branded channel, where content is grouped into ever-changing playlists.

Spotlight Moments joins YouTube's other AI-driven projects such as Video Reach and Video View campaigns, both benefiting from Google's AI.

While AI's role in advertising isn't novel, Google envisions a future where generative AI reshapes ad sales and placements. For example, Google Ads now features a natural language chat, and generative AI is used to auto-generate assets for Search ads, pulling from brand webpages and existing ads to devise new headlines and descriptions.

What does this mean for ecommerce sellers?

This is just the start of how AI will shape advertising going forward. My prediction is that everything from how ads are created, displayed and measured will be driven/created by AI.

Need To Know: ChatGPT Fine-tuning

What is Fine-Tuning? Think of fine-tuning as a way to make ChatGPT better suited for specific tasks or industries. Just like a marketer might tailor an ad to fit a certain audience, fine-tuning customizes the ChatGPT model to provide better answers for a specific use-case.

Why Would You Use Fine-Tuning?

  1. Get even better answers than the usual model.

  2. Save time and money with shorter, faster requests.

  3. Improve reliability, handle unique requests, or even teach the model a new skill.

How Does it Work? It's like training an employee. First, you give the model lots of examples of what you want. For instance, if you're making a sarcastic chatbot, you'd feed it sarcastic conversations. Once trained, the model will start replying in a similar tone without needing as much instruction from you.

When to Consider Fine-Tuning? Before diving in, try to get the best out of the standard model. Sometimes, just by asking it the right way, you can get the answer you need. But if there are specific quirks or styles you want to embed, fine-tuning is your go-to solution.

Things to Remember:

  1. You need examples to teach the model. Like showing an employee what to do.

  2. Not every fine-tuning needs tons of examples. Sometimes, 50 well-made ones can do the trick.

  3. Costs depend on the number of examples and how deep you train the model. Always keep an eye on the budget.

In a nutshell, fine-tuning is a way to make ChatGPT even more tailored to your needs, ensuring it provides the exact answers and style you're looking for.

To fully understand the process, dive in here.

What does this mean for ecommerce sellers?

This is essential homework for any business using ChatGPT especially companies with a lot of data that can be used to train the AI to get better and more relevant input.

Exclusive Interview: Danny McMillan On Amazon’s Project Nile

Danny is the host of Seller Sessions, one of the largest podcasts for advanced Amazon sellers.

Danny is also the co-founder of DATAbrill. Working alongside respected algorithm expert Dr. Ellis Whitehead, DATAbrill manages PPC and advertising automation for 7 and 8 figure Amazon brands.

He also runs the annual conference Seller Sessions Live and is known for his work breaking down A9 and how it works based on the science literature.

To get in touch with Danny, head here.

I wanted to get Danny’s unique perspective on Amazon’s project Nile. Here is an excerpt of the interview.

JL: What do you think about the announcement of project “Nile”? Were there any surprises for you?

DM: A9 already uses Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP)—I have numerous papers covering this. These technologies help the algorithm to understand and interpret user queries, rank products based on relevance, and continuously learn and adapt to changes in user behavior and preferences.

The biggest challenges Nile will need to overcome are Bias, Accuracy, and Data Privacy.

JL: Do you think there will be changes in the A9 algorithm to accommodate this? What do you envisage?

DM: Their end goal is relevance; serving the best search experience to the customer.

Sellers should focus on everything around the product (and market fit) and not hacks (see these as a bit of fun on the side). No amount of hacks can save a subpar product. Invest 95% of your time in getting the product right; if you get that bit right, the rest is much easier to execute.

JL: Do you think Amazon will replace seller support with AI eventually?

DM: Amazon has been using AI for at least three years now. It’s called Cuatro AI and will get better, though some of the responses from support tickets leave a lot of room for improvement. However, support is bad enough already—imagine if you removed all the humans too?

The Quick Read:

Today’s Content Spotlight:

I’m speaking with a lot of ecommerce sellers who are not sure where/how to start with AI and how to get their team going. I’ve put a small framework to help you with this.

The Tools List:

Moonhub.ai - Your AI Powered Recruiter

Sybill.ai -Sybill understands your sales conversations to write your CRM updates, follow-up emails, and accurate call summaries.

Zupyak.com -Get more customers from search engines

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