If you’re new, welcome! If you’re a regular, thanks for being here as we navigate this AI shift in eCommerce. I share what I’m testing and what’s actually moving the needle. Where’s the vault you ask? Every previous edition is saved here.

In this edition (shortcuts):
Claude Found the Gap Between Our Two Best Reports💥
How We Made Sure We Did Not Go Out of Budget on Prime Day
ChatGPT’s New Schedules Feature!
News Worth Reading

Every week, new keywords show up in our clients’ Search Query Performance reports.

Real customers, typing real searches, and Amazon is already putting our products in front of them. For terms we had never added to our keyword rank tracker.

And we used to miss some of them.

Not because the data was hidden. It was right there in SQP. We just were not catching the new ones fast enough to start tracking them and bidding on them. Why? Because it is a manual process, and manual processes are always flawed.

So we built a Claude skill to fix it. Then we turned it into a Routine so it does the catching for us.

If you have Brand Registry, you have Search Query Performance inside Brand Analytics.

It is not a keyword tool guessing at search volume. It is Amazon telling you the actual queries customers used, and whether your product showed up for them.

That is the part most people skip past. These are not keywords you brainstormed. These are keywords Amazon already decided your product is relevant for. The demand is proven. The only question is whether you are tracking it and ranking for it.

New ones appear all the time. Buyer language shifts. Seasons change. A term nobody was using last month starts driving impressions to your listing this month.

If your rank tracker only watches the keywords you already knew about, you never see the new ones coming.

We built a Claude skill that compares the SQP keywords against the keywords already in our rank tracker, and flags anything new.

No exporting. No copy paste. No sitting there with two tabs open trying to spot what changed.

The reason it can do that is simple: both reports already live in our data warehouse (Big Query). The SQP data and the rank tracking data are sitting in the same place. So the skill just reads both, lines them up, and tells us what is new. Nothing to download, because nothing left the warehouse to begin with.

The output from Claude is simple. It tells the keywords showing up in SQP reports that you we not tracking yet.

The skill worked. But someone still had to remember to run it.

So we turned it into a Routine. Now it runs on its own and tells us what is new. Our standard approach is to send these auto-generated emails to the right team members for their accounts.

Here is the thing that stuck with me.

The skill is not just about SQP. It is about the gap between any two reports that should be compared and almost never are because of the manual effort required.

You have plenty of these. Your search term report and your negative keyword list. Your prices and a competitor's. Your reviews and your own bullet points. Each one is fine on its own. The signal is in lining two of them up, and that is exactly the work that keeps getting pushed to next week.

Claude is good at that. Reading two sources and telling you where they do not match. That is the quiet advantage.

Know anyone who wants to work with an agency that has AI and tech in their DNA and are pros at managing advertising and creatives for E-commerce? Forward them this newsletter and let them connect with us at [email protected].

If you run super successful, money-printing ads on Amazon, you know the worst mistake you can make is running OOB (Out of budget) on them.

Your campaign hits its cap, the ads stop, and you go dark right when shoppers are still buying. On a normal day it stings. On a big traffic day it is money walking out the door.

We did not want to find out hours later that we had gone dark. So we built a Claude Routine to watch for us.

It runs every three hours through the event and does one job: tell each person on my team exactly which of their campaigns have gone out of budget, so they can top them up fast.

But a raw list of every OOB campaign is just noise (also, we could have made it hourly but we felt that was too noisy for the team). So we made it smart about what actually counts:

🔶 It only flags campaigns that are genuinely out of budget and still turned on
🔶 It skips campaigns whose whole portfolio is already capped. No point chasing those, the limit is somewhere else.
🔶 It ignores campaigns that have not been spending anyway. Dead weight does not need an alert.
🔶 It groups what is left by account, so each person gets only their own campaigns to deal with.

Here is the part I am proudest of. It only emails you when your list has changed since the last check. If nothing moved in the last three hours, you get nothing. No alert fatigue, no inbox full of identical snapshots. Just a tap on the shoulder when something actually needs you.

Think about how different that is from babysitting a dashboard. Nobody had to remember to look. The Routine watched, filtered out the noise, and pinged the right person at the right moment.

Now, could we have used an Amazon Budget rule for this? Sure, but that would be WAY limiting in triangulating our specific set of requirements of noise. Plus, it would miss the side bonus of team members noticing which campaigns are actually running out multiple times in a day with our alert counter.

The lesson holds beyond one event. Most people manage budget by checking whether it already ran out. The better move is to let something watch the pace for you and speak up only when it matters.

Here is a small feature that quietly took a task off my plate.

It is called ChatGPT Schedules. You give ChatGPT a job, you tell it when to run, and it emails you the result. That is it.

I use it to keep tabs on a product I follow closely. I told it to search every week for any real news: can people test it, demo it, join a waitlist, preorder, or buy, and to email me a summary. Now every Monday it just shows up in my inbox.

I could have built this with Zapier. But honestly, why bother. This was easier, and I am already paying for ChatGPT.

You will find Scheduled Tasks inside ChatGPT (you need a paid plan).

You write the instruction in plain English, pick how often it runs, and you are done. It emails the results to you.

🔶 Watch a competitor. "Every Monday, search for any new product launches, price changes, or review trends for [brand], and send me a summary."

🔶 Take the pulse of your niche. "Every Friday, search for news in [category]: new entrants, waitlists, preorders, big price moves, and send me a short summary."

🔶 Keep an eye on your own brand. "Every week, search for mentions of [your brand] across news, forums, and social, and flag anything I should see."

It searches the public web. It is not looking inside Amazon, so it will not catch BSR shifts or ad changes. For keeping up with public news on a competitor or a category, it is great. For your own account data, you still go to your reports (or, as above, a skill that reads them).

Have you tried Schedules yet? What would you point it at? Hit reply and let me know!

🔶 The market is shifting from "tokenmaxxing" to efficiency. Buyers are done paying for raw power and want right-sized model spend instead. The same logic behind picking the cheapest model that gets the job done.

🔶 Alexa+ can now close a sale inside the ad itself. New agentic ads on Echo Show let a shopper buy through a spoken conversation, no click and no second screen. The funnel is shifting under our feet. (June 23)

🔶 Prime Day 2026 set a spending record, but with smaller carts. Record transactions, lower average order value than last year. More buyers, thinner baskets, tighter margins to manage. (June 27)

We hope you liked this edition of the AI for E-Commerce Newsletter! Hit reply and let us know what you think! Thank you for being a subscriber! Know anyone who might be interested to receive this newsletter? Share it with them and they will thank you for it! 😃 Ritu