🗞️ Flip Your Ad Ops into AI Ops💥🚀

At PPC Ninja we’ve always been obsessed with one thing. Helping brands squeeze every last drop of efficiency from their ad dollars. Advertising is at the core of what we do. But lately we’ve been building a new kind of muscle too. AI powered DIY apps that supercharge the way we run our operations.

Why? Because ad management today is not just about setting bids and writing copy. It is about speed. Scale. And giving teams the tools to move faster than their competitors. That is exactly why we have been experimenting with low code no code builds. Turning messy workflows into clean automated apps that do the grunt work for us and for our clients.

Over the past couple of weeks we rolled out a series of these apps using AI, specifically Claude Artifacts. Think of them as the secret productivity layer sitting on top of our PPC management. Let me show you a few as ideas that you can easily implement without coding.

No-Code App: Negative Keyword Generator

Simply feed it any product description (Title + Bullet points) and the AI spits out the most probable negative keywords. Clean, relevant, and exportable as a CSV at the end. Wow.

For example, I pasted in the product description for this product to the Negative Keyword Generator tool:

And I got this back. Look at the detail, and it’s fully interactive! Select/Deselect words as you see fit.

So, how does it work?

Once the user uploads the product description, Claude uses AI and semantics to figure out the most likely incorrect categories of words that could get you to spend more dollars than you need to.

It then generates a bunch of negative words by category. The good thing is that a human can look at this generated list and select or deselect words as they see fit. This is GREAT for your broad, phrase and auto-campaigns.

At the end it gives me the ability to download my negative keywords as a CSV.
AH-MA-ZING!!

Search Term Normalizer

Another tool we created was for normalizing Search Terms. What is normalization?

Normalization is the process of cleaning up keyword lists so only the most relevant and deduped terms remain. It works like this. Strip out superfluous words. Consolidate singular plural variations since ads treat them the same so why keep both. Standardize the format so the list is tight, lean, and usable.

The result is a streamlined keyword list that cuts the noise and keeps only what matters. It ever prioritizes those word variants that have a higher search volume.

Here’s a real output. On the left, you see the normalized terms: a clean list of high-value keywords that are ready for use. On the right, the discarded terms: duplicates, reordered phrases, and plural/singular overlaps that would have only cluttered the account.

In other words, normalization trims the fat. Strip out superfluous words. Consolidate singular plural variations. Standardize the format so the list is tight, lean, and usable.

And the reason I’m showing you this is not just to geek out over tidy keyword lists. It is to spark your creativity. 

There are surely a million tasks like this in your workflows that you repeat over and over again. Don’t do that! Start building with Claude artifacts or any other low code no code setup. Get your productivity back. Free up your time. And ultimately make more money where it matters most—the bottom line. Try it!

Legacy ChatGPT Models Are Back!

Thought they were gone for good? Not quite. After enough noise (thank you Reddit), OpenAI quietly rolled the old models back into your account.

Here’s how to find them:

1. Go to Settings → General.

2. Toggle Show additional models.

Voilà. Your favorite legacy models are now just a click away.

Oh, and while you’re in there, one more pro tip: under Data Controls, you can opt out of “Improve the model for everyone” if you’d rather keep your chats out of OpenAI’s training pool.

Old friends restored. Privacy optional.

Everyone’s talking about AI-native checkout like it’s a breakthrough.

But as Joe Kaziukėnas lays out, we’ve seen this movie before—Google, Facebook, Instagram ALL launched native checkout, only to kill it quietly. Not because the tech didn’t work, but because users didn’t trust it, merchants didn’t adopt it, and platforms weren’t really incentivized to make it stick.

Now AI assistants are flirting with the same idea. But unless they solve for context, trust, and actual community behavior, they’re just rebooting a failed feature with better language models. What do you think? Read the full post:

Super excited to be on the Dream 100 panel for the Billion Dollar Seller Summit (BDSS 12 Virtual). This is MUST attend event for e-Commerce brands. Don’t miss it!

I’ll be Speaking at the Amazon Accelerate Pre-Conference Workshop for Partner Agencies and Brands

When: Sep 15, 2025
Seattle

AI Workflow Automations for Scale
Missed the event? Click here to purchase the replay.

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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? Ask them to subscribe here: www.ppc-ninja.com/subscribe. They will thank you for it 💥💪!!

~Ritu